C-IoT Cloud-Based Services and C-IoT User Device Diversity

5.1 C-IoT Cloud-Based Services

5.1.1 Introduction and Drivers to C-IoT Service Platform

Internet of Things (IoT) vision is expected to be distributed cloud-based computing, advanced sensors and big-data analysis. RFID and Sensor Network

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. These result in the generation of enormous amounts of data, which have to be stored, processed and presented in a seamless, efficient, and easily interpretable form. This model will consist of services that are commodities and delivered in a manner similar to traditional commodities. Cloud computing can provide the virtual infrastructure for such utility computing which integrates monitoring devices, storage devices, analytics tools, visualization platforms, and client delivery. The cost-based model that Cloud computing offers will enable end-to-end service provisioning for businesses and users to access applications on demand from anywhere.

Advancement in technology in the networking and telecom areas drives a new wave of architectural design and new Market Opportunities. More details are provided in [1]. Sensor Fusion

Sensor fusion is a technology that has come of age, and at just the right time to take advantage of developments in sensors, wireless communication, and other technologies. With sensor fusion and sensor hub chips, it is now possible to efficiently interface to a variety of digital sensors.

A current trend combines a microcontroller with three or more MEMS sensors in a single package. The microcontroller is an ultra-low-power that process data sensed by external sensors such as for gyroscope, magnetometer, and pressure sensors. Functioning as a sensor hub, it fuses together all inputs with a set of adaptive prediction and filtering algorithms to make sense of the complex information coming from multiple sensors.

While quite a lot of functionality can be achieved at a local level, interaction with the Cloud is where the fun really begins. Remote sensor data can be processed by a sensor fusion device and sent to the Cloud for recording, further analysis, or even to trigger an action. Social and Sensor Data Fusion in the Cloud

Mobile phones increasingly become multi-sensor devices, accumulating large volumes of data related to our daily lives. At the same time, mobile phones are also serving as a major channel for recording people’s activities at social-networking services in the Internet.

These trends obviously raise the potential of collaboratively analyzing sensor and social data in mobile cloud computing. Participatory sensing, for instance, enables to collect people-sensed data via social network services (e.g., Twitter) over the areas where physical sensors are unavailable. Simultaneously, sensor data are capable of offering precise context information, leading to effective analysis of social data. Gateways

Capitalize on strong presence of gateways – connecting to the Embedded local area network (LAN) and wide area network (WAN) – Cloud Computing companies are announcing initiatives to create standards for gateways that can deal with a flood of data from devices associated with the “IoT.”

Software may be a bigger piece of the IoT puzzle than connectivity itself. With sensors, cameras, machinery, medical equipment and countless other objects gathering data, and various applications processing and analyzing that information, something will need to tie all those elements together. Smart portable device companies are announcing a cloud-based platform for developing back-end IoT applications, with the aim of saving effort for enterprises. C-IoT Service Platform

For the realization of a complete IoT vision, an efficient, secure, scalable, and market-oriented computing and storage resourcing is essential. Cloud computing is the most recent paradigm to emerge, which promises reliable services, delivered through next generation data centers that are based on virtualized storage technologies. This platform acts as an aggregator of data from multiple ubiquitous sensors; as a computer to analyze and interpret the data; as well as providing the user with easy to understand web-based visualization. The service platform usually consists of sensor fusion software components, which performs ubiquitous sensing and processing works in the background, hidden from the user.

The service platform will consolidate data collected from multiple appliances from multiple IoT service providers. This represents a significant milestone in the evolution of the IoT, establishing a standardized and secure platform for service providers to quickly and cost-effectively introduce differentiating IoT services.

Heavy-duty processing could be done inside the service platform, or it could happen inside the web-connected data centers, or the cloud.

Cloud computing promises high reliability, scalability, and autonomy to provide ubiquitous access, dynamic resource discovery required for the next generation IoT applications. Consumers will be able to choose the service level by changing the Quality of Service parameters.

The C-IoT service platform will support applications in smart energy, smart meters, tele-health, and other smart home services.

5.1.2 Classes of C-IoT Cloud Computing

Similar to cloud computing, there are three primary classes of IoT cloud computing: public, private, and hybrid. Cloud computing service providers (CCSPs) such as Google and Amazon that provide services over a WAN are considered to be providing public cloud computing solutions. There are three categories of public cloud computing solutions. They are: Software as a Service (SaaS)

Software as a Service (SaaS) applications have been growing rapidly ever since the mid-2000s, led primarily by the CRM category, and followed by other departments such as HR, finance, and marketing. In fact, the current buzz in the SaaS industry is all about the “marketing cloud.”

In one form of SaaS, an independent software vendor (ISV) such as Salesforce.com hosts an application in one or more of their own data centers. In another form of SaaS, an ISV such as Virtual Bridges hosts an application in one or more data centersprovided by an Infrastructure as a Service vendor such as Amazon. In either case, the application is provided to users on a usage basis. Infrastructure as a Service (IaaS)

The two primary forms of infrastructure as a service (IaaS) are compute and storage. Providers of IaaS solutions typically implement their solutions on a virtualized infrastructure and charge for them on a usage basis. Platform as a Service (PaaS)

Platform as a service (PaaS) is the delivery of a computing platform and solution stack as a service. PaaS offerings from providers such as Force.com include workflow facilities for application design, application development, testing, deployment, and hosting as well as application services such as web service integration, database integration, and security.

There is significant interest in public cloud computing solutions, most notably SaaS and IaaS. However, due in part to concerns about security and data confidentiality, most IT organizations will, like Bechtel, decide to adopt the same techniques internally as is used by CCSPs such as Google and Amazon. That approach is referred to as private cloud computing.

A hybrid IoT cloud computing solution involves a combination of services provided by the IT organization itself as well as by one or more CCSPs. For example, an IT organization may either already have, or be in the process of acquiring a four-tier application. The IT organization may decide that for security reasons that it wants to host the application and database servers itself. However, in order to improve the interaction with the users of the application, the IT organization may also decide to let a CCSP host the web tier in numerous data centers around the globe.

As noted, private cloud computing involves IT organizations implementing the same techniques themselves as are typically associated with public cloud computing solutions.

5.1.3 C-IoT Innovative and Collaborative Services

Cloud-based services are the future for creative, innovative, and collaborative services. IoT Innovative and Collaborative Services represents the aggregate of IoT Point solution that analyzed in a collaborative fashion and is scalable by the complexity, security, and performance of an application. Here are some potential areas of IoT cloud-based services:

· Leveraging SaaS to drive Innovation and Results. Competition is intense. Market forces are increasingly volatile. And business leaders are under even more pressure to drive innovation. How can you make every area of your organization more effective-and do it faster than ever, with fewer resources? The answer is in the cloud. How sales, finance, marketing, procurement, and supply chain leaders are using cloud solutions – and SaaS in particular – to become more agile, efficient, and customer-focused. Such solution will respond to: (i) How industry leaders are using SaaS capabilities to drive business process innovation across their value chain. (ii) Ways to balance the needs of line-of-business and IT decision makers to deliver more customer value faster. (iii) How you can reduce time-to-value and respond to market changes faster using SaaS solutions

· Make your Business Smarter with Cloud-based Analytics. Every industry faces incredible growth in the amount of data collected each day, even each hour – customer behavior, market changes, investments, supplier performance, sales figures. Cloud analytics solutions are designed to handle this tidal wave of data while providing insights quickly, delivered through SaaS can create competitive advantage using traditional business intelligence methods and deeper analytics embedded within business processes. SaaS-based business analytics can become more agile, serve the customer better, and deliver business results.

· Saas connect people with collaborative Business Networks. Now more than ever, business gets done through connections. Information sharing, community building, and collaborative planning are necessary ingredients for staying effective. SaaS is rewiring the approaches for how people and information are aligned. Entire value chains and business ecosystems are now collaborating in the cloud in ways that were not possible in the analog world. Internal teams can access information in more fluid, more intuitive ways.

· Saas provides collaborative intelligence by correlate data received from Fitbit with data from Nest thermostat and LED lighting such that when, say going to sleep, with just moving your hand with Fitbit wearable device, it trigger two actions adjusting the temperature of the thermostat and dim the LED light.

5.1.4 The Emerging Data Center LAN

There are four-stage evolutionary path that IT organizations can take to evolve their data center LANs. A critical characteristic of the evolutionary path is that it is flexible. Virtualization plays key role is the consolidation and management of data centers. Data centers consume a lot of power. Energy management starts from the SoC to server. Example on SoC energy management is provided in [2]. Distributed Servers

As part of stage 1, most IT organizations begin the process of assessing the cost/benefits of a centralized versus distributed servers. In some cases, consolidating servers out of branch offices and placing them into centralized data centers could result in reduction of cost and enables IT organizations to have better control over the company’s data. In addition to consolidating servers, during this stage many companies also reduce the number of data centers they support worldwide and most begin to virtualize at least some of their data center servers. During this stage, some IT organizations begin to implement LAN switches with 10 Gbps interfaces to support the anticipated increase of I/O needs.

The overall approach to data center design at this stage is characterized by having functionality such as servers, storage, LAN switches, firewalls, and load balancers be both manually configured and dedicated to a single service or application. This approach to data center design and management results in an increase in the overall cost of the data center. It also increases the time it takes to deploy a new service or application since new infrastructure must be designed, procured, installed, configured, and tested before a new service or application can go into production.

The trend is to have hybrid clouds interconnecting global clouds with private clouds. Data Center Virtualization

Everything Virtualized – Gateways, network appliances/servers, storage servers, and sensor nodes.

One of the key characteristics of stage 2 is that during this stage IT organizations implement server virtualization more broadly. The increased deployment of server virtualization at this stage leads to greater flexibility and the increased movement in server-to-server communications. Another change that occurs during stage 2 is that as IT organizations deploy servers with an increased number of cores, the number of virtual machines (VMs) per physical server typically increases proportionally. One impact of the increase in the number of VMs per physical server is that the network I/O requirements of the multi-core physical servers that have been virtualized in stage 2 begin to exceed the capacity of the existing GbE and multi-GbE aggregated links.

However, the biggest change to the traditional IT model that occurs during stage 2 is that driven both by the need to save money and to reduce complexity, many IT organizations implement a two-tier data center LAN, consisting of access and core switches, in at least one of their data centers. Cloud Optimized Data Center LAN – Hybrid Clouds

In the traditional data center LAN environment, the data network is kept separate from the storage network. In stage 3, some IT organizations begin to experiment with deploying a unified data center switching fabric.

In stage 3, many IT organizations begin to deploy a new generation of Lossless Ethernet technologies that are based on a collection of standards that are commonly referred to as IEEE Data Center Bridging.

During stage 3 the bandwidth efficiency and availability of Layer 2 data center LANs with redundant links can be greatly improved by assuring that the parallel links from the servers to the access layer and from the access layer to the core layer are always in an active–active forwarding state.

Another major change that occurs in stage 3 is that many IT organizations begin cross train key employees and by creating goals and a reward system that encourages employees to take a more holistic view of IT. They also do this in part by beginning to implement common tools such as service orchestration. The Near Term Future

There is no doubt that data center LANs will continue to evolve past what IT organizations achieved in stage 3. For example, virtually all IT organizations will continue to expand their implementation of a unified fabric within data centers and to implement continuingly more sophisticated automation. Many IT organizations will also increase efforts to reduce the impact of organizational silos.

Another possible change to data center LANs in the near term future that will build on top of what was already achieved is that many IT organizations are likely to extend their unified fabric both between their own data centers as well as between their data centers and one or more data centers provided by a CCSP. One obvious advantage of doing this is that it enables IT organizations to efficiently move workloads between data centers and hence enhances the ability of the IT organization to implement disaster recover/business continuity solutions.

5.2 C-IoT User Device Diversity

5.2.1 Introduction

Portable and wearable computing introduced 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. 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 doctor by triggering a call over the cellular network.

The “cloud” will become more intelligent, not just a place to store data – Cloud intelligence will evolve into becoming an active resource in our daily lives, providing analysis and contextual advice. Virtual agents could, for example, design your family’s weekly menu based on everyone’s health profiles, fitness goals, and taste preferences.

Many products and reference designs for wearable devices were released to the market. Examples: smart earbuds, smart headset, and a smartwatch to a device – developed with Rest Devices for Baby product line – that can be worn on an infant’s onesie that monitors the baby’s vitals and sends the data to a coffee mug, where it can be displayed. 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 everyday.

With open-source OS like Android, the fast growing IoT and sensor’s technology are empowering mobile developers to connect and control objects like thermostat, light fixtures and experiment with an endless range of products.

Access to complete Bluetooth Smart SoC, plus embedded Wi-Fi, enables OEMs of all sizes to seamlessly deliver connectivity to battery-operated devices for sports and fitness, health and wellness, security, automation, and more.

Making available Smart Development Kit through strategic distribution partners will accelerate time-to-market of IoT products and solutions that matter. The hardware development kit opens the door for original equipment manufacturers (OEMs) to develop products for the “IoT” with ease. It provides access to a low-power client device with an integrated Bluetooth Smart (formerly Bluetooth Low Energy) software stack and application profiles, offering OEMs an easy-to-use, cost-effective embedded wireless solution with a small footprint to inspire connectivity in a new range of devices.

5.2.2 C-IoT Developers/Platform

Collaborative Internet of Things (C-IoT) is empowering growth of Entrepreneurs and software developers at three areas:

1. Mobile devices for innovative IoT applications

2. Gateway-based applications

3. IoT cloud services.

Much of today’s IoT development focuses on technology. Should I use 2G or LTE, WiFi or mesh networks? Should I embed connectivity directly in my device, or use a gateway? How do I make robust and compact enough devices? How do I make a wearable with the best battery life? Which of the 50+ IoT cloud platforms is the right one for my application? Is my home automation solution secure against hackers? How can I use artificial intelligence to optimize the maintenance schedule of my factory robots? Entrepreneurs and Software Developers for Mobile Devices

The evolution in mobile since 2008 has resulted into creation of community of entrepreneurs and developers for both iOS and Androids.

Android and iOS won because they used fundamentally different business models from those of Nokia/Symbian, Windows Mobile, and Blackberry. That in turn has created an abundance of apps and devices. This entrepreneur-driven demand creates new markets that are several times bigger than the existing ones. Consumers Drive Application Development for Mobile Devices

The demand for iPhones (and later for Android smartphones) did not come from business users. It came from consumers craving the hundreds of thousands of apps available on these devices. The combined value of all those apps is beyond the utility that Microsoft could ever hope to create on Windows Mobile devices.

Platforms thrive by a steady stream of innovation by developers, experimenting day and night in their quest to find new use cases. The solutions to these use cases drive sales of iPhone and Android phones.

WiFi, social networks, smartphones, and tablets all first found grassroots success with consumers and only later started to appeal to enterprises.

The most newsworthy example is the battle brewing between Google and Apple to win control of the consumer market. Through a series of acquisitions, these two giants are locked in a mega-struggle to make their smartphones the central element of a much bigger market – the smart home – including intelligently connected and controlled lighting, heating, and entertainment. C-IoT Developers

Today’s forecasters predict fast, attractive growth of the market as it is. They promise tens of billions of devices in the market by the end of the decade, based on the current state of the market, known demand and technology evolution.

If developers and entrepreneurs adopt IoT technology as swiftly as they did Android and iOS, there will be well over 4 million IoT innovators at work by the end of this decade. See Figure 5.1. Think about how much demand they could create for the IoT industry.

As a contrast, VisionMobile forecasts a fast growth of the IoT developer base in the next years, reaching well over 4 million innovators and entrepreneurs by the end of the decade. With every new use for IoT technology that they discover, demand will grow and this market will become more attractive still [3].


Figure 5.1 IoT developers. Source: VisionMobile

Steady stream of developer-driven innovation is already emerging in C-IoT.

· Developers are innovating on asthma inhalers (Propeller Health), basketballs (94fifty), smoke detectors (Nest), and bottles of booze (Beverage Metrics’ Tilt). IoT solutions can count pests on the farm (Spensa Technologies), measure radiation around Fukushima (SafeCast), warn you when the sewage system floods (Don’t Flush Me), let you express yourself (Switch Embassy’s tshirtOS) or protect human rights activists (the Natalia Project).

· Wearables (Pebble, Nike+), connected cars (GM, Ford, Dash Labs), and buildings (SmartThings, Panoptix) are opening up APIs for third-party developers, thereby facilitate development of C-IoT applications that inter-operate among multiple point-solutions of Smart things. This will further drive the wearables market to new heights.

· Hackers are combining IoT devices and APIs into amazing new use cases. Like 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.

These wide-ranging and often unexpected devices, services, and apps that come from a growing community of IoT developers is the main factor that will drive demand for IoT to unseen heights.

5.2.3 Wearable Devices – Individual

Work-life balance itself has so 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 wearable comes in.

Thus, wearable devices are typically associated with consumers. Consumers are now connecting their physical bodies to electronic devices such as Fitbit and other health monitors. The value of a wearable device lies in its ability to connect to a smartphone or the Internet with minimal impact on battery life.

Wearable need to go beyond simply measuring steps, heartbeats, and sleep cycles and attain the ability to measure the mood of individuals or to continuously monitor and control heart rate, blood glucose, and other health metrics from their smartphones. Beyond monitoring, users can upload this information to “the cloud” for real-time analysis and graphical measurement, liberating the data from a singular sensor device and allowing it to be accessed from any client device at any time.

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.

As the market continues to gain momentum, there will be wide variety of business opportunities in this growing space to offer the breadth of IP and customized components that enable creative new smart wearable devices to be connected.

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.

Embedded Devices, SoC integration versus SIP (RCP) versus modules – Industry Applications

As price of sensors continue to decline and microcontroller unit (MCU) processing, the future sensors become more intelligent by providing local processing and limited storage. This becomes attractive to many of the Industry Applications such as energy management. Hence, various design options are examined such as integration of the MCU with the sensor as an integrated SoC, exploring option of System In Package option and having modular approach. Power management is a key consideration in determining the right approach.

5.2.4 Harvesting (Self-Powered Nodes) – Infrastructure Applications

In general, sensors associated with public infrastructure applications such as for asset tracking and logistics may rely on self-powered to eliminate the cost to cover services for battery replacement.

Smart appliance sales are rising. Wearable fitness trackers are creating a new market in quantified health. Apple is making an entry into the home automation and health industries, through IoT applications.

5.2.5 Embedded Devices and Servers

Healthcare and home-automation have been pushing the market forward, but there are plenty of other industries that wearable technology and embedded systems can disrupt. On a macro-level, there are two major entry points into IoT across industries – servers and embedded processors.

Powerful, embedded systems are essential to creating disruptive IoT devices. A lot can be done with low-cost sensors connected to WiFi, but it’s advances in high-end embedded devices that will grow the market. This will include healthcare technology, digital signage, industrial automation, and even casino gaming.

As the high-end wearable and embedded market continues to grow, there will be a corresponding growth in the amount of data produced. In fact, a lot of the value of such technology will come from the highly targeted, highly specific data it produces. This means companies will need enhanced data processing capabilities, along with business intelligence software, to sort and analyze the information influx.

In short, more wearable and embedded devices will create more data, which will increase the need for larger data centers. More data centers mean more servers, which equals a huge opportunity for both companies.

In this field, Intel x86-based servers have been the industry standard for years. Gartner estimates that Intel sales are 92% of all server processors in 2013 versus AMD of 7%. Intel also recently invested $740 million in Cloud era, a big data analytics company. Their intention is not to compete with the cloud computing solutions from companies such as Microsoft and Amazon Web Services, but rather to spur the adoption of Hadoop among enterprises. Similar to embedded systems, increased cloud usage ultimately means increased server sales.

AMD, on the other hands, announced a new “ambidextrous” server chip that bridges ARM and x86 processors, a product they hope will appeal to companies looking for greater flexibility. AMD also continues to invest in the low-cost, micro-server market, where they hope their graphics-experience and APU tech will give them an edge. Theoretically, micro-servers are poised for wide adoption in data centers, and could help improve energy efficiency. So far however, there has been little movement, for a variety of reasons.

IoT will continue to change how industries operate, and there are significant opportunities both in embedded systems and servers. AMD seems to have an edge into the embedded world, while Intel is poised to maintain its dominant server position. Intel’s resources make them a large threat, especially in the high-end embedded market and in wearable, if they can promote adoption of their Edison processor. Given AMD’s projections that the embedded market will soon be worth over $9 billion, it is likely that neither company is going to cede the area without a fight.

5.2.6 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 wearable.

5.2.7 IBM Watson for Cognitive Innovations

Among the major initiative by companies is that of IBM by establishing early 2014 IBM Watson Group, a new business unit dedicated to the development and commercialization of cloud-delivered cognitive innovations. The move signifies a strategic shift by IBM to accelerate into the marketplace a new class of software, services and apps that think, improve by learning, and discover answers and insights to complex questions from massive amounts of Big Data.

IBM will invest more than $1 billion into the Watson Group, focusing on development and research and bringing cloud-delivered cognitive applications and services to market. This will include $100 million available for venture investments to support IBM’s recently launched ecosystem of start-ups and businesses that are building a new class of cognitive apps powered by Watson, in the IBM Watson Developers Cloud. A high level appreciation of Watson winning Jeopardy in 2011 is provided in [4].

5.2.8 Far-Reaching Consequences

When these brain-sensing wearable become as pervasive as Fitbits, corporate cultures around the world will be visible for all to see. Employees seeking better opportunities would have an in-depth view into the working dynamics of any particular company. High-school students considering careers in a particular field will be able to evaluate its pros and cons more accurately. With aggregate employee sentiment being widely available, HR departments will become increasingly important in ensuring employee retention.

HCM software is the closest thing to measuring and tracking information about employees. However, none of the existing cloud HCM solutions adequately capture the sentiment of their most valuable assets – their employees.

During the post World-War II economy, manufacturing equipments that could produce a better widget faster and cheaper were regarded highly as prized assets because they were an important part in providing a competitive edge. In the knowledge economy, happy, engaged, and intellectually stimulated employees are the ones that provide their companies with competitive differentiation. That is why the next cloud revolution, the People Cloud will not be about employers using HCM software to measure the numerical worth of their employees, but rather millions of workers driving change in their organizations through real-time sentiment data.

The world around us is changing at speeds never seen before. Mobile devices are collecting countless levels of data through innovative technologies such as motion coprocessors, gyrometers, A, ambient light sensors, application analytics, and more.

We are also seeing a huge increase in the number of “smart” homes equipped with connected lighting, air conditioning, all the way to internet-connected refrigerators. All this is on top of the numerous connected devices already found in modern homes such as iPhones, iPads, printers, connected TVs, game consoles, and so on, and did I mention the rise in connected cars?

With the huge leaps that digital technology has made over the past few years, we are starting to see companies tapping deeper and deeper into these massive data streams, positioning us on the verge of a new era of analytics and measurements.

5.2.9 C-IoT (Collaborative IoT)

OEMs creating wearable products require interoperable technology that will allow these new devices to connect with smartphones, tablets, and wireless gateways available today. Since many companies are able to power the Wi-Fi and Bluetooth in the majority of smartphones on the market today, the wireless SoCs are an ideal choice for OEMs developing consumer products that are designed to seamlessly communicate with other mobile devices on the market. The C-IoT service platforms leverage sensor fusion software framework components, to perform ubiquitous sensing and processing works transparent from the user. The 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.


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2. [2] Behmann, F. (2010) Energy Management in Power Architecture, Embedded Insights, December 21, 2010, http://www.embeddedinsights.com/channels/author/fawzi-behmann/ (accessed 18 November 2014).

3. [3] VisionMobile http://www.visionmobile.com/blog/2014/06/who-will-be-the-ios-and-android-of-iot/ (accessed 18 November 2014).

4. [4] Behmann, F. (2011) The Inner Workings of IBM’s Watson. A video interview by Bill Wong of Electronic Design Magazine (Oct. 6, 2011), http://www.engineeringtv.com/video/The-Inner-Workings-of-IBMs-Wats;ESC-Boston-2011-Videos (accessed 18 November 2014).