Application Requirements

2.1 C-IoT Landscape

Advancement of technologies will continue to accelerate the evolution of IoT (Internet of Things), impacting many areas that will touch our lives.

In order to address technology and standards that are driving the collaborative Internet of Things (C-IoT), we introduce a C-IoT model that will be used as an illustration throughout the book. The model will be used to describe business apps requirements, define high-level architecture solution, and enabling technologies and protocols.

2.1.1 C-IoT Model and Architecture Layers

Figure 2.1 describes a generic C-IoT model consisting of three layers: Sensing, Gateway, and Services. Sensing Layer

This layer enables interface to objects that are currently passive and where tapping into these objects will generate a stream of data and information that matter to IoT for enterprise for any given market and individual. Gateway/Aggregation Layer

This layer enables the stream of data to move from one level to the next for additional processing. For example, this can be for moving from body area network (BAN), personal area network (PAN) to home area network (HAN) or from HAN to local area network (LAN) or from LAN to wide area network (WAN).


Figure 2.1 C-IoT model Service Layer

This layer provides insights on the data collected from all layers and offers the insights as services to Individuals, Industries, or Infrastructures.

2.1.2 C-IoT Model and Enabling Technologies

Figure 2.2 describes and elaborates on C-IoT model with several attributes:

1. On the right-hand side of the triangle are Processing (MCU/MPU (microcontroller unit/microprocessor unit)), Connectivity (BAN/LAN/WLAN/WSN/WAN), storage (Server), and data analysis (Big Data/Analytics) in the three layers Sensing, Gateway, and Services.

2. On the left-hand side is the architecture view Physical, Virtual, and Cyber, highlighting enabling technologies and protocols.

Connectivity “C” exists throughout all the layers.

Several technologies and standards contribute to realizing building blocks architecture solution in these layers, enabling building smarter C-IoT solutions. Sensing Layer

This layer enables interface to objects that are currently passive and where tapping into these objects will generate a stream of data and information that matter to IoT for enterprise for any given market and individual.


Figure 2.2 C-IoT elaborate model

Building Blocks

Wireless meters and sensors. Affordable wireless sensors and meters can now be used to monitor automated building equipment and relay data to a centralized remote command center. Gateway/Aggregation Layer

This layer enables the stream of data to move from one level to the next for additional processing and services. Examples include BAN, PAN, LAN, and WAN.

Building Blocks

· Internet. The advent of the Internet and decreasing costs of data transmission now makes it financially feasible to transmit data from millions of building data points to the command center.

· Open Data Communication Protocols. Emerging networking standards such as Software Defined Networks (SDNs), Network Functions Virtualization (NFV), and SDx (Software Defined anything) for things like Storage, Data Center, and others are ways to help manage the configuration and operations of the network without the need to know the physical configuration. The trend is arriving to a platform that consists of products from different vendors that can interoperate. This enables moving away from vendor’s proprietary protocol and places more emphasis on operating a heterogeneous network and support of cross-platform data sharing. Such a standardized and secure platform represents a significant milestone in the evolution of the IoT, and enables service providers to quickly and cost-effectively introduce differentiating IoT services. Service Layer

This layer provides insights into the data collected and offers the insights as services to the enterprise or individual.

Building Blocks

· Cloud Computing. The relatively affordable high-capacity computing power of the cloud allows for cost-efficient data analysis to an extent not possible in previous eras.

· Powerful Analytics Software. The best new-generation smart solutions provide numerous dashboards, algorithms, and other tools for interpreting building data, identifying anomalous data, pinpointing causes, and even addressing some issues remotely.

· Remote Centralized Control. Secure Internet technologies can be used to protect data transmissions from hundreds of buildings in a company’s portfolio to the central command center, staffed around the clock by the facility’s professionals.

At each of the above layers, there are a set of protocols and standards that empower each layer. Following are descriptions of protocols and standards that impact the evolution of the C-IoT model.

2.1.3 Definition of Key Elements

Following is a list of terms and components associated with the C-IoT Architecture Model and specifically with the three layers Sensing, Gateway, and Services supported by illustrations and examples where appropriate. Sensing Layer


There are six sensors that we see embedded in many applications.

The sensor kit supports six common types of sensors:

· IR (infrared) temperature sensor

· Humidity sensor

· Pressure sensor

· Accelerometer

· Gyroscope

· Magnetometer.

The first three sensors measure environmental conditions important to practically all devices located in the field. The IR temperature sensor, for example, warns if a device’s motor is overheating. A humidity sensor can detect if moisture is penetrating a waterproof casing and a pressure sensor can report on either excessive or substandard pressure. Taken together, these sensors can form powerful tools like a remote weather station.

The accelerometer and gyroscope are especially important to mobile instruments, as they allow a device’s motion to be tracked independently of GPS (global positioning system) or other external location measurements. Most smartphones already have these features, but the sensor kit handles a wider range of conditions than most smartphone components. Finally, the magnetometer measures magnetic fields and electric currents, providing a safe means of remotely monitoring electric grids and power generators.

Microelectromechanical Systems

MEMS, standing for microelectromechanical systems, is a system with many small devices such as sensors, actuators, switches, robots, or other devices that can detect, for example, light, temperature, vibration, magnetism, or chemicals. They are usually operated wirelessly on a computer network and are distributed over some area to perform tasks, usually sensing through radio-frequency identification. Without an antenna of much greater size, the range of tiny smart dust communication devices is measured in a few millimeters and they may be vulnerable to electromagnetic disablement and destruction by microwave exposure.

The following are examples of applications/services:

· Integrated Work-Order Management. Today’s building management systems can be integrated with a work-order system to streamline communications with on-the-ground facilities staff when human attention is required.

Radio-Frequency Identification

In the IoT paradigm, many of the objects that surround us will be on the network in one form or another. Radio-Frequency Identification (RFID) and sensor network technologies will rise to meet this new challenge, in which information and communication systems are invisibly embedded in the environment around us.

A radio-frequency identification system uses tags or labels attached to the objects to be identified. The tag can be a serial number, a license plate, or product-related information such as a stock number, lot or batch number, production date, or other specific information.

RFID systems can be classified by the type of tag and reader. A typical operation consists of an RFID reader that transmits an encoded radio signal to interrogate the tag. The RFID tag receives the message and then responds with its identification and other information.

RFID tags can be passive, active, or battery-assisted passive. An active tag has an on-board battery and periodically transmits its ID signal. A battery-assisted passive tag has a small battery on board and is activated when in the presence of an RFID reader.

Tags may either be read-only, having a factory-assigned serial number that is used as a key into a database, or may be read/write, where the system user can write object-specific data into the tag. Field programmable tags may be write-once, read-multiple; “blank” tags may be written with an electronic product code by the user.

RFID tags contain at least two parts: an integrated circuit for storing and processing information, modulating, and demodulating a radio-frequency (RF) signal, collecting DC (direct current) power from the incident reader signal, and carrying out other specialized functions; and an antenna for receiving and transmitting the signal. The tag information is stored in a nonvolatile memory. The RFID tag includes either a chip-wired logic or a programmed or programmable data processor for processing the transmission and sensor data, respectively.

Recently, decreased cost of equipment and tags, increased performance to a reliability of 99.9% and a stable international standard around UHF (ultra high frequency) passive RFID have led to a significant increase in RFID usage.

Global Positioning System

The GPS is a space-based satellite navigation system that provides location and time information. Commercial GPS software is available on various devices such as mobile phones and tablets. Although GPS-enabled smartphones are gaining ground in the portable navigation market, the standalone portable navigation device (PND) is far from dead. In fact, today’s PNDs sport more features than ever to help you get from point A to point B quickly and safely – features such as audible driving directions with text-to-speech (TTS), spoken street names, real-time traffic updates, Internet connectivity for points-of-interest search, and large easy-to-read screens, to name a few.

White Space

Spectrum sharing and cognitive radio create new wireless services.

White Space is the name that has been given to unused TV channels in various locations around the United States and in some other countries. The unused channels can be deployed for other communications purposes, making free spectrum useful. Sometimes called TV White Spaces (TVWSs), these channels can be repurposed as needed. TWWS is called Super Wi-Fi and White-Fi as well.

Some standards for White Spaces have been developed, including IEEE (Institute of Electrical and Electronics Engineers) 802.11af, 802.22, and Weightless. The 802.11af is based on the existing Wi-Fi® standards but modified for the White Space bands. Wi-Fi, Bluetooth®, ZigBee®, cordless phones, microwave ovens, and many industrial products currently share the band from 2.4 to 2.483 GHz.

White Spaces are becoming an enabler for the IoT. The White Space spectrum could be used for connecting devices where infrastructure becomes intelligently interconnected allowing collected information to be passed between traditionally disconnected devices and hardware (referred to as machine-to-machine communication or M2M).

For example, cars could communicate with each other, warning drivers of stationary vehicles along their path that would otherwise not be visible due to traffic. Cars could also connect to the road infrastructure for traffic management, allowing intelligent adjustment of speed limits and traffic patterns to eliminate the stop–start traffic congestion often seen on motorways and ensuring a higher average speed and shorter average journey times.

Devices such as mobile phones and tablets could use the free spectrum by knowing which frequencies are available, at what power levels, and at which times of the day in a particular location.

Designed for IoT and White Space with the following considerations [1]:

· Deep indoor coverage with low transmit power

· Unlicensed operation bringing an interference risk that requires frequency hopping to mitigate

· Long battery life implying a sleep mode with periodic awakening (e.g., every 15 min)

· Base station processing to be moved to the core network

· The core network to be implemented in software running in the cloud.

Figure 2.3 shows IoT and White Space Flow Architecture.


Figure 2.3 IoT and White Space flow architecture

IP Camera

An IP camera is the information source provider of the video security system based on IP network. It becomes more and more sophisticated with high-quality optics and also digital video accuracy.

Mainly three functions are important in an IP camera:

· Pixel resolution. Pixel resolution such as high-resolution 720p is already available. Full HD is coming in the near future.

· Compression rate andH.264 AVC is also mature enough now and SVC (scalable video coding) will come soon.

· Performance head room for Video Content Analysis.

A32-bit CPU (central processing unit) at 400 MHz is a minimum requirement now to perform any image processing in addition to the IP encapsulation.

Wireless/Cellular Network Connectivity

Bluetooth: Bluetooth is a short-range wireless with a range typically limited to 30 ft; it uses 2.4–2.48 GHz and a frequency hopping spread spectrum for transmission.

ZigBee: ZigBee is a low-power wireless communications technology designed for monitoring and control of devices and is maintained and published by the ZigBee Alliance. Home automation is one of the major market areas. ZigBee works on the IEEE 802.15.4 standard, in the unlicensed 2.4 GHz or 915/868 MHz bands.

ZigBee IP: ZigBee IP is the first open standard for an IPv6-based full wireless mesh networking solution, providing seamless Internet connections to control low-power, low-cost devices and connecting dozens of different devices into a single control network.

6LoWAPN IP: 6LoWPAN (IPv6 over Low-Power Wireless Personal Area Network) (defined in RFC 6282 by IETF) is connecting more things to the cloud. Low-power, IP-driven nodes, and large mesh network support make this technology a great option for IoT applications. 6LoWPAN is a networking technology or adaptation layer that allows IPv6 packets to be carried efficiently within small link layer frames, such as those defined by IEEE 802.15.4.

6LoWPAN only specifies operation of IPv6 over the IEEE 802.15.4 standard; edge routers may also support IPv6 transition mechanisms to connect 6LoWPAN networks to IPv4 networks.

The 6LoWPAN standard from the IETF now enables IP communication over any low-power wireless or even wired (e.g., PLC) medium. We now have standards for 6LoWPAN over IEEE 802.15.4 (the ZigBee IP standard), 6LoWPAN over IEEE 802.15.4 g (the ZigBee NAN standard), BT Smart, and PLC communications. These networks are typically designed for payloads under 127 bytes.

Other Considerations

ZigBee versus Z-Wave: According to the ZigBee Alliance, ZigBee Home Automation offers a global standard for interoperable products. Standardization enables smart homes that can control appliances, lighting, environment, energy management, and security as well as the expandability to connect with other ZigBee networks.

On the other hand, Z-Wave is described as a wireless RF-based communications technology designed for control and status reading applications in residential and light commercial environments. Target applications for Z-Wave are home entertainment, lighting and appliances control, HVAC (heating, ventilation, and air-conditioning) systems, and security.

Thus, both technologies address similar environments and applications. However, there are some differences both in the physical layer (PHY) and RF.

Z-Wave took the Sub-1 GHz approach, which has superior range versus the 2.4 GHz approach of ZigBee. However, Sub-1 GHz home automation requires different SKUs for different regions.

Z-Wave uses frequency-shift keying (FSK) modulation, which is good enough for the Sub-1 GHz environment. ZigBee is based on direct sequence spread spectrum (DSSS), which is a more advanced and robust modulation.

Protocol Aspects. Both ZigBee and Z-Wave support mesh network topology, which is a strong requirement toward the revolution of “IoT.”

Body Area Network/Personal Area Network

A BAN, also referred to as a wireless body area network(WBAN)ora body sensor network (BSN), is a wireless network of wearable computing devices. BAN devices may be embedded inside the body, implants, surface-mounted on the body in a fixed position wearable technology or accompanied devices, which humans can carry in different positions. The development of WBAN technology started around 1995 around the idea of using wireless personal area network (WPAN) technologies to implement communications on, near, and around the human body. About 6 years later, the term “BAN” came to refer to systems where communication is entirely within, on, and in the immediate proximity of the human body [2].

Local Area

· 802.11b

· 802.11g

· 802.11a

· 802.11n

· 802.11ac

Spectrum: 2.4 and 5.8 GHz Unlicensed bands.

Channel Bandwidth: 20 MHz.

Modulation technologies:

· CDMA: 80211b at 2.4 GHz

· OFDM: 802.11a at 5.8 GHz, 802.11 g at 2.4 GHz.

Security is via station authentication.

Maximum range ~100 M with clear LOS in LAN configuration. Some specialized point–point applications are up to 20 km.

Table 2.1 provides frequency and maximum data rate for 802.11x.

Wi-Fi Alliance is an organization of vendors and users that provides interoperability standards and testing to equipment compliant with IEEE 802.11 standards.

802.11ac increases the maximum data rate for a single client quite a bit compared to 802.11n. Most of the first 802.11ac access points use triple-stream MIMO (multiple input, multiple output), similar to today’s top-end 802.11n access points, but have a maximum data rate of up to 1.3 Gbps. The increase comes from using 80 MHz channels and a new modulation scheme (256 QAM (quadrature amplitude modulation)). As the technology matures, the maximum data rate will further increase by taking advantage of even more MIMO streams, but that will not come for some time. See Figure 2.4 comparing data rates for different 802.11’s.

Note that the above figure compares 802.11ac 80 MHz channels with 802.11n 40 MHz channels.

802.11ac will only work on the 5 GHz band. Nearly every wireless client supports the 2.4 GHz band, but unfortunately the band suffers from high interference levels and is quite crowded. In nearly all environments, the 5 GHz band does not suffer from as much interference or crowding as the 2.4 GHz band, and 5 GHz has more spectrum available for Wi-Fi channels. 802.11ac channels will be 80 MHz wide (compared to the 20 or 40 MHz channels of 802.11n), with the option to spread out to 160 MHz channels in the future, although at double the channel bandwidth compared to 80 MHz, there will only be half as many channels.

The speed, capacity, and performance improvements 802.11ac offers over 802.11n promise several compelling benefits to the enterprise. 802.11ac is well suited to handling streaming video, making it ideal for enterprises becoming increasingly reliant on video conferencing and collaboration and for enterprises that need to preserve service for streaming media and data-intensive applications. Additionally, as BYOD continues to grow its foothold in the enterprise, 802.11ac will help support the larger numbers of devices connecting to corporate WLANs (wireless local area networks). Recent releases of consumer mobile devices, such as those running iOS and Android operating systems, offer 802.11ac compatibility to maximize performance.

Table 2.1 802.11x






Frequency (GHz)






Max data rate

11 Mbps

54 Mbps

54 Mbps

450 Mbps

1.3 Gbps


Figure 2.4 Comparisons of data rates among 802.11g,n,ac

Wide Area

· 2G/2.5G




· 4G – LTE and WiMax

Table 2.2 illustrates the up/down link rates for different cellular generations.

More wireless specifications about communication technologies are provided in Table 2.3.

Table 2.2 Cellular DL/UL rates






80 kbps

237 kbps

384 kbps

Up to 7.3 mbps


20 kbps

59 kbps

384 kbps

Up to 5.4 mbps

Table 2.3 Wireless technologies and attributes




Bluetooth LE







2.5–3.5 G


400 Kbps

400 Kbps

700 Kbps

1 Mbps

1 Mbps

11–100 Mbps

250 Kbps

40 Kbps

250 Kbps

11–100 Mbps

1.8–7.2 Mbps


< 10 cm

< 3m

< 30 m

5–10 m

1–30 m

4–20 m

10– 300 m

30 m

800 m (sub-GHz)

50 km

Cellular net


Very low

Very low


Very low

Very low

Low– high

Very low

Very low

Very low



Are 3G, Wi-Fi competing technologies? Which technology is more cost effective? Will a convergence take place in the future? What is the timeline for these three technologies and their impact on key deployments? The papers [3, 4] take a closer look at each of these technologies and compares market potentials, deployment costs, potential applications, and areas of competitive threat, co-existence, and potential convergence. The papers conclude with examples of efforts taken by operators to deliver what is perceived to be the best, most cost-effective solution to customers.

LTE is a key technology enabler that will have impact on the entire telecom supply chain. LTE impact affects semiconductor SoC, communications networking infrastructure, mobile devices, applications, and quality services transforming means of communications to a new level – higher speed, multimedia content, and enriching personal experiences. The paper [5] covers a number of important topics covering the needs for LTE, LTE market positioning and benefits, LTE market trends, deployment and applications, and LTE roadmap. The paper concludes with an example of enabling differentiated solution for LTE.

SOC architecture is an important building block of wireless solution. Advancement in SoC architecture has bridged the gap between semiconductor vendors, equipment vendors, and service providers. The presentation will address evolution in SoC in the past decade focusing on multicore, security, and power management as key SOC architecture factors for a scalable SOC platform. The paper [6] provides an example of base station on chip that supports multiple standards including LTE, integrated powerful MPU, DSP, and accelerator cores in a heterogeneous, many-core implementation. Gateway Layer


With increase in the number of enabling devices to connect to the Internet, IP address range need to be increased from IPv4 to IPv6. For example, smart meters can now have an IP address. This in turn will enable new applications such as IPv6 used in smart grid enabling smart meters and other devices to build a micro mesh network before sending the data back to the billing system using the IPv6 backbone. Other examples can be (but not limited to) automation and entertainment applications in home, office, and factory environments. The header compression mechanisms standardized in RFC6282 can be used to provide header compression of IPv6 packets over such networks.

Semiconductor Moore’s Law and IoT

The International Technology for Semiconductor Roadmap (ITRS) has assumed the validity of Moore’s law traced back to a paper by Gordon Moore in 1965. Since 1970, the number of components per chip has doubled every 2 years. This historical trend has become known as “Moore’s Law.” As a consequence of this trend, the miniaturization of circuits by scaling down the transistor has dramatically decreased the cost per elementary function (e.g., cost per bit for memory devices, or cost per MIPS (million instructions per second) for computing devices); this has been the principal driver for the semiconductor technology roadmap for more than 40 years.

The industry is now faced with the increasing importance of a new trend, the need to combined digital and nondigital functionalities in an integrated system. This is translated as a dual trend in the ITRS: miniaturization of the digital functions (“More Moore”) and functional diversification (“More than Moore”) introduced in 2007 ITRS publications. “More Moore” continues with geometric scaling to improve density, performance and reliability, and equivalent scaling, including novel design techniques and technology such as multicore design as a continuation of “Moore’s Law.” “More than Moore” allows for the nondigital functionalities (e.g., RF communication, power control passive components, sensors, and actuators). Thus, the new guidance from ITRS becomes more relevant to IoT and understanding processor, system trends, and impact on industry and applications [7]. Figure 2.5 shows Moore’s Law and More.


Figure 2.5 Moore’s Law and More

Continuous miniaturization enables the integration of increased number of transistors on a single chip – system-on-chip (SoC). In 2007, the ITRS System Driver working group identified the SOC driver to include MPU, embedded memory, accelerators, I/O, floating points rise above the MPU driver. The networking driver, which includes SoC and software that target the embedded networking space, represents the rich integration of both “More Moore” and “More than Moore.” A brief description is provided in the ITRS 2007 – System Driver publication [8]. More details can be found in a white paper written on the subject [9]. Future work can align more IoT to SoC and become part of the ITRS System Driver evolution.

Semiconductor SoC and Virtualization

The trend continues toward more powerful embedded systems with multicore processors and SoCs. Virtualization presents opportunities to reduce hardware costs and power consumption while enabling new platform-level capabilities. It allows a device to run multiple operating environments and share the underlying processing cores, memory, and other hardware resources.

The term “virtualization” is overused and needs to be broken down to hardware and software to clearly see which virtualization technologies are most relevant to embedded systems developers.

Hardware virtualization provides a more efficient mechanism for partition/OS switching and hardware resource allocation for a software-virtualized environment. Software virtualization takes advantage of hardware mechanisms to provide a platform, which enables embedded system designers to flexibly partition their systems and run a variety of operating systems. Combining multicore and virtualization, silicon suppliers and third parties have more options for enhancing platform performance, security, and usability.

More details are described in the paper [10].

Cyber-Security and Internet of Things

Recently, as many as 800 million digital records such as credit and debit card details were hacked or lost. According to a recent estimate by the Center for Strategic and International Studies (CSIS), the cost to global economy of cyber-crime and online industrial espionage stands at $445 billion a year. Security software for connecting objects/things to the Internet tends to be rudimentary. This can cause risks involving personal safety, car operations, hacking medical devices, and smart appliances. There is a need to apply high standards of security. The task of protecting both data and people is facing multiple threats. This will even be more challenging in the context of using open source and Big Data/Analytics. The risk is compounded by a number of other trends, including telecommuting, the Bring Your Own Device phenomena, wearable smart devices, and the growth of sensitive data within organizations.

Security Standards for Wi-Fi


Provides weak security

Requires manual key management


Provides dynamically generated keys

Provides robust security for small networks


Requires manual management of pre-shared key

Provides robust security for small networks


Requires configured RADIUS server

Provides dynamically generated keys

Software Defined Network (SDN)/Network Functions Virtualization

Over the past 5 years or so, it was easy for developers to embrace the cloud without dealing with the plumbing and wiring IT typically deals with. For IT to embrace the cloud, they need a more agile, enabling technology platform. SDN becomes a gateway to that reliable off-premises solution. Further, addition of security and other application services in the Layer 4–7 realm – by companies such as F5 – will deliver a holistic solution that works like a cloud environment but can be wired up in a way that IT can understand, trust, and embrace.

The new realities of a maturing SDN – combined with software-defined application services – will change the perception of the possible and result in enterprise IT solutions that look a lot more like consumer-oriented Web properties such as Netflix, Etsy, and Digg.

A big factor is SDN, which is going to be a key, underpinning element to this shift. The plumbing that runs beneath application and layer 4–7 architectures needs to be agile enough to support the elasticity and structure of the cloud as a run-time environment. While L4–7 technologies and the cloud have afforded a more fabric-based environment aligned with what the cloud promises, core switching has been a bit behind.

SDN is a new architecture that has been designed to enable more agile and cost-effective networks. The Open Networking Foundation (ONF) is taking the lead in SDN standardization, and has defined an SDN architecture model as depicted in Figure 2.6. SDN has three layers: Infrastructure layer (physical layer), Control Layer (Logical Layer), and Application Layer [11].

The key benefit of SDN is to automate network provisioning, monitoring, and control. This will include automate traffic monitoring and control over Layers 2 and 3, secure flow update, and L2/L3 GRE over IPSEC.

The Network Functions Virtualization concern is to automate distribution of network services across network appliances as virtual machines (VMs) that provide isolation (safety) across VMs. Examples of distributing L4–7 network services include Firewall, VPN (virtual private network)/IPSec, Deep Packet Inspection (DPI), and Intrusion Detection system/intrusion prevention system (IDS/IPS). Automated VM migration can be deployed for load balancing and improving resource sharing. Figure 2.7 shows NFV positioned at higher level than SDN and focus on handling of network services across network appliances.


Figure 2.6 ONF/SDN architecture


Figure 2.7 NFV (open stack + OVS)

Geographic Information System

A geographic information system (GIS) is a computer system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data. GISs have transformed the way spatial (geographic) data, relationships, and patterns in the world are able to be interactively queried, processed, analyzed, mapped, modeled, visualized, and displayed for an increasingly large range of users, for a multitude of purposes. Services Layer

Embedded design is becoming more complex as design parameters evolve and demands for quicker time-to-market increase, especially for emerging IoT applications. Working closely with embedded software platform providers enhances the ability to provide the flexibility, reliability, scalability, and ease of use desired by customers developing the next generation of the IoT and graphical user interfaces (GUIs) for a high-performance, connected MCU.

MCU-based embedded solutions offer developers a software strategy based on the “application platform” approach. The approach contributes to expand product ranges, to accelerate specification process, and to improve user experience for markets such as smart grid, smart metering, smart appliances, building and home automation, and other IoT applications.

Embedded Service Switches can collect data from remote locations for real-time analysis by experts located at a remote site or headquarters. They can also help monitor the transit of vehicles and equipment to remote sites. Connected sensors can monitor the condition of the vehicles, cargo or crew, and convey this information to remote data centers or to other vehicles.

Industries are seeing unprecedented levels of automation and supply chain efficiencies as industrial control systems (ICSs) connect to the Internet. The IoT is certain to bring even greater acceleration of connectivity, not only in the production process and supply chain, but throughout all business processes. Businesses that respond to these innovations and move toward improved interconnectivity can become more globally competitive and ultimately lead in their markets.

Big Data

Today, big data is not limited to traditional data warehouse situations, but includes real-time or line-of-business data stores used as the primary data foundation for online applications that power key external or internal business systems.

It used to be that these transactional/real-time databases were typically “pruned” so they could be manageable from a data volume standpoint. Their most recent or “hot” data stayed in the database, and older information was archived to a data warehouse via extract–transform–load (ETL) routines.

But big data has changed dramatically. The evolution of the Web has redefined the following:

· The speed at which information flows into these primary online systems

· The number of customers a company must deal with

· The acceptable interval between the time that the data first enters a system and its time of exit

· Transformation of the data into information that can be analyzed to make key business decisions

· The kind of data that needs to be handled and tracked.

Some analysts such as Gartner have attempted to categorize these changes by describing big data as follows:

1. Velocity. How fast the data are coming in

2. Variety. All types of data are now being captured (structured, semi-structured, unstructured)

3. Volume. Potential of terabytes to petabytes of data

4. Complexity. Involves everything from moving operational data to big data platforms

5. Difficulty in managing the data across multiple sites and geographies.

Metcalfe’s Law

Coined by Robert Metcalfe, the inventor of Ethernet, Metcalfe’s Law states that the value of a network grows by the square of the size of the network. The idea behind this law is that a network’s value is increased as the size of the network increases; this law is often referred to when talking about the Internet’s value. For example, if the network has five machines, its value would be 25 (52 = 25), but if another network had 1000 machines its value would be 1 000 000.

This law is also considered applicable to more than just the Internet or a computer network. For example, a software product may increase in value as it grows in size. If a product only has 25 users, it is less likely to be known and used. However, if the same product has 1000 users, it is more likely to be known and used [12].

As more things, people, and data become connected, the power of the Internet (essentially a network of networks) grows exponentially. By combining people, process, data, and things, the exponential power of the Internet will allow us to create exponential responses to the extraordinary challenges faced by individuals, businesses, and countries.

2.1.4 Requirement Considerations

We present a taxonomy that will aid in defining the components required for IoT from a high-level perspective. There are three IoT components, which enable seamless

1. Sensing: made up of sensors, actuators, and embedded communication hardware

2. Gateways: connectivity and aggregation and virtualization

3. Cloud/analytics for on-demand storage and computing tools for data analytics and application/services. Sensing

Radio-Frequency Identification (RFID)

RFID technology is a major breakthrough in the embedded communication paradigm, which enables design of microchips for wireless data communication. The microchips help in automatic identification of anything they are attached to, acting as an electronic barcode. The passive RFID tags are not battery powered and they use the power of the reader’s interrogation signal to communicate the ID to the RFID reader. This has resulted in many applications particularly in retail and supply chain management. The applications can be found in transportation (replacement of tickets, registration stickers) and access control applications as well. The passive tags are currently being used in many bankcards and road toll tags, which are among the first global deployments. Active RFID readers have their own battery supply and can instantiate the communication. Of the several applications, the main application of active RFID tags is in port containers for monitoring cargo.

Sensing – Wireless Sensor Networks (WSN)

Recent technological advances in low-power integrated circuits and wireless communications have made available efficient, low-cost, low-power miniature devices for use in remote sensing applications. The combination of these factors has improved the viability of utilizing a sensor network consisting of a large number of intelligent sensors, enabling the collection, processing, analysis, and dissemination of valuable information, gathered in a variety of environments [13]. Active RFID is nearly the same as the lower-end WSN (wireless sensor network) nodes with limited processing capability and storage. The scientific challenges that must be overcome in order to realize the enormous potential of WSNs are substantial and multidisciplinary in nature. Sensor data are shared among sensor nodes and sent to a distributed or centralized system for analytics. The components that make up the WSN monitoring network include

1. WSN Hardware. Typically, a node (WSN core hardware) contains sensor interfaces, processing units, transceiver units, and power supply. Almost always, they comprise of multiple A/D converters for sensor interfacing and more modern sensor nodes have the ability to communicate using one frequency band making them more versatile.

2. WSN Communication Stack. The nodes are expected to be deployed in an ad hoc manner for most applications. In designing an appropriate topology, routing and MAC layer are critical for scalability and longevity of the deployed network. Nodes in a WSN need to communicate among themselves to transmit data in single or multi-hops to a base station. Node dropouts, and consequent degraded network lifetimes, are frequent. The communication stack at the sink node should be able to interact with the outside world through the Internet to act as a gateway to the WSN subnet and the Internet.

3. Middleware. This is a mechanism to combine cyber infrastructure with a Service Oriented Architecture (SOA) and sensor networks to provide access to heterogeneous sensor resources in a deployment-independent manner. This is based on the idea of isolating resources that can be used by several applications. A platform-independent middleware for developing sensor applications is required, such as an Open Sensor Web Architecture (OSWA). The Open Geospatial Consortium (OGC) builds OSWA upon a uniform set of operations and standard data representations as defined in the Sensor Web Enablement Method (SWE).

4. Secure Data Aggregation. An efficient and secure data aggregation method is required for extending the lifetime of the network as well as ensuring reliable data collected from sensors. Node failure being a common characteristic of WSNs, the network topology should have the capability to heal itself. Ensuring security is critical as the system is automatically linked to actuators and protecting the systems from intruders becomes very important. Gateways

Addressing Schemes

The ability to uniquely identify “Things” is critical for the success of IoT. This will not only allow us to uniquely identify billions of devices but also to control remote devices through the Internet. The few most critical features of creating a unique address are uniqueness, reliability, persistence, and scalability.

Every element that is already connected and those that are going to be connected must be identified by their unique identification, location, and functionalities. The current IPv4 may support to an extent where a group of cohabiting sensor devices can be identified geographically, but not individually. The Internet Mobility attributes in the IPV6 may alleviate some of the device identification problems; however, the heterogeneous nature of wireless nodes, variable data types, concurrent operations, and confluence of data from devices exacerbates the problem further.

Persistent network functioning to channel the data traffic ubiquitously and relentlessly is another aspect of IoT. Although, the TCP/IP takes care of this mechanism by routing in a more reliable and efficient way, from source to destination, the IoT faces a bottleneck at the interface between the gateway and wireless sensor devices. Furthermore, the scalability of the device address of the existing network must be sustainable. The addition of networks and devices must not hamper the performance of the network, the functioning of the devices, the reliability of the data over the network, or the effective use of the devices from the user interface.

Gateways – Visualization

Visualization is critical for an IoT application as this allows interaction of the user with the environment. With recent advances in touch screen technologies, use of smart tablets and phones has become very intuitive. For a layperson to fully benefit from the IoT revolution, attractive and easy to understand visualization have to be created. As we move from 2D to 3D screens, more information can be provided to the user in meaningful ways for consumers. This will also enable policy makers to convert data into knowledge, which is critical in fast decision making. Extraction of meaningful information from raw data is nontrivial. This encompasses both event detection and visualization of the associated raw and modeled data, with information represented according to the needs of the end user. Services


One of the most important outcomes of this emerging field is the creation of an unprecedented amount of data. Storage, ownership, and expiry of the data become critical issues. The Internet consumes up to 5% of the total energy generated today and with these types of demands, it is sure to go up even further. Hence, data centers that run on harvested energy and are centralized will ensure energy efficiency as well as reliability. The data have to be stored and used intelligently for smart monitoring and actuation. It is important to develop artificial intelligence algorithms, which could be centralized or distributed based on the need. Novel fusion algorithms need to be developed to make sense of the data collected. State-of-the-art nonlinear, temporal machine learning methods based on evolutionary algorithms, genetic algorithms, neural networks, and other artificial intelligence techniques are necessary to achieve automated decision-making. These systems show characteristics such as interoperability, integration, and adaptive communications. They also have a modular architecture both in terms of hardware system design as well as software development and are usually very well suited for C-IoT applications.

2.1.5 C-IoT System Solution – Requirement Considerations

A C-IoT solution is designed to run on classes of hardware devices that are severely constrained in terms of memory, power, processing power, and communication bandwidth. A typical C-IoT solution system has memory on the order of kilobytes, a power budget on the order of milliwatts, processing speed measured in megahertz, and communication bandwidth on the order of hundreds of kilobits/second. This class of systems includes both various types of embedded systems as well as a number of old 8-bit computers.

Understanding power efficiency is also critical as devices (such as wearable devices) are often not connected to power supplies and have to operate using energy harvesting sources or a single battery for several years without maintenance or battery replacement.

In addition to power consumption, connected device developers must consider factors such as system cost, component count, MCU performance, system size, standards, interoperability, security, ease of use, and in-field troubleshooting.

Adding wireless connectivity to remote devices not easily reached by Ethernet cable or power-line communications is another IoT design challenge that can be addressed by embedded developers with RF expertise.

Finally, software is required to bridge connected devices, aggregate sensor data, and present information to end users in an intuitive way via displays or over the Internet to their computers, tablets, or smartphones.

This chapter will focus on establishing IoT networking and architectural requirements utilizing the reference model introduced in the previous chapter.

The requirements will translate into arriving to an IoT energy-efficient device that may include

· Smart Sensing

· MCU platform with built-in wireless capabilities

· Support of a range of operating systems

· Development platform making the device available to entrepreneurs, who can build their own products on top of the design. Smart Sensors

The trend toward a more useful world of connected devices hinges on a new class of smart sensors. Sensor integration and sensor fusion will continue to be the watchwords for these new sensor networks. In turn, more sophisticated sensor systems will rely on a new class of processors – low power and high performance data lower price point needed to enable widespread use. We may expect more everyday devices to become intelligent and networked. Sensor Fusion

From Transducer to System on a Chip

Sensing technology has advanced far from the single-point transducer and bias circuitry. Modern sensor systems can incorporate bias, temperature compensation; signal conditioning, and even filtrations and A/D conversion. What is more, serial-bus multichannel sensor systems on a chip take advantage of fairly high-speed serial protocols such as IIC (Industrial Internet Consortium) and SPI. This reduces the cabling requirements and lets sensor circuitry remain close to what it is sensing to reduce noise.

While more sensors are being integrated into microcontrollers to form smart sensor nodes, multiple sensors are still delivering sensing data that need to be processed and analyzed to result in decision-making and trigger actions.

Sensor fusion is taking hard sensor data and fused with context-aware data such as location and owner data referred to as soft data (who, what, when, where, etc.) to perform situation assessment analysis, following which rule-based/knowledge-based decision-making actions can be taken intelligently at the edge nodes. The C-IoT service platform, which leverages sensor fusion software framework components, will perform ubiquitous sensing and processing works transparent to the user. This will enable the development of C-IoT applications that interoperate among multiple point solutions of Smart things. This will further drive the IoT market products to new heights. Robotic and Sensor Fusion – Requirements

Most modern robots, such as room vacuum cleaner robots and pool cleaners, perform preprogrammed tasks and routines. Sensors are no longer an obstacle when designing a robotic control loop, and can be an integral part of the actuator/control mechanism. Clearly defined sensor types, limits, controls, and safeties are relatively easy to comprehend. But as evolved robots are more able to do complex tasks, the interleaving of sensor data to be used for real-time decision-making becomes more crucial. The fusion of sensory data is where the big picture is looked at rather than an individual control loop.

The requirement for more-capable and less-expensive robots calls for developing real-time control loops for a variety of functions including manipulating spinning, rotation of parts, vibration, and temperature. MCU and C-IoT

The microcontroller is a genesis of the IoT. Over the past few decades, MCUs have been increased in functionality by embedding intelligence into the electronics around them. We are in an era where devices will connect with people and other devices. MCU Low-Power Operation

IoT systems are severely power-constrained. Battery-operated wireless sensors may need to provide years of unattended operation, with little means to recharge or replace their batteries. An IoT system provides a set of mechanisms for reducing the power consumption of the system on which it runs.

The following features characterize the MCUs:

1. Low Power. Need very small operating current (32–80 MHz, NOP instructions). Reduction in power consumption can be further achieved by implementing a low-power “Snooze” mode in addition to the three traditional power management modes (Run, Halt, and Stop). The “Snooze Mode” allows common peripherals (i.e., ADC (analog-to-digital converter) or UART) to operate independently, while CPU is disabled. In this mode, power dissipation can be reduced by over 30% in comparison to an implementation without this mode. In “Halt Mode,” the CPU is disabled, but all peripheral functions are operable. In this mode, with running RTC (real-time clock) and LVD (low-voltage detection), power dissipation is reduced to ~0.5 μA/MHz. In “Stop Mode,” the high-speed clock oscillator and internal high-speed oscillator are disabled, so lowest power consumption is possible. For example, with running WDT (watch dog timer) and LVD, the current is reduced to about 0.5 μA/MHz.

2. Scalability. Offer a wide range of devices, which are available at a wide range of pin packages and different amount of Flash.

3. High Efficiency. – Have high-performance DMIPS (Dhrystone Million Instructions per Second)/MHz. This also calls for a maximum number of instructions to be executed in one clock cycle. This may call for implementing DMA/DTC/ELC functionality. For example, ELC reduces interrupt processing and improves real-time performance.

4. Cost-Saving Features at System Level. A high-precision (±1%) on-chip oscillator (32/64 MHz) makes 32 MHz CPU operation possible, without external oscillators and built-in features such as a reset circuit, LVD, WDT, and data flash with background operation function reduce the system cost.

5. Security Features. Safety features in hardware are required to ensure compliance with IEC/UL (International Electrotechnical Commission) 60 730. Examples include hardware WDT, TRAP instruction, illegal memory access, and frequency detection, Flash memory CRC, RAM parity error detector, RAM and SFR guarding, and A/D converter tests.

6. An Extensive Ecosystem. Offers developers to have access to development tools and kits, third-party network, online resources, engineering community, and online training. Networking IPv6 and IEEE 802.15.4 Design Challenge

IoT solutions provide three network mechanisms: the uIP TCP/IP stack that provides IPv4 networking, the uIPv6 stack that provides IPv6 networking, and the Rime stack that is a set of custom lightweight networking protocols designed specifically for low-power wireless networks. The IPv6 stack was contributed by Cisco and was, at the time of release, the smallest IPv6 stack to receive the IPv6 Ready certification. The IPv6 stack also contains the RPL routing protocol for low-power loss IPv6 networks and the 6LoWPAN header compression and adaptation layer for IEEE 802.15.4 links. The Rime stack is an alternative network stack that is intended to be used when the overhead of the IPv4 or IPv6 stacks is prohibitive.

Mapping from the IPv6 network to the IEEE 802.15.4 network poses additional design challenges [14].

· Addressing Management Mechanisms. The management of addresses for devices that communicate across the two dissimilar domains of IPv6 and IEEE 802.15.4 is cumbersome.

· Address Resolution. IPv6 nodes are assigned 12-bit IP addresses in a hierarchical manner, through an arbitrary length network prefix. IEEE 802.15.4 devices may use either of IEEE 64-bit extended addresses or, after an association event, 16-bit addresses that are unique within a PAN.

· Differing Device Designs. IEEE 802.15.4 devices are intentionally constrained in form factor to reduce costs (allowing for large-scale network of many devices), reduce power consumption (allowing battery-powered devices), and allow flexibility of installation (e.g., small devices for body-worn networks). On the other hand, wired nodes in the IP domain are not constrained in this way; they can be larger and make use of mains power supplies.

· Differing Focus on Parameter Optimization. IPv6 nodes are geared toward attaining high speeds. Algorithms and protocols implemented at the higher layers such as TCP kernel of the TCP/IP are optimized to handle typical network problems such as congestion. In IEEE 802.15.4-compliant devices, energy conservation and code-size optimization remain at the top of the agenda. IoT and Wi-Fi-Based Applications

When it comes to measuring technological performance, it is hard to resist the allure of a simple number. To compare digital cameras, buyers carefully compared megapixel count. For decades, clock speed – megahertz, then gigahertz – served as the universal shorthand for CPU performance. The higher the number the better it is, most people thought.

Of course, this was never true, and that became evident once single-core CPU performance plateaued. Manufacturers began touting their caching, their multicore processors, and their sophisticated bus architectures. The “megahertz myth” slowly lost its power. As a result, CPU developers began competing on the features of their entire platform.

Something similar is happening with Wi-Fi today. With the advent of the 802.11ac standard, Wi-Fi is encountering what we might call its “CPU moment.” In the past, range and throughput were what mattered most in a Wi-Fi solution. But for next-generation Wi-Fi applications, those considerations are no longer sufficient.

That is not to say they are not important. They are critically important. But for emerging applications, like streaming wireless HDTV, rate and range do not mean anything without a third consideration: reliability.

In the past, Wi-Fi was a convenience. You needed it to check your email, work from home, update your iPhone. If you did not get a strong connection in one room, you could always move to another. It was annoying, but you could work around it.

Wireless HD and UHD video are different. Last year, Forrester estimated that nearly 115 million households in the United States owned at least one TV, and the number of households that watched online video on a TV set had increased by nearly 30%. A separate Forrester report estimates 66 million US households will access the Internet via game consoles, Blu-ray players or connected HDTVs by 2017. And increasingly, those connections will be wireless.

Delivering wireless HDTV today (and UHD coming up quickly) with wire-like quality requires a Wi-Fi signal that is fast, yes, but also reliable. According to a report from the OECD, by 2017, “households with two teenagers will have 25 Internet-connected devices.” On the basis of current trends, most of these devices will be wireless, and all of them will contribute to interference.

For laptop users, an unreliable wireless connection might be an inconvenience. For TV viewers it is a potential deal-breaker. If they are having trouble with their picture, they cannot simply move their TV to a different room. They will not tolerate buffering. They will expect their TV to work the way it did when the signal came over cable. And they will expect to have this same experience with multiple TVs running at once.

As the end user’s tolerance for error declines, the differences between Wi-Fi solutions become more important. While 802.11ac is sometimes described as “Wi-Fi for HDTV,” not all 802.11ac solutions are equally capable of delivering an HD signal. These features, such as higher-order MIMO, are equally required to enable the performance in 802.11ac, just as they were in 802.11n. An access point with 4 × 4 MIMO could deliver twice the performance of a 3 × 3 MIMO device at equal transmit power, or the same performance using much less transmit power.

To penetrate walls and navigate around potential sources interference, precision is as important as power. To that end, digital beam-forming will be adopted on wider scale by 802.11ac products going forward. Digital beam-forming, as originally defined in 802.11n, had multiple optional modes, while 802.11ac limits the implementation options to only one, which will enable better interoperability. Digital beam-forming allows a transmitting device to aim its Wi-Fi signal at the receiver rather than broadcasting equally in all directions. This not only improves the Wi-Fi signal’s range, but also its speed. But beam-forming is not a stock commodity. Different 802.11ac solutions from different manufacturers will have noticeably different beam-forming capabilities, determined by algorithms of different quality.

Different Wi-Fi solutions will prioritize HD video differently, as well. Some are effective at managing Wi-Fi streams to ensure that one slow device (often a mobile device) does not slow down the whole network. With others, a single misplaced access point could bring down the whole network. A device with multi-user 4 × 4 MIMO (MU-MIMO) will be even more effective at sending multiple video streams to multiple devices, akin to a wired connection.

Service providers are well aware that the days of “good enough” wireless performance are over. To meet the demands of 1080p HDTV, 4K UHD, and the increasing number of devices connecting to a home network (i.e., the IoT), ISPs are preparing to provide Wi-Fi technology that delivers a flawless high-speed signal for any purpose. Wi-Fi in the home is about to take a huge leap forward. You might not be able to measure it with a single number, but the difference will be unmistakable. Inter-Cloud

A group of interrelated technologies is redefining how we live and work: cloud computing, big data, mobility, and the IoT. The cloud is at the epicenter of all this activity: big data migrates to the cloud to be sliced and diced; today’s tablets, smartphones, and phablets rely on the cloud for services and entertainment ranging from social networking and microblogs to streaming video; and the hyper-connected world of smart grids, biosensors, and connected vehicles will rely on the cloud to collect data and then turn down thermostats, alert physicians, or avoid collisions.

As a result, cloud computing is growing exponentially. The industry is generally viewed as having three major segments: “infrastructure as a service,” where computers and storage are available on an on-demand, pay-per-use rental basis, while residing in a cloud service provider’s data center; “software as a service,” which includes applications accessible over a network such as the Internet, for example, customer relationship management and billing but also voice and video communications and gaming; and a layer in between, referred to as “platform as a service,” which enables developers to rapidly develop and deploy new applications.

A broad variety of companies offer cloud products and services, and just to list the largest ones would use up all of the space in this article. Suffice it to say that there are hundreds of cloud service providers of various sizes, and a rich ecosystem of additional companies that provide chips, networking gear, servers and storage, power distribution equipment, colocation and interconnection facilities, software stacks, management and monitoring tools, consulting services, and so forth.

This rich set of options offers plenty of choice to customers, whether they are consumers or businesses. And, as the cloud moves from early adopters to ubiquity, customers will leverage not just one cloud provider, but many, to solve needs across various business units and functions as well as one-off strategic initiatives.

However, a plethora of providers has its downsides: cost and risk associated with the management of complexity, search costs associated with provider selection, and transaction costs associated with everything from migration to operations.

And, while there will no doubt be some consolidation and organic growth, causing large providers to become even larger, there will also likely be a long tail of mid-sized and small providers that will compete on other factors, such as location, specialized expertise, or customer intimacy. By way of analogy, Walmart, Target, and Albertsons may have a substantial share of the retail market, but there is no shortage of “Mom and Pop” fruit stands. Marriott, Starwood, and Hilton may have a large portion of the global hotel market, but there are plenty of roadside inns and bed and breakfasts.

The IEEE is helping to ameliorate problems associated with incompatibility across multiple providers. The IEEE is a global organization with a charter to “foster technological innovation and excellence for the benefit of humanity.” Among other things, the IEEE has developed hundreds of critical industry standards, including one that we are all familiar with, IEEE 802.11, better known as Wi-Fi. In 2012, the IEEE launched the Cloud Computing Initiative, chaired by Steve Diamond, to facilitate and coordinate cloud computing and big data activities across the breadth of the IEEE. An early focus of the Initiative was the formation of the IEEE P2302™ Inter-cloud standards working group, chartered to develop standards for cloud computing interoperability and federation.

In the same way that proprietary networks were made interoperable and thus easy to use by the Internet, the vision of this effort is for clouds, including proprietary clouds, to be made interoperable and easy to use via the Inter-cloud. The Inter-cloud does not supplant today’s cloud providers; in fact, it should benefit current and emerging providers as well as business and consumer customers.

Analogies from the air travel industry and the Internet can help explain this. While there are hundreds, if not thousands, of airlines and millions of web sites around the world, they have agreed to jointly follow a number of protocols and procedures.

Airlines often need to transfer bags between carriers and the Internet needs to transfer data packets between ISPs. The Inter-cloud will need to reliably transfer applications and data between providers.

Airlines needed to agree on what codes to use for airports and the Internet needed a standard way of using URLs such as “” The Inter-cloud will need mechanisms to uniquely identify cloud service providers.

Travelers must present valid identification documents, payment methods, and boarding passes; the Internet and Inter-cloud both need mechanisms for identification, authentication, and payment.

Airlines want the ability to advertise their available seats and the prices for those seats on a variety of exchanges such as Travelocity and Expedia; web sites want to be found in search results; cloud providers will want to be able to advertise available resources on Inter-cloud exchanges.

The similarities are apparently endless, because abstractly, any service industry – airlines, Internet, retail, hotel, rental cars, telephony, and so on – faces similar challenges, and there are clear benefits to solving these kinds of challenges collaboratively while continuing to compete in other areas. An airline can compete on price, on-time arrival, service quality, and legroom. It does not need to compete based on a better scheme for naming airports.

And, in the same way that a shared mechanism for interline baggage transfer does not obviate the need for airlines, nor a standard mechanism for IP addressing put any web sites out of business, the Inter-cloud will facilitate continued growth of the industry, while increasing customer satisfaction.

The Inter-cloud will benefit service providers because they will be able to more easily partner to share each other’s resources, advertise services to customers, participate in markets and exchanges, and help each other out during emergencies such as outages. It will benefit customers, because they will be able to more easily select from multiple providers, switch providers if one ceases service, offer improved user experiences thanks to a more dispersed footprint for highly interactive applications, and more easily build complex solutions from individual service components. Moreover, the Inter-cloud will take the onus for solving these problems away from users, helping to accelerate cloud adoption.

To help make the Inter-cloud standards a reality, the IEEE recently announced the Inter-cloud Test bed initiative to help evolve and validate the P2302 standard. Emerging standards need to be tested in the real world on real physical networks, servers, storage, and software. And interoperability standards require even more testing, as various combinations of components are evaluated for things like functionality, reliability, and performance. Almost two dozen companies and academic institutions have come together as founding members of this initiative and the test bed and related IEEE-led efforts are open to all who wish to contribute – not only service providers, but equipment vendors, subject matter experts, and end-customers.

The idea is that testing – both abstractly and against emerging customer scenarios – will identify needed improvements in the emerging standard, which can be addressed. These improvements will then be further tested. The Internet took decades to go from a vision of packet switching to where it is today. Between the IEEE, industry, and academia, one can hope that the vision of an Inter-cloud, conceived as early as 2009 by test bed initiative founder and chief architect David Bernstein, cloud computing initiative chair Steve Diamond, and their colleagues, is now getting the attention it deserves. HMI – Touch, Feel, and Control

The Human Machine Interface (HMI) involves the interaction between users and equipment and provides control and operating status but it also defines the “look and feel” of the equipment and applications being used.

The HMI can incorporate many different approaches including switches, TFTs, GUIs, JPEG pictures, and so on. Many can be used together, but with users demanding more advanced control and monitoring options, the use of advanced interfaces is increasing even on the simplest of applications.

2.2 Application Requirements – Use Cases

This section will illustrate the application requirements by selecting some applications from the three market groupings: Individual, Industry, and Infrastructure.

The following are the identified applications:

· Health & Fitness (Lead Example)

· Video Surveillance

· Smart Home & Building

· Smart Energy

· Track & Monitor

· Smart Factory/Manufacturing

· Others: Smart Car, Smart Truck, Drone, Machine Vision, and Smart City.


Figure 2.8 Application sample use cases

Sample applications across the three domains Individual, Industry, and Infrastructure are depicted in Figure 2.8.

2.3 Health and Fitness System for Individual/Industry/Infrastructure (LEAD EXAMPLE)

2.3.1 Landscape

Today, healthcare operates in silos across the three I’s domains:

· Individual. Trying to be in the center striving to live healthy but is confronted with many challenges if he/she falls sick. Such an individual is frustrated because information is scattered, and is confronted with high cost of treatment and exuberant cost of surgery if the person is not covered by insurance.

· Industry. This is represented by here by physicians, clinics, labs, hospitals, and pharmaceuticals. Physicians are transiting from a paper-based system to an electronic system; typically, treat symptoms by prescribing medication, lab tests, and sometimes surgery. In general, physicians do not talk to those involved in alternate/functional medicine to understand the root cause and resort to natural means to restore the body to a healthy condition and strive more toward wellness and prevention.

· Infrastructure. Here this is represented by the Government, which takes long to develop and administer policies and handle disputes between hospitals, physicians, insurance, and individuals. The Government takes time to release new drugs to the market and considers prescription drugs as mainstream, giving little attention in general to functional medicine and wellness.

These Health and Fitness functions and activities operate in silos. Figure 2.9 represents them, where some of the functions are centered on physicians, hospitals, or the Government. An Individual is confronted with a great challenge trying to live a balanced life with focus on Wellness/Prevention and absence of Sickness/Treatment. This is represented by the activities on the right-hand-side (RHS) of the circles versus those activities on the left-hand-side (LHS).

Call for collaborative IoT. As IoT begins to offer ways to have access to data resulting from sensing and other sources, tools gain insight from the accumulated set of data. This will result in expanding these applications representing a single solution to the other domains. Then, we start seeing these apps/systems representing these activities communicate and interconnect the physician’s functions with those of functional medicine and determine the best course of action for either wellness and prevention or diagnosis and treatment.


Figure 2.9 Health and fitness domains – today


Figure 2.10 C-IoT health and fitness domains – future

The future vision of Collaborative Internet of Things (C-IoT) empowering Health and Fitness is shown in Figure 2.10; which shows breakdown of the silos and enables collaboration among different IoT apps spanning the three domains and collaborating between Wellness/Prevention (RHS) and Sickness/Diagnosis/Treatment (LHS). The paradigm shift will result in placing the Individual in the center assessing all options and making informed decisions. General Observations

· Medical clinics, hospitals, physicians, and nurses are experiencing a new wave of automation of patient records. Sharing of information with other agencies requires compliance with the Privacy Act. IoT is helping the medical community to connect medical devices to the Internet and enable monitoring and tracking important information about patient.

· IoT is also playing an increasing role in the lives of individual where several initiatives have started allowing an individual to start monitoring and tracking health signs and fitness readouts about himself/herself that was never possible before.

· Such information will be of value not only to the individual but also to the physician under sickness condition. If surgery is required, then can the physician and patient view the readout from lab tests, along with tracking and recoding vital information about the patient? In addition, if a surgery is recommended, can pricing of surgery and insurance coverage be viewed by the patient for making a decision? Connecting these systems to establish a bigger picture is what IoT can enable over time.

· The Government plays a vital role in administering healthcare, connecting with physicians, insurance agencies, and administering Medicare/Medicaid services and policies and procedures.

· On the wellness/preventive side, IoT is also empowering individuals to monitor their burned calories, sleeping habits, and other factors. As technology advances and common platform development is in place, more IoT-based apps will be deployed connecting medical with wellness. Both will be aimed to ensure that the individual has a quality of life by being connected with all the parties concerned such as medical clinics, labs, pharmaceutical, hospitals, therapy, insurance providers, recreation centers, alternate medicine, and natural food stores.

· There are now 100 000 apps that are available in the Health & Fitness and Medical fields supported by platforms from Apple and Android. Both platforms are by far the leading mobile operating systems for mobile health apps today [15].

· The biggest group of mobile health apps is categorized as fitness apps. More than 30% of all apps that are listed in the Health & Fitness and Medical apps sections of Apple App Store, Google Play, BlackBerry Appworld, and WindowsPhone Store are fitness trackers or exercise guides.

2.3.2 Health & Fitness Sensing Requirements Wearable Devices

Portable and wearable computing promise to introduce major shifts in how humans interact with computing devices and information, dramatically reducing the gap between immediate information and the person for whom that information is the most useful.

These small wearable devices come in the form of smart bracelets, smart watches, smart eye-glasses, smart T-shirts, smart shoes that are equipped with location sensors (RFID, NFCs (near-field communications), GPS) that track assets (kids, pets, elderly) as well as sensors for tracking health fitness biometrics (pulse, blood pressure, temperature, pedometer, etc.). Wearable wireless health devices also include accelerometers to warn of falls, and insulin pumps and glucose monitors for diabetics.

2.3.3 Health & Fitness Gateway Requirements

The adoption level shows an increasing trend and there will be more takers for these devices in the future. It is also evident that several software, service, and product companies are showing interest in connecting devices with a view to make their primary product or service more attainable.

Health fitness has many different dimensions of measurement, that it would be hard-pressed to imagine anyone spending an inordinate amount of time documenting these dimensions manually on their smartphones at frequent intervals. This is where the role of wearables comes in.

Wearable wireless fitness devices (bands) are another addition to the IoT. These connected bands take vital data from the body throughout the day and transmit wirelessly to user devices such as computers, smartphones, and tablets. These bands provide vital data to an individual and they are indeed a great tool to reduce medical expenses; health insurance companies too are taking interest in promoting them. Each of these devices can issue an alert to their physician by triggering a call over the cellular network.

Analysts expect the wearable computing device market to grow in the coming years. Juniper Research said in a report that the number of device shipments will increase from about 15 million devices in 2013 to 150 million devices by 2018.

2.3.4 Health & Fitness Service Requirements

C-IoT is gradually taking part in every facet of our lives. There is a high level of adoption of medical devices that are connected to the Internet and to each other. The recent emergence of a variety of wireless monitoring services is reaffirming this fact. Several connective devices have been already established in the healthcare industry.

Wearables need to go beyond simply measuring steps, heartbeats, and sleep cycles and attain the ability to measure the mood of individuals.

Today, a handful of companies produce wearable devices to detect brainwaves that infer how calm or attentive a person may be. With further growth in this area, sensors that are powerful enough to stream brainwave signals in real time will be developed. The form factors of these devices would also be compact enough so as to be inconspicuous. Individual – Wearable Devices (e.g., Fitbit)

Consumers are now connecting their physical bodies to electronic devices such as Fitbit and other health monitors. Devices such as the Fitbit come with iOS and Android apps, include capabilities for social sharing, and track everything from sleeping habits, to the number of steps taken every day.

A fitness bracelet can also connect to another fitness device such as smart weight scale that monitors body weight, body fat, so the consumer’s weight and fat are connected to the fitness-monitoring database for more accurate computing of calorie consumption, and so on.

In 2014, portable and wearable computing introduced major shifts in how humans interact with computing devices and information, dramatically reducing the gap between immformation and the person for whom that information is the most useful. Health and fitness buffs already wear monitors that record their heart rate and the distance they run, coupling that to a PC to analyze the results. Wearable wireless medical devices include accelerometers to warn of falls, and insulin pumps and glucose monitors for diabetics. Each of these devices can connect to a smartphone via Bluetooth, and can issue an alert to their physician by triggering a call over the cellular network.

Already since CES 2014, many products and reference designs for wearable devices have been released to the market. Examples include smart earbuds, smart headset, and a smart watch to a device – developed with Rest Devices for their Baby product line – that can be worn on an infant’s onsite that monitors the baby’s vitals and sends the data to a coffee mug, where it can be displayed.

Wearable Devices, Health Monitoring, and Your TV.

You are wearing a fitness/health device and watching television in your bedroom. The device is linked to your TV through shared logins or a simple linkage through your phone; so now, your TV knows about your body’s activity levels including your sleep/wake patterns.

Figure 2.11 illustrates some examples of wearable devices.


Figure 2.11 Examples of wearable devices

Advertisers will make smarter TV buys and stop sending commercials to sleeping consumers. Taking this one step further, since your fitness device knows your activity levels, it could inform which commercials you see – for example, more active consumers might get the stepper and workout equipment commercials that, the author states, are wasted on him. Wearable, Mobile, and TV

To build on the example above, looping your smartphone into this relationship will give advertisers an additional dataset. Your GPS and cell tower data tell us where you have been locally and if you have been out of town/on vacation. We know if you go to the gym, play tennis, or like to dine out.

On the basis of these specific data, digital (smartphone) and analog (TV) ads that are highly relevant to your behavior (and travels) can be sent to you. Wearable Devices – Other Examples

· People are innovating on asthma inhalers (Propeller Health).

· Wearables (Pebble, Nike+) are opening up APIs for third-party developers.

· Hackers are combining IoT devices and APIs into amazing new use cases, for example, using a Fitbit activity tracker to pause movies on Netflix when you fall asleep or combining Fitbit with SmartThings to lock you out of your house until you have completed your morning run.

As largely a part of IoT, talking medical devices are continuing their journey effectively. This includes a device that reminds the person of taking a medication dose, checking blood pressure, taking a walk, or his/her cardio at a scheduled time. Examples of such groups that benefit from chatty clinical devices are those with regular age-related illnesses such as blood sugar and blood pressure and obesity patients. The way it works is that the app sends out notifications to the patients.

Wearables need to go beyond simply measuring steps, heartbeats, and sleep cycles and attain the ability to measure the mood of individuals.

Today, a handful of companies produce wearable devices to detect brainwaves that infer how calm or attentive a person may be. With further growth in this area, sensors that are powerful enough to stream brainwave signals in real time will be developed. The form factors of these devices would also be compact enough so as to be inconspicuous. Performing Sentiment Analysis Using Big Data

With the human brain containing on average 86 billion neurons, there are potentially trillions of brainwave signals from these wearable devices that need to be analyzed. The amount of time employees stay attentive at work can signify how engaged they are. A sustained series of spikes in brain activity could indicate stressful working conditions. Extreme brain focus at night, followed by lack of restful sleep may imply an organization with a workaholic culture.

Big Data algorithms will be able to correlate these data with several other bodily measurements such as sleep, physical activity, and heart rate to reflect the average sentiment within an organization in real time. Individuals could monitor their own sentiment privately within their smartphone app, and the general public could view anonymous aggregated data about an organization. Millenials, who already share data about their physical exercises through a combination of wearable devices and social media, will continue to do so with these highly advanced brain-sensing wearables.

2.3.5 Health & Fitness and Solution Considerations

Inter apps interface is required to support the following:

· Vital sign monitoring (blood pressure, heart rate, glucose, pedometer, etc.)

· Remote consultation and monitoring

· Medical Consultation. Medical reference apps provide information about drugs, diseases, and symptoms. The apps also give advice on how to take drugs or what to do in case of experiencing pain. They also show locations of pharmacies and medical centers/physicians.

· Diagnostics

· Nutrition. Nutrition apps help their users keep track of their diet, inform them about, for example, vitamins, calories, and fat content, as well as socio-economic aspects of food products (e.g., fair trade)

· Fitness and weight-loss trend analysis and alerts

· Reminders and alerts

· Medical Condition Management. Medical condition management apps represent the fifth largest group of mobile health apps. This group consists of all apps that track, display, and share the user’s health parameters, medicament intake, feelings, behavior, or provide information on a specific health condition, for example, diabetes, obesity, heart failure.

· Personal health records (PHRs)

· Connectivity with providers (healthcare, insurance, family care giver)

· Wellness. Wellness apps summarize all kinds of relaxation solutions, yoga instructions, and beauty tips.

· Integration of local functionality and remote services

· Providing intelligence in gaining insights from big data via analytics tools and capabilities. Because of its powerful processing capabilities, storage capability, and diverse set of algorithms for cognitive computation, IBM Watson is emerging as an important system in analyzing vast amount of medical records.

2.3.6 Health & Fitness and System Considerations

· Integrated sensing, gateway, and services

· Context-aware, recognizing individual, device, location, and apps

· Personalized

· Diversity of user mobile/portable/fixed devices (smartphone, smart watch)

· Adaptive and responsive to change

· Anticipatory of subsequent steps and actions

· Secure at each layer sensing, gateway, and cloud.

2.3.7 Health & Fitness and Hospitals

Good hospital communications is essential for patient welfare and operational efficiency. With increasing numbers of events that need to be monitored, an increasing number of complex decisions need to be made to instantly notify increasing numbers of specialized medical responders via different wireless communications devices. These systems will become increasingly flexible to accommodate new technology as it emerges.

The wireless technology trend will follow the development of new types of sensor as they become capable of sensing the “chemical signatures” of an increasing number of treatable medical conditions.

It will also lead to an increase in automatic dispensing of medicine in response to what the sensor is reporting. For example, a small personal syringe pump could respond to the information coming from the sensor. This would enable smooth, precise dosing, without the unregulated “overshoot/undershoot” situation that may arise due to the delay between the test and the treatment.

2.4 Video Surveillance, Drone, and Machine Vision

2.4.1 Landscape

High-definition networked cameras, video surveillance software, and digitally based storage solutions are leading the industry in video surveillance. Right features and functionality would be required to meet basic surveillance needs for Individual home, Industry, or Infrastructure.

The next evolution is Proactive Video Surveillance Systems. These systems allow the user to intervene, manage, deter, stop, and apprehend perpetrators during an incident. Proactive systems are groundbreaking, providing new cost-effective tools that expand camera capability through video analytics and monitoring solutions.

Although video surveillance has increased in penetration at street intersections at different municipalities, demonstrating an irreversible trend for the future [16], we see video surveillance also penetrating home markets due to lower cost of cameras and overall system cost and this will continue to grow for various industry applications.


Figure 2.12 C-IoT video surveillance business App crossing three domains

See Figure 2.12 for C-IoT video surveillance penetration of Individual, Industry, and Infrastructure domains. Market, Drivers, Positioning

According to Transparency Market Research firm, Global Video Surveillance and Associated services (VSaas – Video Surveillance as a Service) market is $42.81 Billion by 2019 at a CAGR (compound annual growth rate) of 19.1% for 2013–2019. Regionally, it accounts for 35% share in North America, 31% share in Asia Pacific, and 44% in the Rest of the World. Asia Pacific is expected to be the fastest growing market with a market size of USD 17.12 billion in 2019.

Top target markets for video surveillance are commercial, industrial, institutional, residential, and infrastructural applications. Among the commercial applications, the office segment is observed to hold the highest share followed by infrastructure encapsulating highways, streets and bridges, transportation, communications, and stadiums.

2.4.2 Video Surveillance – across Home, Industry, and Infrastructure Individual (Home, Apartment)

Home Security

Video surveillance systems are now available at low cost to be used to protect homes/apartments. For the home, the video camera can be installed outside the home as an added protection. Video images can be viewed locally or remotely. Industry

Health Clinics

Network video offers cost-effective, high-quality patient monitoring and video surveillance solutions that increase the safety and security of staff, patients, and visitors, as well as property. Authorized hospital security staff can view live video from multiple locations, detect activity, provide remote assistance, and much more.


The key to success for retailers is to provide a satisfying customer experience. With network video, you can achieve greater security and loss prevention, optimize store management, and significantly improve store performance. Easily integrated with POS (point-of-sale) and EAS systems, an Axis network video solution enables remote and local monitoring at any time, from any place. You get rapid ROI (return on investment) as well as great interoperability; for instance, by combining people counting, integrated alarm functionality, and register monitoring.


Network video is used in a multitude of industrial applications, such as remote monitoring of manufacturing lines and processes, performance enhancement of automated production systems, incident detection, and perimeter security. Network video can also support virtual meetings and improve remote technical support and maintenance.

Banking and Finance

Starting with existing CCTV equipment and infrastructure, you can create state-of-the-art network video surveillance systems that deliver exceptional image detail and powerful event management. Security staff can monitor multiple branches from a central or mobile location, and rapidly verify and respond to alarms. Infrastructure

City Surveillance

Network video is an essential tool for fighting crime and protecting the public. In emergencies, network cameras can help police or firefighters to quickly focus their action. Advanced network cameras offer razor-sharp detail, motion detection, and tamper-resistance.

Operating over both wired and wireless networks, they are ideal and extremely cost-effective tools to promote the security that ensures safer cities.


Network video helps protect all kinds of public buildings, from museums and offices to libraries and prisons. Supervising security at building access areas and remote monitoring points 24/7, Axis cameras increase security for staff and visitors. They also help prevent vandalism and provide visitor statistics.


Network video gives you the means to improve safety, control flow, and enhance overall security at airports, railways, subways, and public transport hubs, and even on-board vehicles. Remote surveillance lets you monitor everything: check-in, platforms, gates, hangars, parking lots, and baggage systems, as well as vehicles in service. Network video traffic monitoring and management reduces congestion and improves traffic flow.


From daycare centers to universities, Axis network video systems help deter vandalism and increase safety for staff and students. Using the existing IP infrastructure, no extra cabling is required. Features such as motion detection give security operators powerful tools to support action and avoid false alarms. Remote learning is another interesting application, for example, for students who are unable to attend lectures in person.

See Figure 2.13 for an example of C-IoT for video surveillance for a school campus.


Figure 2.13 C-IoT and video surveillance for school campus

2.4.3 Video Surveillance Sensing Requirements

The IP camera is the information source provider of the video security system based on an IP network. It becomes more and more sophisticated with high-quality optics and digital video accuracy.

Mainly three functions are important in an IP camera:

· Pixel resolution. Pixel resolution such as high-resolution 720p is already available. Full HD is coming in the near future.

· Compression rate and H.264 AVC is also enough mature now and SVC will come soon.

· Performance head room for Video Content Analysis. Lens Quality

Camera lenses are subjected to rigorous controls to assure the very highest quality in every respect. Advanced Iris Control

P-Iris, a precise iris control system featured in some Axis cameras, further ensures optimal image quality in all lighting conditions. CPU

A 32-bits CPU at 400 MHz is the minimum power to perform any image processing in addition to the IP encapsulation. Video Coding/Encoding/Compression


· H.264

Video quality products can be configurable for several resolutions and different frame rates, and support key compression formats such as Motion JPEG, MPEG-4, and H.264 to ensure excellent video quality with minimized bandwidth and storage demands. IR Camera – Day and Night

The IR camera has true day/night functionality, with an automatically removable infrared cut filter. This enables color video under high- and low-light conditions, as well as IR-sensitive, black/white video at night. Power over Ethernet

The RJ-45 connector enables connection to the IP network. Built-in support for Power over Ethernet enables the camera to be powered via the network, consolidating power and reducing installation costs by eliminating the need for a power outlet. Advanced Signal Processing

Advanced Signal Processing is used in designing ASICs for high-performance embedded applications. Areas of expertise include networking, open standards, Network protocols, and the most popular operating systems.

Different Wi-Fi solutions will prioritize HD video differently, as well. Some are effective at managing Wi-Fi streams to ensure that one slow device (often a mobile device) does not slow down the whole network. With others, a single misplaced access point could bring down the whole network. A device with MU-MIMO will be even more effective at sending multiple video streams to multiple devices, akin to a wired connection.

2.4.4 Video Surveillance Gateway Requirements Cameras

· HD IP D1 Cameras (1080 × 720!) high quality images/videos

· Work in diverse operational environment (Weatherproof night vision, thermal)

· Hi resolution > 3–5 Megapixel, wide viewing angle, long distance coverage, and zoom lens (2.8–12 mm!)

· Wall/pole/ceiling mount

· Some can be operated remotely for camera zoom, pan, and tilt

· Controller per cluster of cameras (8/16/32/64/128!)

· Potential upgrade to D4 with local storage and processing for facial recognition/license plate and capability to respond to real time query and real time alert of a match.

· Integrated audio signals into the video stream enabling two-way audio at remote locations

· Connectivity

· Networked-based camera connection for viewing and recording

· Potential advanced technologies for an Intelligent smart system that can detect unusual activity or compare images against database suspect photos

· Scalable system that expand to cover more locations and more cameras and enhance server capacity.

Figure 2.14 illustrates some types of IP image sensor cameras


Figure 2.14 Examples of image sensor IP cameras Power Source and Cabling

· 120 or 240 V

· Backup battery

· Solar energy

· Power over Ethernet enabling connection to IP network. Gateway

· Wireless

· Other options (HDMI output!)

· Concentrator/gateways/routers for public safety.

Determining capacity needs to take into consideration video demand on network bandwidth required, considering simultaneous streaming by cameras.

Facilitate audio/text message feedback to the target site via VoIP (voice-over- Internet Protocol).

There is a need for connectivity to a cloud server and capacity to store video images, and faster retrieval under flexible query.

The proposed networking equipment should include routers/gateways/ concentrators, servers, and so on.

2.4.5 Video Surveillance Services

Fixed Position and PTZ (pan–tilt–zoom) video surveillance cameras provide live video pictures that are displayed on the GMS computer screen. This camera can capture a still picture when the gross weight is taken and this image can then be viewed on another work-station for comparison with a live video or saved to disk for future use.

Traffic Eyes are used to verify that the truck is correctly positioned on the scale. Two eyes and reflectors are used at the front and back of above-grade scales. Two additional long-distance eyes and sensors are used to monitor the sides of in-ground scales. Requirements

· Video cameras are to stream videos to the cloud server and at the same time, video streaming can be viewed from a communication-monitoring center.

· If suspicious behavior is detected, the video monitor can send a public message via speakers mounted at key locations to deter the individual(s) and at the same time notify the first responder for action. Figure 2.13 illustrates an example of a communication-monitoring center and secure access.

· In some cases, camera can be installed in critical premises with a capability of a push button to connect directly to the central control for real-time viewing and intervention.

· Video clips can be downloaded about the incident covering, when, where, and how about the incident for further analysis and archived as a part of incident record system. The video is to be complemented by graphical location of the incident (GIS/GPS) and report from the first responder (Figure 2.15). Local Storage

SD/SDHC memory cards enable recordings without having to use external equipment. NVR – Network Video Recorder

Network of cameras redundant feed into 3 terabyte (SATA hard drive, Internal DVD!) – cloud server(s) and a shadow unit for hot-standby redundancy. Some cameras may have local storage but all will stream video into the NVR. The NVR has the capacity to hold feed up to 45 days before it is recycled (after being archived).


Figure 2.15 Communications monitoring center and secure access Remote Viewing

· Remotely view and manage your video surveillance system from anywhere through the Internet or smartphone/tablet in real time.

· Flexibility of viewing by sequence of camera, cluster of cameras, single camera, auto/on-demand viewing, and so on.

· Two-way audio at remote locations.

· Features/flexibility of viewing stored videos. Management Platform

· Flexible surveillance management platform that can be integrated with other systems for a consolidated view of public safety.

· Application flexibilities for client custom features such as video analytics. Visibility

Explore options to conceal visibility of cameras. Examples:

· Some camera systems make it more difficult for people under surveillance to determine if they are being watched, as it is usually impossible to figure out in which direction the camera is facing.

· Some cameras employ dummy lenses to conceal the surveillance target.

· Using a one-way transparent casing provides for the possibility of retaining the overt impression of surveillance – and hence a deterrent capacity – without having to place a camera in every housing or to reveal to the public (and offenders) the exact location under surveillance. Service Plus

· The choice of camera locations should, ideally, result from a high-quality site assessment and analysis that not only incorporates a micro-level mapping of local targeted locations but also a potential scale of the system aiming at a bigger target.

· It is also valuable to conduct a number of site visits that examine the lines of sight for the cameras and identify any potential obstructions.

· If possible, construct a seasonal picture of the target site taking into consideration environmental seasonal changes and traffic.

· Identify hot spots and other areas that require coverage, location of 360° speakers, and wide-angle cameras.

· Ensure initial architecture and configuration is scalable to add more sites and regions. IoT Hosting Services

Hosting solution would include installing the camera, connection to the Internet, maintaining the recording, and monitoring. A service provider will manage system maintenance as well as storage of recorded data. Typically, such services are ideal for small business at a single or multiple locations, small offices, retail stores, gas stations, and convenience stores. On the other hand, clients can now focus on the business and yet have remote access to the cameras from any location that provides an Internet connection, review recorded videos, and get event notifications.

2.4.6 Example: Red-Light Camera – Photo Enforcement Camera

· Red-light running is one of the major causes of collisions, deaths, and injuries at signalized intersections in the United States.

· Twenty percent of drivers do not obey intersection signals.

· Crashes caused by red-light running result in more than 800 fatalities and 165 000 injuries each year, according to the NHTSA.1

· The economic impact of red-light running on society is estimated to be $14 billion annually. Other motorists and pedestrians account for nearly half the deaths caused by red-light running crashes.

· Across the nation, communities are reducing the number of deaths and injuries from red-light offenses by 20–50%, simply by implementing red-light cameras.

· For 20 years, the technology of the photo enforceable camera has proven to be extremely accurate and reliable. Installed in over 500 communities.

· Does photo enforcement invade our rights of privacy “Big Brother” watching!

· Photo enforcing technology is simply one tool available to the community to ensure that citizens are driving in a safe and responsible manner for the benefit of themselves and those around them.

· When you choose to travel on public streets, you have a responsibility to operate in a safe and legal way.

· Does photo enforcement put police officers out of a job?

· Photo enforcement helps ensure that limited resources are maximized.

· Much like a radar gun used by an officer, photo enforcement is merely a tool that frees up some of the officers’ limited time for enhanced safety and security in the community.

· Does my community really need red-light cameras?

1. – Insurance Institute of Highway Safety report, 27 January 2007 shows when red-light cameras are introduced, incidents of red-light running dropped from 198 incidents to 2.

· Will extending yellow signal timing be sufficient?

o The use of adequate yellow signal timing reduces red-light running-related injuries and collisions.

o Longer yellow timing used together with red-light cameras provides a more significant decrease in incidents of red-light running.

o STAT: Results showed that yellow timing changes reduced red-light violations by an average 36%. The addition of red-light camera enforcement reduced red-light violations by an additional 96% beyond levels achieved by longer yellow signal timing alone.

See Figure 2.16 for an example of a red-light photo-enforced camera.

2.4.7 Conclusion

The market for network video products has grown tremendously in the past few years. The rapid deployment of network video indicates an irreversible shift from old, analog video technologies as network video advances with ever more effective, innovative, and easier to use products.

HDTV surveillance cameras are becoming the norm and more megapixel cameras are being introduced. There are cameras that can handle challenging lighting conditions such as low light, high contrast lighting, and total darkness, enabling improved surveillance capability. Processors in cameras and video encoders are not only faster but also smarter. In addition, efficient video compression techniques as well as a new type of iris control, P-Iris, have been introduced.


Figure 2.16 Example of red-light photo enforced

Product choices are required to meet a variety of needs. There are smaller, more discreet – even covert – cameras, as well as thermal network cameras. There are needs for different fields of view, which are available from telephoto to 360° panorama. Axis’ product development has also focused on easy and flexible installation. Outdoor cameras, for example, are weatherproofed right out of the box. Virtually most cameras and video encoders support Power over Ethernet, which simplifies installation. Many varifocal fixed cameras (box and dome) allow the focus and angle of view to be remotely set from a computer. Many fixed cameras also have the ability to stream vertically oriented views that maximize coverage of vertical areas such as aisles and hallways.

Managing cameras and video streams are being made easier. There is increased support for intelligent video functionalities. There are also video management solutions to suit every type of customer – whether it is a retail store with a few cameras or one involving hundreds of cameras at multiple sites. Products that support ONVIF can be easily integrated into systems that incorporate other ONVIF-conformant products from different manufacturers.

Greater network bandwidth is becoming more commonplace, and technologies have improved to make the transmission of data over wired and wireless networks safer and more robust.

Progress has also been made in storage solutions, especially for small systems. Today high-capacity network-attached storage (NAS) solutions are available that provide terabytes of storage at minimal costs and memory cards that enable weeks’ worth of video to be stored in a camera or video encoder.

2.5 Smart Home and Building

2.5.1 Landscape Smart Home

Smart Homes provides integrated, centralized control of two or more individual systems:

· Environment control

· Smart thermostat (e.g., Nest)

· Air moisture

· Smoke alarm

· Flood detector

· Lighting system

· Drapes

· Sprinkler systems (outdoor)

· Smart Energy HVAC

· Smart Meters

1. Gas meter

2. Electricity meter

3. Water meter

4. HVAC Control

· Smart Appliance

1. Refrigerators (consume 50% of home’s energy budget)

2. Stove

3. Dishwasher

4. Washer/dryer

· Smart Plug

· Security/Safety (indoor, outdoor)

· Video Surveillance (e.g., Dropcam)

· Alarm System

1. Motion Detectors Sensors

2. Door Locks, key Fobs

3. Window/Door/Garage control

· Health and Fitness

· Wearable/portable devices (e.g., iWatch, fitbit)

· Chronic Disease Management

· Living Independently.


· Set Top Boxes and multimedia

· HD TV/Video Streaming

· Hi-Fi Systems

· VoIP

· Data Networking, Storage, Printing

· Remote Control.

See Figure 2.17 for C-IoT for a Smart Home. Smart Building

· HVAC Control: heating (electric, gas), ventilation, air-conditioning

· Lighting control

· Smoke detector and sprinkler system

· Access control

· Data network, VOIP

· A/V system

· Wireless systems

· Facilities.


Figure 2.17 C-IoT for smart home

With an increasing demand for energy efficiency, safety, reliable connectivity, and precise control, industrial drives for factory automation systems are becoming more and more sophisticated, requiring cutting-edge technologies.

Devices: Smartphone, tablets, PC, wearable devices.

Devices may be connected through a wired or wireless network to allow control via a personal computer, and may allow remote access via the Internet (using a PC, smartphone, or tablet).

See Figure 2.18 for C-IoT for Smart Building.

2.5.2 Requirements General Features

· Solution Architecture and platform, sensors, and other devices

· Integrated, wirelessly enabled platform that combines home security and automation capabilities

· Monitor your home’s energy usage and consumption

· Remotely adjust your thermostat settings for heating and cooling

· Security monitoring centers 24/7

· Help lower your energy use by showing where/when electricity is being used

· Allow customers to customize a solution, based on individual needs, and the ability to manage and control their services from their location or from abroad

· Remotely lock or unlock doorsc02fig18

Figure 2.18 C-IoT for smart building

· Remotely turn on or off lights and appliances

· Set up to receive automatic event notifications

· The ability to add more features and services after the initial installation. General Attributes

Many industrial network applications share attributes such as

· Real-time operation to detect state changes and take appropriate actions within an acceptable timeframe

· Deterministic operation to execute instructions in a predetermined order and at a predetermined time

· Reliable operation, often with N + 1, 2N, or N +M redundancy, depending on the perceived cost of an outage

· Secure operation to ensure that unauthorized persons cannot accidentally or intentionally access or change data and manipulate control systems

· Safe operation to ensure that the system will not harm people or nearby equipment

· Ruggedized systems to operate in harsh environments such as

· –40 to 120 °C temperatures at each chip on a board

· Locations that are dirty, dusty, or surrounded by dangerous chemicals or emissions

· Environments that contain high levels of electromagnetic radio emissions across a wide frequency spectrum

· Remote systems, which are difficult to access for maintenance and repair. These systems require designs that minimize parts with higher failure rates, such as fans, to reduce time between system-level failures

· Systems that are operated by people who are not necessarily technology experts, who may not have access to sophisticated diagnostic equipment, and who often do not have time to read a long instruction manual or take a training course.

2.5.3 Smart Home & Building Sensing Requirements Wireless Meters and Sensors

Affordable wireless sensors and meters can now be used to monitor automated building equipment and relay data to a centralized remote command center. Requirements call for

· Smart Meters for Electricity, Gas, Water, and Heat

· Grid Infrastructure

· RFID Transceiver + NFC smart Interface tag.

2.5.4 Smart Home & Building Gateway Requirements

An industrial gateway or industrial router is a ruggedized device that connects two or more networks, with signals directed only to ports where they are needed. The gateway can convert between standard Ethernet and industrial Ethernet protocols, between wireless and wired interfaces, or between Ethernet and fieldbus communications protocols. Processor performance can range from 200 to 1500+ MIPS. On-chip memory is often greater than 256 KB L2 cache. Factory automation equipment is ruggedly constructed for fanless operation in a harsh industrial environment. Internet and Cloud Computing

The advent of the Internet and decreasing costs of data transmission now makes it financially feasible to transmit data from millions of building data points to the command center. The relatively affordable high-capacity computing power of the cloud allows for cost-efficient data analysis to an extent not possible in previous eras.

Gateway infrastructure securely aggregates data from a manageable number of meters and sends them to the utility servers. Open Data Communication Protocols

Today, protocols such as 802.11ac, 802.11n Wi-Fi LAN, and 3G/4G WAN, integrated IPv4/IPv6 TCP/IP stack are required to support cross-platform data sharing. We have seen 802.11ac clients and APs (access points) come to market, but it will be some time before 802.11ac most new laptops and some smartphones can support it. Owing to the backward compatibility of 802.11ac with 802.11n, and because 802.11ac is limited to 5 GHz only, 802.11n will still be around for years to come. Already today, 802.11n is widely used to support rich services such as voice, video conferencing, and video streaming. More details about wireless technology and impact on applications trends can be found in [17].

Field bus protocols originally evolved to interconnect industrial drives, motors, actuators, and controllers. These numerous field buses include PROFIBUS, DeviceNet™, ControlNet™, CAN, InterBus, and Foundation Field Bus. Subsequently, manufacturers created higher-level networking protocols to interwork with the field bus protocols across Ethernet. These include PROFINET, EtherNet/IP™, Modbus® TCP, and SERCOS III. As a result, devices are needed to bridge between legacy and newer network protocols.

This brings opportunities for developers to innovate and challenge to meet Advanced SoC Architectural requirements for target market in the embedded space. For further details and examples, refer to [18, 19].

2.5.5 Smart Home & Building Services

The IoT-based solution will contribute toward reduction of operating costs, extension of product functionality, and enhancing user experience. The C-IoT-based solution for the connected home provides an integrated set of apps. These apps need to interoperate and work together harmoniously. For example, as you leave your work to go home and you press a single “coming home” button on your mobile device, in response, your house turns on the outdoor lights, brings up the indoor temperature from an energy-saving to a welcome-home temperature, closes drapes, and opens the garage door as soon you reach the premises and unlocks the door as you touch the handle. Powerful Analytics Software

The best new-generation smart solutions provide numerous dashboards, algorithms, and other tools for interpreting building data, identifying anomalous data, pinpointing causes, and even addressing some issues remotely. Remote Centralized Control

Secure Internet technologies can be used to protect data transmissions from hundreds of buildings in a company’s portfolio to the central command center, staffed around the clock by facilities professionals. Integrated Work-Order Management

Today’s building management systems can be integrated with a work-order system to streamline communications with on-the-ground facilities staff when human attention is required.

In North America, companies such as Verizon, AT&T, Comcast, and Time Warner Cable provide home monitoring services for devices such as cameras, thermostat, appliances, and door/window control.

With connected refrigerators, lights, thermostats, and other sensors in the home, we can glean insights into the user’s current environment. Is it dark? Is it warm or cold? Is the TV on or off? What are they watching? Who is home? This and more can be gained by connecting addressable advertising with connected homes.

Taking this one step further, sooner or later our fridge will know what we are low on, and send us ads or recommendations based on previous contents and consumption patterns. Our connected TVs will know what we watch and who is watching; this will allow marketers and networks to bring truly relevant content to the viewer’s screen.

2.6 Smart Energy

2.6.1 Landscape

Most of our high-energy use today comes from heating/cooling, cooking, lighting, washing, and drying. These home appliances are beginning to become smart with connectivity features that allow them to be automated in order to reap benefits that smart metering and variable tariffs bring. The utility companies are beginning to better manage the energy demand and perform load balancing more efficiently.

On the Utility/Industry side, Data Aggregators/Concentrators form an important component in automatic meter reading (AMR). It creates the necessary network infrastructure by linking several utility meters (electricity, gas, water, heat) to the central utility server and captures and reports vital data. It also helps synchronize the time and date data of utility meters to a central utility server and enables secure data transfer of user authentication and encryption information. Communication to utility meters is comprised of an RF or wired (power line modem) connection, enabling data transfer to the central utility server via GPRS, Ethernet, and GSM, POTS, or UHF/VHF networks.

According to Pike Research, it is estimated that by 2020, there will be 963 million smart meter units and 63 million energy management users. This in turn will offer great opportunities for utilities to manage and control energy distribution to their customers; it also gives homeowners the opportunity to better manage their energy usage through smart energy management. Individual: Smart iThermostat and Home

Smart homes will be able to self-manage things like energy consumption and climate control. Taking into account the homeowner’s long-term energy goals as well as things like outside weather and city resources based on the smart grid, this future home will actively optimize its activity in real time. Smarter Materials

Not only smarter, these homes of the future will be built with smarter materials. Currently in development, MIT’s Mobile Experience Lab is building a new type of window that uses two layers of polymer-dispersed liquid crystal to let in light and heat when desirable and similarly, block it. Used in tandem with the structure’s autonomous climate control, this facade will be able to shift to maximize comfort inside the home. Similarly, the prototype blends data from sensors both inside and outside of the home with historical weather information to determine the most comfortable combination of heat and air-conditioning while also minimizing carbon dioxide emissions.

· Cloud Storage and Computation

· Big Data Analytics

· Web and Mobile, remote operations

· Target Applications

· Manage energy usage through smart energy management.

See Figure 2.19 illustrating C-IoT for Smart Energy.

2.6.2 Requirements

General requirements call to enable consumers to reduce electrical bills by deferring operation when energy costs are at a peak. In addition, energy patterns can be monitored so that the consumer can be given alerts if an appliance needs service, possibly avoiding breakdown and costly repairs.


Figure 2.19 C-IoT for smart energy

2.6.3 Smart Energy and Sensing Requirements

· Climate control

· Thermostats

· Moisture detection

· Thermostat, plugs, switches

· Appliance power controls (e.g., refrigerators)

· Security and alarm (motion and video, contact relays)

· Video surveillance cameras, motion detectors

· Garage door/Door locks control contacts.

2.6.4 Smart Energy and Gateway Requirements


· WLAN – Wi-Fi

· Cellular WAN


· ZigBee

· Siri.

2.6.5 Smart Energy – Services

IoT for Home Automation should focus on providing customers with a comprehensive home security and automation solution that offers the best possible customer experience and uses the most advanced mobile Internet technology on the market to make their lives easier and keep their families and property safer. The IT Services is to provide a unique suite of services, from start to finish, that will give homeowners control of their property and their possessions through an easy to navigate user interface.

· Established technology footprint, scale, and maturity (3B + Wi-Fi and 100 M HomePlug endpoints).

· Wi-Fi and HomePlug are based on the same IEEE networking model, which allows for seamless connectivity without translation.

· Combining the flexibility of Wi-Fi and ubiquity of the power line provides unsurpassed coverage throughout the HAN. When used in the HAN, the combination of Wi-Fi and HomePlug Green PHY provides an unsurpassed whole home coverage.

· High bandwidth (Mbps), IP-based connectivity enables state-of-the-art security protocols and quick software updates against cyber threats. Smart Thermostat (e.g., iThermostat, Nest)

Smart Thermostat is a programmable thermostat, being offered by utility companies, that gives you control over the temperature in your home through any Web-enabled PC or smartphone for the purpose of helping customers save electricity and money.

The Smart Thermostat has evolved over time and a recent model includes a thermostat with a color touch screen display, an enhanced online portal with expanded features, and upgraded controls via the mobile app. It also automatically switches between heating and cooling as needed to keep indoor temperatures comfortable, a feature that is especially useful between seasons. The cost savings it offers just by using its preprogrammed settings complements the convenient controls.

The energy savings solution is available from utility companies to their customers, who receive the equipment and installation with no upfront charges. It leverages your high-speed Internet connection at home to connect your thermostat with the online- and smartphone-based controls. The Smart Energy Dashboard

The utility company has expanded the features offering with Smart Energy Dashboard, an energy savings solution that offers a personalized view of your home’s electricity consumption, giving you insight into how your habits at home affect your electricity usage and your bill.

The dashboard is available online to any customer for free by the utility company, and it now offers a new home comparison section that lets you compare the electricity usage of your home with similar homes in your area based on information you provide, including ZIP code, home type, age of home, square footage, and heating type. It also offers a new usage breakdown section including a pie chart that shows your approximate electricity usage and cost for heating, cooling, water heating, lighting, electronics, appliances, refrigeration, and other equipment.

The dashboard shows you how much electricity you are using over time and how the outside temperatures may be affecting your usage. It shows your electricity usage and cost by month, day, and even hour if you have a smart meter. It also offers you a forecast of your estimated usage and costs at any point of a billing cycle.

2.6.6 The Smart Energy App

Utility companies are also offering customers mobile access to their accounts through a free app on smartphones or tables. The app now allows you to control your home temperature settings.

It also provides a number of features available through the dashboard in addition to giving you the opportunity to check and pay your bill.

There are several other types of smart thermostat such as Nest (Google) and Lyric (Honeywell).

Nest (purchased by Google for $3.2 billion) is a company that makes a Learning Thermostat that saves energy with control over Wi-Fi from your mobile device or laptop. Nest also remembers what temperatures you like and turns itself down when you are away. Nest creates a personalized schedule based on the temperature changes you have made. All you have to do is get comfortable. It is so simple that 95% of Nests have schedules. Other features offered by Nest include:

· Automatically turns itself to an energy-saving temperature when you are away, so you do not waste energy heating or cooling an empty house.

· Connect your Nest thermostat to Wi-Fi, download the free Nest Mobile app, and change the temperature from anywhere.

· Provides Energy History and Report to understand how your energy use changes month-to-month and how you can save more.

· Shows you when you are choosing a temperature that will help you save. Look for the Leaf every time you turn the ring.

Recently, Nest has opened its platform to other devices and developers to develop IoT applications that enable interoperability between devices in the home using Google’s cloud.

2.6.7 Smart Energy and Network Security

NIST SP 800 82 (NERC and IEEE) provides guidance for securing ICSs, including supervisory control and data acquisition (SCADA) systems, distributed control systems (DCSs), and other systems performing control functions. The guideline provides overview of ICS and typical system topologies, identifies typical threats and vulnerabilities to these systems, and provides recommended security countermeasures to mitigate the associated risks.

Major ICS Security Objectives

· Protecting individual ICS components from exploitation

· This includes deploying security patches in as expeditious a manner as possible, after testing them under field conditions; disabling all unused ports and services; restricting ICS user privileges to only those that are required for each person’s role; tracking and monitoring audit trails; and using security controls such as antivirus software and file integrity checking software where technically feasible to prevent, deter, detect, and mitigate malware.

· Maintaining functionality during adverse conditions

· This involves designing the ICS so that each critical component has a redundant counterpart. Additionally, if a component fails, it should fail in a manner that does not generate unnecessary traffic on the ICS or other networks, or does not cause another problem elsewhere, such as a cascading event. NIST SP 800-82, Rev 2

NIST SP 800-82, Rev 2 is a major update, which includes

· Updates to ICS threats and vulnerabilities

· Updates to ICS risk management, recommended practices, and architectures

· Updates to current activities in ICS security

· Updates to security capabilities and technologies for ICS

· Additional alignment with other ICS security standards and guidelines.

ICS overlay for NIST SP 800-53, Rev 4 security controls will provide tailored security control baselines for Low, Moderate, and high impact ICS.

2.7 Track and Monitor

Tag (and GPS) – Smart Tracking and Monitoring of Assets.

2.7.1 Landscape RFID – Definition/Standards

In the IoT paradigm, many of the objects that surround us will be on the network in one form or another. RFID and sensor network technologies will rise to meet this new challenge, in which information and communication systems are invisibly embedded in the environment around us.

RFID refers to a wireless system comprised of two components: tags and readers.

2.7.2 Track and Monitor – Sensing Requirements

The reader is a device that has one or more antennas that emit radio waves and receive signals back from the RFID tag. Tags, which use radio waves to communicate their identity and other information to nearby readers, can be passive or active, and are attached to the object to be identified or tracked. Passive RFID tags are powered by the reader and do not have a battery. Active RFID tags are powered by batteries.

A typical operation consists of an RFID reader that transmits an encoded radio signal to interrogate the tag. The RFID tag receives the message and then responds with its identification and other information.

RFID tags can store a range of information from one serial number, a license plate, or product-related information such as stock number, lot or batch number, and production date to several pages of data. Readers can be mobile so that they can be carried by hand, or they can be mounted on a post or overhead. Reader systems can also be built into the architecture of a cabinet, room, or building.

RFID tags contain at least two parts: an integrated circuit for storing and processing information, modulating and demodulating an RF signal, collecting DC power from the incident reader signal, and other specialized functions; and an antenna for receiving and transmitting the signal. The tag information is stored in a nonvolatile memory. The RFID tag includes either a chip-wired logic or a programmed or programmable data processor for processing the transmission and sensor data, respectively.

Fixed readers are set up to create a specific interrogation zone, which can be tightly controlled. This allows a highly defined reading area for when tags go in and out of the interrogation zone. Mobile readers may be handheld or mounted on carts or vehicles.

Recently, decreased cost of equipment and tags, increased performance to a reliability of 99.9% and a stable international standard around UHF passive RFID have led to a significant increase in RFID usage.

Overview/Market/Drivers of Growth/Positioning/Relation to IoT (Reference IoT Model).

It could be argued that the industry got a little ahead of itself in the early 2000s when RFID was expected to transform supply chains overnight. The concept of the “IoT” was still years away, but the appeal of digitizing physical assets and achieving absolute visibility led to some grand theories. However, although much of the early hype has faded, RFID continues on a trajectory toward widespread adoption and impact.

According to RFID market research from IDTechEx, RFID market is on a very healthy evolutionary track, growing from $7.88 billion in 2013 to $9.2 billion in 2014. IDTechEx expects the RFID market will reach $30.2 billion in 2024 [20].

The driver to this growth is not the wholesale replacement of bar codes with RFID tags, nor is it the deep pockets of sophisticated retail, healthcare, or governmental entities. It is the mind-set that a mere handful of tags and a single reader can provide a meaningful ROI for a very small slice of a given process.

2.7.3 Track and Monitor – Services

When tags are in place because one part of the supply chain sees the value, the technology becomes more appealing for others to collect data because the required investment is much less. There is an opportunity to leverage an investment that someone else has already paid for, opening the door for more applications that contribute to streamline the operational efficiency and provide large amount of data to drive greater insights for establishing next course of action or driving the next phase of a roadmap.

RFID technology helps in automatic identification of anything they are attached to, acting as an electronic barcode. The passive RFID tags are not battery powered and they use the power of the reader’s interrogation signal to communicate the ID to the RFID reader. This has resulted in many applications particularly in retail and supply chain management. The applications can be found in transportation (replacement of tickets, registration stickers) and access control applications as well. The passive tags are currently being used in many bank cards and road toll tags, which is among the first global deployments.

Active RFID readers have their own battery supply and can instantiate the communication. Of the several applications, the main application of active RFID tags is in port containers for monitoring cargo.

2.7.4 Track and Monitor – Solution Considerations

RFID is not bar codes. Bar codes will remain the standard for capturing data at specific points in a process for years to come. It is the places between those points where RFID might prove valuable. RFID will tell you what happened for an object being tracked from point A to point B. Now you know both where an object is and what it is doing. From there, you can start to think about what it could be doing. Unlike a bar code, an RFID tag constitutes a unique identifier for the tagged item – it is not those kids, elderly, trucks, trains, but it is those specific uniquely identified kids (by name) in schools, elderly (by name) at home, trucks (by ID) at warehouse, or trains (by unique ID) at station. Whether between two points in a facility or between two cities, RFID can prevent objects (products and assets) from getting lost along the way. In the process, it can create visibility from Point A to Point B or from a warehouse – dock door to doorstep of a retail store.

Uniqueness is often important in e-commerce applications where value-added information results in better comprehension that can be targeted to achieve greater efficiency.

Because RFID is for relatively short ranges, from between sub-meter to a few meters, it is complimentary to GPS technology for both asset and product tracking. For instance, a container might be fitted with GPS and an RFID reader and as an RFID-tagged case is put on the container the two might be associated in software. When paired with RFID technology, sensors and data loggers can monitor conditions like temperature and impacts. These are widely used in the food traceability industry, mainly to meet insurance requirements.

Active RFID is nearly the same as the lower-end WSN nodes with limited processing capability and storage. The scientific challenges that must be overcome in order to realize the enormous potential of WSNs are substantial and multidisciplinary in nature.

2.7.5 Track and Monitor Examples Implanted RFID Chip to Manage Critical Healthcare Issues

RFID tag implanted under the skin of a person empowers the individual to know and manage his/her healthcare issues. The tag could alert physicians of the implants during surgery and relay necessary information for individuals with life-threatening diseases, and could be particularly useful during a medical crisis. It also could be used to keep track of other implantable devices, such as a pacemaker, a patient might have. The tag does not contain any medical records, but its 16-digit number could be linked to a database of patient medical information. When the tag is scanned, the number could be quickly cross-referenced to reveal specific medical data about the patient. The 134.2-KHz RFID tag could save lives and possibly limit injuries from errors in medical treatments. Advancement beyond RFID Tags to Track Elderly at Home

A lot of elderly people live alone. So if they get into trouble (e.g., fall down unconscious or have an injury that prevents them from moving) there is no one aware that they need help. If the environment in their households can be automatically monitored for signs of sudden onset of an acute health problem then helpers can be sent to check on them, video cameras could be activated to see if they are all right, or they could get a phone call.

An RFID reader-tag system can be used to track elderly. Researchers are adapting RFID and sensor technologies to automatically identify and monitor human activity to be able to determine if an individual’s normal routine is being maintained so that timely assistance can be provided if it is needed. Home medical monitoring can and will go far beyond what RFID tags can accomplish. Imagine an electronic monitoring system built into your bed that monitors the gases in your breath, tracks your breathing and pulse, and studies your movements in bed. It could detect problems like sleep apnea or nervous disorders and diagnose a chronic illness in its early stages. Safety of Our Kids in Schools and Buses

RFID-enabled badge Readers are being installed on schoolbus doors and in classrooms. When a child is in range, the reader transmits data to a GPS system. The system is only being used for notification purposes, giving parents and schools the ability to log on and view students’ attendance records.

The schools across the country are adopting a variety of different tools to monitor students both in school and outside school. Among these tools are RFID tags embedded in school ID cards, GPS tracking software in computers, and even CCTV video camera systems. According to school authorities, these tools are being adopted not to simply increase security, but to prevent truancy, cut down on theft, and even improve students’ eating habits.

2.8 Smart Factory

2.8.1 Factory Automation – Robot

Robots fascinate us. Their ability to move and act autonomously is visually and intellectually seductive. We write about them, put them in movies, and watch them elevate menial tasks like turning a doorknob into an act of technological genius.

For years, they have been employed by industrial manufacturers, but until recently, never quite considered seriously by architects. Sure, some architects might have let their imaginations wander but not many thought to actually make architecture with robots. Now, in our age of digitalization, virtualization, and automation, the relationship between architects and robots seems to be blooming

· By the end of 2007, there were around 1 million industrial robots in use, worldwide. About 60% of these are articulated robots, and about 22% are gantry robots.

· The global market for industrial robots was worth approximately $6.2 billion in 2008, excluding software, peripherals, and systems engineering.

· The automotive industry is the largest user of industrial robots.

· Although the global economic crisis has severely impacted sales of industrial robots – especially in the key automotive sector – the need to automate industrial processes to improve efficiency and safety of the workplace remains constant, and is expected to lead to renewed growth between 2010 and 2012.

2.8.2 Industrial

Industrial Robotics is a branch of engineering that combines electronics, control systems, mechatronics, artificial intelligence, computer science, and bioengineering. A robot is a device, which includes sensors, actuators and a control system. Robots are generally classified by their purpose:

· A factory robot or an industrial robot performs jobs such as cutting, welding, and gluing;

· A service robot or a mobile robot adds to its primary tasks also movement within its working environment.

See Figure 2.20 for an example of a robot in smart factory.

Embedded Power provides a complete suite of power conversion solutions to meet the needs of robotics applications.


Figure 2.20 Future C-IoT robot as a caregiver

· Automated assembly

· Automated manufacturing

· Automated packaging

· Warehouse management

· Goods handling

· Goods transport

· Pick-and-place systems

· Portal robots.

The following are the key enabling product requirements:

· Integrated ADC and FPU and analog

· Standard Low-side, High-side, and Bridge Smart Power Devices for driving solenoids, DC motors, and stepper motors

· Dedicated ICs for actuator driving, charging, and power management

· One of the industry’s broadest ranges of Power MOSFETs and IGBTs (Insulated-Gate Bipolar Transistors)

· PC Controller technology

· Real-time Operating Systems based on multiprocessor technology

· Safety Technology – 100 Mb, multicore processor technology

· Open interface Robot Arm – Multitude of Sensors

A robotic arm assembly may have movement in several axes. A worm-driven shoulder joint could move the arm up and down in conjunction with an electric-driven hydraulic actuator. An independent elbow joint adds another axis of control, and a wrist joint adds a directional and rotational set of axis.

While each of these can be an independent set of control loops using their own stress and strain sensors, they are not isolated functions. The movement of an arm up, for example, can induce overload stresses on a wrist joint if too much weight is loading down the arm and the wrist is in the wrong position. As a result, all sensor data can be important, even for sometimes seemingly unrelated tasks. This is the fusion of sensory data where the big picture is looked at rather than an individual control loop.

Example: Multi-fingered robot hand for industrial robotics application.

A wireless teleoperated robotic hand system is intended for providing solutions to industrial problems like

· Robot reprogramming,

· Industrial automation, and

· Safety of the workers working in hostile environments.

The robotic hand system works in the master slave configuration where Bluetooth is used as the communication channel for the teleoperation.

The master is a glove, embedded with sensors to detect the movement of every joint present in the hand, which a human operator can wear.

This joint movement is transferred to the slave robotic hand, which will mimic the movement of human operator. The robotic hand is a multi-fingered dexterous and anthropomorphic hand.

All the fingers are capable of performing flexion, extension, abduction, adduction, and hence circumduction. A new combination of pneumatic muscles and springs has been used for the actuation purpose. As a result, this combination reduces the size of the robotic hand by decreasing the number of pneumatic muscles used. The pneumatic muscles are controlled by the opening and closing of solenoid valves.

2.8.3 Service Robot

According to the International Federation of Robotics (IFR), a service robot is a robot that performs useful tasks for humans or equipment excluding industrial automation application. Note: The classification of a robot into industrial robot or service robot is done according to its intended application.

· A personal service robot or a service robot for personal use is a service robot used for a noncommercial task, usually by lay persons. Examples are domestic servant robot, automated wheelchair, personal mobility assist robot, and pet-exercising robot.

· A professional service robot or a service robot for professional use is a service robot used for a commercial task, usually operated by a properly trained operator. Examples are cleaning robot for public places, delivery robot in offices or hospitals, firefighting robot, rehabilitation robot, and surgery robot in hospitals. In this context, an operator is a person designated to start, monitor, and stop the intended operation of a robot or a robot system.

A degree of autonomy is required for service robots ranging from partial autonomy (including human–robot interaction) to full autonomy (without active human–robot intervention). Therefore, in addition to fully autonomous systems, service robot statistics include systems that may also be based on some degree of human–robot interaction or even full teleoperation. In this context, human–robot interaction means information and action exchanges between human and robot to perform a task by means of a user interface.

In some cases, service robots consist of a mobile platform on which one or several arms are attached and controlled in the same mode as the arms of industrial robots. Furthermore, contrary to their industrial counterparts, service robots do not have to be fully automatic or autonomous. In many cases, these machines may even assist a human user or be teleoperated [21].


Figure 2.21 Robot in smart factories Caregiver Robot

Robots may become gentler service/caregivers in the next 10 years. See Figure 2.21.

Lifting and transferring frail patients may be easier for robots than for human caregivers, but robots’ strong arms typically lack sensitivity.

Japanese researchers are improving the functionality of the RIBA II (Robot for Interactive Body Assistance), lining its arms and chest with sensors so that the robot lifts and places patients more gently.

2.9 Others (Smart Car, Smart Truck, Drone, Machine Vision, and Smart City)

2.9.1 Smart Car Definition

Next-generation telematics and infotainment for passenger cars are not just around the corner, they are here.

Embedded wireless connectivity enables a broad range of functionality that is transforming the automobile experience. From basic safety and security services, such as automatic crash detection and notification, to next-generation safety services enabled by vehicle-to-vehicle (V2V) and vehicle-to-roadway infrastructure communications, to enhanced remote diagnostics and maintenance, to 4G LTE-powered advanced 3D navigation and connected infotainment services, mobile technologies are at the forefront of driving innovation in the next generation of connected cars.

This automotive heritage combined with unparalleled expertise in mobile technologies allows it to play a unique role in enabling automakers to offer advanced systems that empower drivers and passengers with the capabilities they have come to expect from their connected consumer devices and more, while truly revolutionizing the driving experience.

To address the rapidly expanding automotive opportunity, Automotive Solutions, comprising automotive-grade Snapdragon processors, Gobi 3G/4G LTE multimode modems, and low-power Wi-Fi and Bluetooth solutions, provide unprecedented, integrated connectivity options for the automotive ecosystem to create new, breakthrough connected systems and services.


· Standard car/efficiency and IoT empowered for efficiency, safety

· Electric car

· Driverless car

· V2V

· Vehicle-Infrastructure

See Figure 2.22 about C-IoT for smart cars. Market, Drivers, Positioning

Vehicle and C-IoT

According to Semicast Research, the “revenues for original equipment (OE)automotive semiconductors grew by 12% to USD $25.5 billion in 2012, while the total semiconductor industry is declined by almost 3% to USD $292 billion.” This represents a high growth in the semiconductor automotive industry compared to the negative growth of the total semiconductor market [22].

The automotive world is changing rapidly. The unprecedented growth is driven by advancement of technology in the automotive technology empowered by IoT-enabled sensors, Robot-assisted manufacturing, and larger adoption.


Figure 2.22 C-IoT for smart cars

Advancement of technology in alternate energy has led to the introduction of electric and hybrid vehicles. Six-month sales data suggest that in the first half of 2013, all-electric vehicle sales in the United States unexpectedly overtook sales of plug-in hybrid electric vehicles (EVs that also have a combustion engine) for the first time.

In addition, most car manufacturers are developing “autonomous cars,” that is, vehicles that still need a driver to take over the steering wheel or acceleration/braking pedal functions in case of unanticipated events. But Google has made a leap with a pure “driverless car” – a car without human intervention, steering wheel, and acceleration/braking pedals. This leap will boost revenue growth for semiconductors over the coming years. It is important to note that unlike today’s autonomous cars; Google’s driverless car totally depends on its sensors, semiconductor ICs, and algorithms running inside several electronic control units (ECUs). Semiconductor technology is already available for implementing driverless cars, but human acceptance is a key challenge.

CAR – Head-Up Display

Aerospace has a continuous influence into the design – aerodynamics of cars and now in terms of instrumentation and guidance system. The latest is head-up display (HUD) technology, which was originally developed for fighter jets. Projecting information directly into the driver’s line of sight allows people to process it up to 50% faster – due to shorter eye movement – and keep their attention focused on the road ahead. Head-up display technology is currently available on several high-end vehicles and is starting to show up in other segments. In fact, more than 35 vehicle models currently available in the United States have standard or optional HUDs. According to IHS Automotive, 9% of all new automobiles in 2020 will be equipped with HUD technology versus 2% in 2012. Sales this year alone is projected to climb 7% to 1.3 million units.

Key components of HUD systems include mirrors, heat sinks, optical films (for light refraction), graphics processors, digital light-processing projectors, LCDs, LEDs, and OLEDs.

As the technology matures, HUDs are growing in size. The recent North American International Auto Show in Detroit displayed a system that projects an image 16 in. wide by 6 in. high, about twice the size of most current head-up images. Requirements

Sensing Environment

Powertrain Control Module (PCM): Electronic signals from various sensors act like the engine’s eyes and ears helping it make the most of its driving conditions.

Sensors are required for all the key functions necessary for

· Managingignition timing,

· Fuel delivery

· Emission control

· Transmission shifting

· Cruise control

· Engine torque reduction (if the vehicle has antilock brakes with traction control)

· Charging output of the alternator

· Controlling the throttle.

Reliable sensor inputs are an absolute must if the whole system is to operate smoothly.

The powertrain control module (PCM) is required to learn and make small adjustments to the fuel mixture and other functions over time as the vehicle accumulates miles.

In the case that the PCM controls the transmission, it may take a while to relearn the driver’s habits, so the transmission may not shift in exactly the same manner as before until this occurs.

Remember, a PCM needs all its sensor inputs, proper battery voltage, a good ground, and the ability to send out control signals to function normally.

Autonomous Vehicle:Autonomous Vehicles,” that is, vehicles that still need a driver to take over the steering wheel or acceleration/braking pedal functions in case of unanticipated events.

Key Requirements

In addition to the requirements described for IoT Empower Vehicles, Autonomous vehicle will require safety-compliant MCU’s and optical sensors.

Functional safety needs to be increasingly important for ASIL (Automotive Safety Integrity Level)-compliant MCUs.

· Processor units are predicted to reach almost half a billion dollars by 2020, from just $69 million last year.

· Sensing Requirement. Among the sensors used for autonomous driver assistance applications are optical sensors for navigation purposes.

· Driver assistance applications optical sensors are expected to grow sevenfold in the period spanning 2013–2020.

Requirement Considerations

Hybrid vehicles use discrete power and modules extensively in the engine management system, to control the motor/generator units either when running from the hybrid powertrain, or when energy is being stored under braking. Other considerations such as impact of next-generation wireless in the networking solution can be found in [23, 24].

Need for Insulated-Gate Bipolar Transistors (IGBTs)

IGBT is a high-voltage, high-current switch connected directly to the traction motor in a hybrid electric or electric vehicle. It takes direct current energy from the car’s battery and, through the inverter, converts the alternating current control signals into the high-current, high-voltage energy needed to commutate or turn the motor. The IGBT is an ideal motor inverter switch for 20–120 KW EV motors due to its high efficiency and fast switching. The more efficient the IGBT, the less power is lost to wasted heat, resulting in better “mileage or miles per watt of energy.”

Safety is a main concern for cars and their drivers; therefore, ISO 26262, an international functional safety standard for electrical and electronic systems in automobiles, was published in November 2011. Examples of automotive applications that must meet the standard include EV battery management, steering, braking, transmission, and powertrain. TI is a member of the ISO 26262 working groups and leads the semiconductor subgroup.

Need for a solution to include optimized power efficiency, ranging from high-power modules, microcontrollers, to sensors and discrete components. The following are the key areas:

· The first area is the main inverter, which controls the electric motor to determine driving behavior and captures kinetic energy released through regenerative breaking, feeding recovered energy back to the battery.

· The second is the DC/DC converter module, which supplies the 12-V power system from the high-voltage battery.

· The third area covers the auxiliary inverters/converters, which supply power on demand to systems such as air-conditioning, electronic power steering, oil pumps, and cooling pumps.

· The fourth area is the battery management system, which controls the battery state during charging and discharging to enable the longest possible battery life.

· The fifth area is the on-board charger unit, which allows the battery to be charged from a standard power outlet.

Other requirements include the following:

· Intelligent power switches for anti-lock brake systems

· MEMSs inertial sensors for automotive airbags

· Telematics microprocessor for General Motors’ OnStar

· Increasing electronics integration for infotainment

· Near-field communications technology or NFC

· Longer driving range between charges

· Faster battery charging times

· Safety and security, car access

· In-vehicle networks

· Secure connected mobility

· Car-to-car communication

· Car-to-infrastructure communication

· Remote car management and broadcast reception.

Driverless Vehicle

A driverless vehicle, also defined as a robotic vehicle [25], is capable of sensing its environment and navigating without human input. Robotic cars exist mainly as prototypes and demonstration systems. Currently, the only self-driving vehicles that are commercially available are open-air shuttles for pedestrian zones that operate at 12.5 miles per hour (20.1 km/h). According to a recent study by IHS research, nearly 12 million self-driving cars are being sold annually and almost 54 million will be in use on global highways by 2035 [26].

Autonomous vehicles sense their surroundings with techniques such as radar, lidar, GPS, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Some autonomous vehicles update their maps based on sensory input, allowing the vehicles to keep track of their position even when conditions change or when they enter uncharted environments.

Unlike today’s autonomous cars, Google’s driverless car totally depends on its array of sensors, semiconductor ICs, and algorithms running inside several ECUs. ECUs are solely responsible for

· The safety of the passengers inside the driverless car

· The safety of pedestrians and other vehicles.

MCUs and other semiconductor ICs used in these ECUs need to be compliant with stringent safety certifications such as ISO 26262 or ASIL. ASIL-compliant chips cost more than the standard ICs.

Advanced electronics with higher computational capabilities and the absence of human intervention in driverless cars demands higher functionality – via algorithms – from an ECU. With this higher number of algorithms, the following trends will be evident:

· The number of cores and DMIPS in a processor chip will need to increase

· The use of Ethernet or FlexRay modules for higher bandwidth and secure communication

· An increase in the size of nonvolatile memory for storing huge amounts of data

· An increase in volatile memory to support image processing and to execute code.

Driverless, but not entirely autonomous, autonomous driver assistance systems have active-control mechanisms that take over the control of a car from the driver only to brake or steer in avoiding an accident when the driver does not respond to the warnings.

Adaptive cruise control (ACC) and Automatic emergency braking (AEB) are few examples. An autonomous car is a vehicle that not just spontaneously brakes or steers but drives a car automatically in different driving scenarios without human intervention. As shown in the picture below, Google’s driverless car is still not “fully autonomous” because of limited operational conditions, especially with a speed limit of 25 miles per hour.

Requirement for Vehicle–Vehicle

Safety applications using V2V technology need to address a large majority of crashes involving two or more motor vehicles. With safety data such as speed and location flowing from nearby vehicles, vehicles can identify risks and provide drivers with warnings to avoid other vehicles in common crash types such as rear-end, lane change, and intersection crashes. These safety applications have been demonstrated with everyday drivers under both real-world and controlled test conditions.

The safety applications currently being developed provide warnings to drivers so that they can prevent imminent collisions, but do not automatically operate any vehicle systems, such as braking or steering. NHTSA is also considering future actions on active safety technologies that rely on on-board sensors. Those technologies are eventually expected to blend with the V2V technology. NHTSA issued an Interim Statement of Policy in 2013 explaining its approach to these various streams of innovation. In addition to enhancing safety, these future applications and technologies could help drivers to conserve fuel and save time.

2.9.2 Smart Roadside Challenge

Increasing truck travel demand is resulting in too many legally loaded commercial motor vehicles queued up at inspection stations and, thus, unnecessary delays. Levels of enforcement are not keeping pace with this increase in trucks traveling – resources are being strained to deliver effective enforcement programs to ensure that all users of the highway are safe. The Smart Roadside will allow screening of trucks and drivers using wireless communication between the vehicle and the infrastructure while they travel at highway speeds. Objectives

The objective of the smart roadside is the development and advancement of freight technology and operations by improving data sharing between industry and government. A second objective is overseeing enforcement of government size and weight limits by relying on law and enforcement agencies.

The smart roadside allows truck and driver to be screened with roadside sensors. Regulatory functions are employed while not interrupting the travel of compliant carriers. Sensors can provide shippers greater visibility of good movement. Smart Roadside Requirements

· Standards and specifications are called for weigh-in-motion technology

· Development of virtual Weigh Station sites

· Development of Bridge Weigh-in-Motion Systems

· Test wireless roadside inspection

· E-Tolling

· Over-Height detector

· Weather monitoring station

· In-Vehicle monitoring

· Radiation detection systems

· Truck parking.

Smart trucks will be connected to smart roads.

See Figure 2.23. Technology options that can be used to identify electronically every commercial vehicle include

· Dedicated short-range communications (DSRCs)

· Other RFID such as windshield, license plate, or door-mounted placardc02fig23

Figure 2.23 C-IoT and smart road for trucks

· Commercial Mobile Radio Service (CMRS)

· Optical readers. Sensing Requirement

Smart systems/sensors are to be integrated with existing screening systems:

· Identification

· Dimension measurement (weight, height, width, and length)

· Smart infrared inspection system (tires and bearings)

· Radiation detectors

· Connectivity between trucks (V2V) and overall system.

Details can be found in [27].

2.9.3 Drone

Drones Approved. FAA Gives OK to First Commercial Use Over Land (June 10, 2014)

· An AeroVironment Puma drone [28] undergoes preflight tests in Prudhoe Bay, Alaska, on Saturday, June 7.

· The drone will be used to survey roads, pipelines, and other equipment at the largest oil field in the United States. Surveillance Drone

· Drones can carry various types of equipment including live-feed video cameras, infrared cameras, heat sensors, and radar.

· Mission planning software and tablet application streamline data transport and processing.

· They upload images and flight logs to the cloud server for fast data processing, analytics and access anywhere that can be viewed on mobile or desktop devices. Privacy Concerns

· Drones carry Wi-Fi crackers and fake cell phone towers that can determine your location or intercept your texts and phone calls. Drone manufacturers even admit they are made to carry “less lethal” weapons such as rubber bullets.

· Concern of use among commercial establishments, hobbyists, and others.

Please see an example of a drone carrying a video surveillance camera in Figure 2.24.


Figure 2.24 C-IoT and drone

Considerations in designing Video Surveillance Networks.

· Processing and power management

· IPv6 for mobile devices

· As more of the applications associated with video surveillance, such as sending feeds to mobile devices, operate over IPv6, there will be increasing momentum toward using IPv6 natively within video surveillance networks.

· Governments are also beginning to mandate the use of IPv6 in public sector networking systems.

System Powering/Connectivity/Reliability/Security.

· Powering PoE + (Camera’s power is delivered via data cable)

· POE standard provides 15 W of PoE

· Advanced camera’s capabilities (zoom, pan, tilt) would require 30 W of power (PoE + standard)

· Use of the network’s multicast signaling protocol to deliver video streams to multiple locations

· Redundancy

· Double up on data paths

· Ensure switch equipment support dual power supply units (PSUs)

· Double up on power supply.

System Powering/Connectivity/Reliability/Security.

· Resilient backbone supporting multiple head-ends for data recording, network management, disaster recovery

· Bandwidth

· Higher resolution images mean higher data rates. A 1 Gb uplink from a switch connecting 48 cameras might be enough today, but may well be inadequate within a few years.

· – Bandwidth should be provisioned to allow for up to a fivefold increase in bandwidth requirements within the installation’s lifetime.

· Security

· Configure high-security authentication on all camera-connected ports

· Configure switches to send alarm messages if cameras are ever unplugged

· Ensure that any switch ports to which cameras have not yet been attached are shut down

· Video Analytics

· Create custom criteria-based alerts

· Send alerts to you mobile device

· Technology advancement to smart camera for facial recognition, license plate recognition, compare images.

2.9.4 Machine Vision VTT – Embedded Industrial Solutions

· Machine vision systems for industry automation and microscope applications, to develop sensor prototypes with wireless data interfaces, DSP algorithms for signal extraction using multichannel spectral and statistical analysis, and hardware prototypes of embedded microprocessor systems

· Our expertise fields include developing and choosing suitable optics, illumination, cameras, frame grabbers, and software

· We are able to select, develop, and execute optimal image-processing algorithms

· We also have broad experience with various microcontrollers. We know how to build low-power embedded systems or cost-effective hardware-in-the-loop systems with fault injection capabilities.

Figure 2.25 shows an example of machine vision.


Figure 2.25 C-IoT and machine vision Applications

· Microscope Application – Automatic quality control with machine vision for laser diodes

· Computer vision applications for recognition and tracking of owners unattended baggage in airports

· Data collection and analyzing system of driver’s driving performance (where sensor seat foils are used to measure the driver’s drowsiness)

· Sub-micron resolution in 3D Biomaterial Structuring

· Life science research in biophotonics.

2.9.5 Smart City

Focus on infrastructure, environment, and sustainability (air, water pollution monitoring) in bringing all the intelligence into a market.

According to Forrester Research, smart city is defined as a “city” that uses information and communications technologies to make the critical infrastructure components and services of a city – administration, education, healthcare, public safety, real estate, transportation, and utilities – more aware, interactive, and efficient. Information and Communications Technology (ICT) will play a key role in creating the foundation for smart cities – whether those cities are newer communities being built from scratch or centuries-old metropolises. Demand from local governments, along with similar conglomerations like universities and company towns, will drive incremental opportunities for ICT suppliers in the coming years [29]. C-IoT and Smart City

Of course, being able to control your home via a mobile device is the first step toward a truly “connected” home, and it is something already evident in the marketplace. But beyond mobile control both in-home and remotely, homes are being outfitted with smarter technology that can respond to outside stimulus and actively automate things like climate control and energy.

For example, the Advanced Homes technology allows the home to access meter energy data residing in the cloud and analyze it. The future of connected homes is really about a connected community; a connectivity that is beyond consumption of data by owners or controlling their lighting remotely.

As a starting point, municipalities have begun replacing the current light with LED lighting, which is more economical, reliable, and long lasting. This is due to the rapid advancement in LED technology, increase in production, and consequently decrease in LED pricing. Many estimates suggest that lighting as a whole accounts for about one-fifth of global electricity consumption, and LED-based lighting has had a major impact on that figure.

Figure 2.26 shows an example of what a smart city may consist of.


Figure 2.26 C-IoT and smart city

When Government/municipalities set direction for adopting LED technology, this will have a chain effect on the other domains, industries/utilities and individual/home.


· Cities: Enhance public safety and accelerate environmental initiatives, while keeping costs low with increased operational efficiencies. Provide more valuable services to citizens and build regional economic advantage.

· Utilities:

Grow value continuously from existing smart grid investments and streamline operations with integration across existing back-office systems. Eliminate the need for multiple networks and increase ROI.

· Simple Management:

Make quick adjustments to street lighting based on changes in weather, traffic, public events, or accidents. Implement controlled run time and automated dimming to achieve up to 40% in operational savings.

· Seamlessly Add Smart City Services:

Easily integrate other smart city devices and applications, such as intelligent traffic signal control, networked parking meters, and environmental sensors.

· Choose the Best Approach for Your Needs:

With Smart LED; there are many cost-effective solutions for making the environment for the individual smarter.

But LEDs can do more than just save costs. They also can be a platform for a host of technologies that can monitor what is going on in the vicinity of the light pole. For example, by linking these so-called intelligent streetlights into a network, you have the makings another layer of intelligence for a smart city.

By adding video surveillance cameras to street smart poles, you are adding a security and preventative measures to crime and traffic violation.

Adding electronic banners that can be used for advertisement, alerts, and announcements brings the community closer.

Adding a speaker on each street pole, which then can be used for multi-functional services, such as to deter crimes, and provide instruction in the case of emergency.

All these single-point solutions can be interconnected and data can be analyzed in conjunction with other sources of data to develop scenario analysis (C-IoT).

Thus, there are many opportunities that can be creatively implemented to enhance living and improve safety, lower maintenance cost, and bring the operations to a new level of effectiveness and efficiency. Predictive Technology and Home Automation

Imagine a TV that turns itself on right before your favorite show starts, or based on your past habits, predictively mutes itself when the commercials begin. Imagine a refrigerator that sends you a friendly reminder to pick up more orange juice when you are on your way home from work (which it knows you are right now, based on your GPS location data). The home of the future is one that knows your behavior, and responds to your routine accordingly.

Beyond just learning the homeowner’s preferences and routine, smart homes will be able to self-manage things like energy consumption and climate control. Taking into account the homeowner’s long-term energy goals as well as things like outside weather and city resources based on the smart grid, this future home will actively optimize its activity in real time.

According to Forrester, a smart environment uses information and communications technologies to make the critical infrastructure components and services of a city administration, education, healthcare, public safety, real estate, transportation and utilities more aware, interactive, and efficient.

In our definition, we make the definition more user-centric and do not restrict it to any standard communication protocol. This will allow long-lasting applications to be developed and deployed using the available state-of-the-art protocols at any given point in time. Our definition of IoT for smart environments is the Interconnection of sensing and actuating devices providing the ability to share information across platforms through a unified framework, developing a common operating picture for enabling innovative applications. This is achieved by seamless large-scale sensing, data analytics, and information representation using cutting-edge ubiquitous sensing and cloud computing. This requires vision and innovation that will empower design and development of smart systems [30].

Each day, the world becomes more and more connected through the “IoT” – a phrase that describes the expanding role the Internet plays in everything we do. In fact, according to some estimates, smart, Internet-enabled devices are expected to grow to 50 billion by 2020. That means that virtually smart devices and Internet connections affect every industry across the globe. Whether it is on a personal level – an oven, washer and dryer, watch, phone, car, baby monitor, home security – or whether it is at a larger level like a healthcare network, a school district, or a law firm, we are connected now, more than ever.

Market, Drivers, Positioning

The technology that allows us to be connected on so many levels is astonishing. It is fundamentally changing our world. So many things can now be done faster, more effectively, more efficiently, and more conveniently. They save time, energy, and money, while allowing us to focus our efforts on what truly matters most to us.

Big data too is playing an important role in the technology revolution. And because of big data in the cloud, companies of all sizes can access huge amounts of data to improve products and services for consumers the world over.

Unfortunately, all the good that is coming about with these tech advances can be drastically diminished with one fell swoop of a cyber attack, and next time, it could be your car being hacked instead of your router or cloud data. While the efforts companies are making to bring the best technology to individuals and businesses is laudable, the security measures still have a long way to go.

The list of large-scale data breaches is getting bigger and bigger. Recently, we witnessed the hacking of data of millions of consumers of major stores like Target and Wal-Mart. Microsoft recently revealed that there is a severe flaw in its Internet Explorer browser and millions of consumers were affected by the recent the Heart bleed bug. The list is growing and cyber attacks will continue.

The effects of a cyber attack on one device or company are scary, but when you include a network with thousands of connected devices or a family that is totally connected, the fear worsens dramatically.

Hackers could potentially control drug infusion pumps, which control things like pain medicine delivery, chemotherapy, and antibiotics. Many of the medical assets like in X rays, defibrillators, and other vital systems are found to be vulnerable. A cyber thief could also potentially blue-screen or completely shut down equipment. Information being sent across the network could be changed and manipulated whereby physicians could misdiagnose a patient, or prescribe an unneeded medication.

Two of many things that these findings show case are (i) any industry can be vulnerable to cyber attack and (ii) consumers need to demand that vendors provide the best in data security before they buy a product.

Some of the findings show that the main responsibility for the equipment flaws was with the vendors themselves. Too much equipment did not require any authentication and many of the hard coded passwords were too simple like “admin” or “1234.” And while much responsibility does lie with the vendors, companies too need to be aware of the dangers. Many hospitals were totally unaware of the risk and problems.

Technology companies are aware of the security threats IoT imposes. In fact, Cisco has launched the “Internet of Things Grand Security Challenge,” offering up to $300 000 worth of prizes for Internet security innovation in hopes of finding a solution. While such efforts should certainly be lauded, it begs the question how far behind innovation in security will fall behind innovation in the IoT.

What does this all mean? Most importantly it means that individuals and companies need to take every necessary step to ensure their cyber safety. That safety cannot be taken for granted anymore. Fortunately, by taking the often times simple and necessary steps all entities can protect themselves from cyber attacks. As important as it is to take action, companies and people need to stay up to date with security advances, install the latest software, update passwords, implement new technologies, And do everything possible to keep their data and network safe. Requirements

1. Individual. Smart shopping Home – for example, identify food items to buy, identify stores that have sales or coupons; perhaps, order online and have a smart car to pick up the items on being notified when they are ready

2. Industry. Smart retails, shopping malls, parking, transactions (epos),

3. Infrastructure. Smart parking, smart street lighting, digital signage, public safety, and disaster management.


1. [1] Weightless (accessed 18 November 2014).

2. [2] Wikipedia (accessed 18 November 2014).

3. [3] Behmann, F. (2005) Impact of Wireless (Wi-Fi, WiMAX) on 3G and next generation – an initial assessment. IEEE Xplore, Elecro Information Technology, 2005 IEEE International Conference, Lincoln, NE, May 22-25, 2005, Print ISBN: 0-7803-9232-9, 2F10832%2F34150%2F01626995 (accessed 18 November 2014).

4. [4] Behmann, F. (2005) Business view of the convergence/integration of Wi-Fi, WiMAX and 3G cellular. IEEE Communications and Signal Processor Societies Joint Chapter, Austin, TX, June 16, 2005,

5. [5] Behmann, F. (2010) Power Architecture Enabled Differentiated Solution for LTE. Embedded Systems, Sep 1, 2010, (accessed 18 November 2014).

6. [6] Behmann, F. (2012) SOC architecture evolution as a key driver of wireless network transformation. International Conference on Communications, ICC 2012, Ottawa, Canada, June 10–15, 2012, Session SA03, (accessed 18 November 2014).

7. [7] ITRS (2007) ITRS, 2007 Edition, Executive Summary, pp. 8–9, (accessed 18 November 2014).

8. [8] ITRS-System Drivers (2007) ITRS, 2007 Edition, System Drivers, pp. 3–7, (accessed 18 November 2014).

9. [9] Behmann, F. (2009) The ITRS Process Roadmap and Nextgen Embedded Multicore SoC Design, March 22, 2009, pp. 1–4, (accessed 18 November 2014).

10.[10] Behmann, F. (1980) Virtualization for Embedded Power Architecture. Electronic Product Magazine, pp. 32–33, SEPTEMBER 2009.

11.[11] Open Networking (accessed 18 November 2014).

12.[12] Computer Hope (2007) Metcalfe’s Law. (accessed 18 November 2014).

13.[13] Wireless Sensor Networks (accessed 18 November 2014).

14.[14] IETF RFC 4919, (accessed 18 November 2014).

15.[15] Research2guidance (accessed 18 November 2014).

16.[16] Behmann, F. (2014) IP video surveillance – an irreversible trend for the future. IEEE Communications & Signal Processing Joint Chapter, Austin, July 17, 2014, (accessed 18 November 2014).

17.[17] Behmann, F. (2008) Wireless Technology and Applications Trends, Freescale FTF, June 16, 2008, Session AN142.

18.[18] Behmann, F. (2012) Developers … how to meet advanced SoC architecture requirements? Design-West, San Jose, CA, March 26–29, 2012.

19.[19] Behmann, F. (2012) Power Architecture Combines Rich Features for Embedded. RTC Magazine (May 5, 2012), (accessed 18 November 2014).

20.[20] Modern Material Handling (2006) RFID Market to Reach $9.2 Billion in 2014 and More Than Triple in Next Decade, _in_2014_and_more_than_triple_in_next_decad (accessed 18 November 2014).

21.[21] IFR (accessed 11 December 2014).

22.[22] Mouser (accessed 18 November 2014).

23.[23] Behmann, F. (2006) Convergence challenges and solutions for next-generation wireless networking. Keynote presentation at IEEE- MTT Wireless, Jan 15–20, 2006.

24.[24] Behmann, F. (2007) Non-automotive technologies for the automotive engineer – networking solution offering. Freescale NCSG Conference, June 25, 2007, Session AA331.

25.[25] (2014) The Future of Driving – Assistive Technology; Autonomous Vehicles, March 21, 2014, (accessed 18 November 2014).

26.[26] (2010) Self-Driving Cars Moving into the Industry’s Driver’s Seat, (accessed 18 November 2014).

27.[27] DOT.Gov SmartRoad (accessed 18 November 2014).

28.[28] Avinc (2012) AeroVironment Puma Drone, (accessed 18 November 2014).

29.[29] Forrester Research (2014) Forrester Research on Smart Cities, (accessed 18 November 2014).

30.[30] Behmann, F. (2011) Power architecture 20 years of innovation empowering design and developer community. CSIA-ICCAD Annual Conference and China IC Design Industry, Beijing, china, year-achievements-exhibition/ (accessed 18 November 2014).

1 NHTSA (National Highway Traffic Safety Administration).