Android Wearables (2015)
Part I. Concepts
Chapter 2. The Internet of Things
WHAT’S IN THIS CHAPTER?
· ➤ The Internet of Things and the Internet of Everything
· ➤ The 2020 vision: 50 billion connected devices
· ➤ Categories of devices
The Internet of Things (IoT) is a concept that states that everything that can be connected will be connected. This computing paradigm evolved from both ubiquitous computing and pervasive computing. IoT has three basic rules:
1. Connectivity is key. Objects will connect to each other either directly or through other devices using many technologies. Connectivity implies over the air (OTA) updates. Suppose a series of embedded devices in the home required firmware upgrades. If they didn’t follow an OTA strategy, you would have to run a cable to each one to change their basic configuration.
2. Each device will have a unique identifier to distinguish it from others via software. Technologies such as IPv6 allow devices to have searchable identifiers (IP numbers) within the group, but internally the devices need a unique identifier to distinguish them from the rest.
3. Communication devices should provide encryption so that users can hide information as needed.
HOW WEARABLES RELATE TO IOT
Wearable devices play an important role in this vision. They are IoT devices in the sense that they are always connected to the Internet, even if it is through a device such as a phone or tablet. Many people already own or plan to purchase wearables for fitness or medical reasons.
Eventually wearables will become essential work tools. Imagine factory workers wearing bracelets that report their vital statistics as well as information about their environment. Imagine workers processing food using gloves that analyze the food’s quality at the chemical level. Imagine police officers wearing glasses that display information about passing vehicles. Imagine nurses wearing rings that monitor patients’ blood pressure and upload the information to their chart.
The future of wearables goes hand in hand with the future of IoT. You could say that one informs the other and that one couldn’t exist without the other.
THE PROMISE OF CONNECTIVITY
In February 2011, communications technology company Ericsson published a whitepaper describing the company’s vision of 50 billion connected devices by the year 2020. Connected technology will reach many fields. It will cause more disruption in some fields than others, as shown in Figure 2.1. This figure is based on a memo from Cisco presented in January 2014.
FIGURE 2.1 Information and communication technologies (ICT) disruptive potential versus speed of uptake by field of application (source: Cisco)
Connectivity is one of the most important topics discussed in this book. Only networks that allow for exponential scalability will make it possible. The decrease in cost per gigabyte of transfer is also an important factor in the explosion of connected technologies. This vision goes beyond smart living and game technologies. It can be applied to every field of our lives.
Ericsson’s report was the beginning of a war of numbers. Cisco estimated that by 2020 the world population will be 7.6 billion, compared to the current 7.2 billion. Ericsson suggested that, despite this relatively slow population growth, the number of connected devices will increase from the current 12.5 billion to as many as 50 billion. If you think about simple home devices that can be connected, such as electric meters and smoke alarms, 12.5 billion sounds too small.
An online article in Time magazine after the global consumer electronics and consumer technology trade show CES 2014 elaborated on Cisco’s vision. It looked at market researcher IDC, which projects that by 2020, 220 billion connected devices will be in use. Every company predicts a different number of connected devices because each company uses a different way to define “connected device.”
We will say that a device is connected as soon as it can reach the Internet, even if it does so through a third party. In this way, your refrigerator, your car, your mobile phone, your garden sensor reporting soil moisture, and your activity band are all connected devices. They are technological tools that possess some computational power, that can connect to the Internet, and that can be used to read a sensor or control an actuator (or both).
Big data refers to collections of data that are so large that they cannot be computed by traditional means. This could be due to the multiplicity of data sources to be compared or to the size of each one of the records. Here are some examples of big data:
· ➤ The location of every mobile phone in a certain country
· ➤ The collection of all Google searches for white Americans over 25 years of age
· ➤ What products of a certain brand are bought at supermarkets in Spain by customers younger than 40, cross-referenced with the location of the most commonly bought products in the store
All these cases can provide interesting sets of data that, when explored carefully, could become interesting from both a research and marketing point of view. But how are we meant to approach the problem of all of these data sets? How will we generate them? Who will curate that data, filter it, and make it available?
Cisco brings to the conversation the idea that the amount of data generated in this globally connected network, which some people call the Internet of Everything (IoE), will be so big that we will need distributed computation closer to the data sources. It will be virtually impossible to process all the data sent to the cloud. Think about the number of sensors and actuators in a car. It would be impossible for all the cars in the world to report all that data to the cloud. The systems will have more embedded intelligence and will share only meaningful data.
Silicon vendors such as Qualcomm, Atmel, Intel, Broadcom, ST, and Texas Instruments are trying to produce the best platforms to stay always on and always connected. Those handling the spectrum, such as AT&T, Telefonica, and Vodafone, have their own way of understanding where the value of IoT lies. The following sections discuss different applications of IoT beyond wearable computing.
CONNECTED DEVICES IN THE HOME
In the home, it makes sense to connect security and safety devices. An IP security camera that streams to the Internet, a smoke alarm, and a burglar alarm are perfect examples. Other examples include anything dedicated to measuring and accounting for how you use resources, such as your electric, water, and gas meters. They all have a clear application; being connected brings an added level of service. Other machines in your home also can benefit from being connected.
Suppose you buy an induction stove. This type of stove is probably the most complex piece of engineering in your kitchen. It contains multiple processors that regulate radio waves that heat metallic materials. Besides having all the typical intelligence of any device in the home, these appliances run small neural networks to, for example, determine whether the pot on the stove is made of steel or aluminum. The latter is much less efficient at transferring heat. Therefore, the stove will refuse to heat an aluminum pot. Many of these operations require dedicated microchips (ASICs) instead of general-purpose processors like the ones commanding your microwave. As a result, an induction stove ends up being more expensive than almost anything else in your kitchen.
Currently, the price of adding something as simple as a WiFi or Bluetooth modem to your stove is nothing compared to the appliance’s cost. But other devices, such as a water heater or an inexpensive coffeemaker, are much less expensive, so the price of connecting them to the Internet might not be worth it. If there were a good reason to connect such appliances, we probably would have done so already.
The SandS project, which stands for social and smart, is a series of pilot projects undertaken by the European Commission in which intelligent home appliances connect to the Internet. The project, which started near the end of 2012, has brought together researchers from seven European institutions and companies, working to build connected washing machines, ovens, refrigerators, bread-baking machines, and other appliances.
If you need help programming your washing machine to remove a strawberry stain from a shirt, you can tell the system to look for appropriate cleaning “recipes” in the SandS cloud service. It translates a natural-language request such as “Remove strawberry stain from white shirt” into a piece of XML that gives you the best recipe for your specific machine. The program then is automatically downloaded to your machine, leaving it ready to run.
Another example is the more complex activity of baking. It is a long process that requires adjusting the temperature as you go, or the direction of the heat (from the top or bottom, with or without ventilation). Again, the technical “recipe” could be downloaded from the cloud to the oven.
This process is what the SandS project is experimenting with, and this is what the connected home could be like if the researchers behind the project succeed. However, remember that, even if your coffeemaker is connected to the Internet (see Figure 2.2), you still need to put in water and coffee grounds. And even if your washing machine downloads “recipes” from the cloud, you still need to put the clothes in.
FIGURE 2.2 Connected coffeemaker for the SandS EU research project (source: Arduino)
CONNECTED DEVICES ON THE GO
What we call the on the go (OTG) category of IoT devices refers to devices that people can either wear or carry as they move. This group is composed of mostly small, lightweight gadgets that fit in our pockets. They are usually not connected directly to the Internet, but to our smartphones or tablets. Some of them are wearables, but that is not their defining characteristic.
OTG sensors are already common. They create small networks with your smartphone, mostly via Bluetooth. Examples include the famous Nike+® or any pedometer that tells your phone how far you’ve walked. There are also luggage tags that report whether your suitcase made it to the baggage claim area at the airport. Pacemakers that can be read via radio also fall into this category. Any ultraportable device that runs on batteries and acts as an extra input to your phone or tablet is an OTG device.
Information extracted from OTG devices can be shared via the Internet. Your health habits can be sent directly to your doctor. You may want to share your running records with friends living far away.
OTG actuators are still in their infancy. It isn’t that technology isn’t ready, but that we haven’t really found a use for it. Some examples from the worlds of product and fashion design could be classified as OTG actuators. For example, a mini Segway for Android phones can transform your phone into a small, two-wheeled robot. T-shirts with flat LED displays pulse to the music sent by your tablet. Many of the new wearables, like some of the interactive rings announced during 2014, include nine-axis accelerometer sensors and tiny vibrators to give the users physical feedback.
Bluetooth and near field communication are the most relevant technologies in the OTG category of IoT devices. They create piconets of devices that move with you. In essence, each of us is like a small walking version of the Internet. As explained in the section “Cisco’s Vision,” our phones and tablets are the gateway to the Internet, making that small bubble of wireless sensor information floating around us available to others.
WIRELESS SENSOR NETWORKS
The OTG category describes the emergent field of technologies that aren’t necessarily wearable but that are at least easily portable. A much more clearly defined category within IoT has been around for some time—the one dedicated to wireless sensor networks(WSNs). This field, which has existed for years, is devoted to creating smart networks that can be deployed quickly to monitor buildings, measure environmental data in farm fields, track farm animal activity, or simply collect data about your home.
The main characteristic of WSNs is that they use wireless technology to cover a certain area. One of their most relevant aspects is that they are meshed. In other words, it is possible to extend the network by simply adding new nodes to it. Information is automatically routed from one node to the next until it reaches the gateway that in turn connects to the Internet. Figure 2.3 illustrates this functionality.
FIGURE 2.3 Mesh network architecture
A Scenario of Use of WSN
A typical WSN scenario is a network that monitors patients in a hospital. Most hospitals were built some time ago. Therefore, it is not easy to make these buildings “smart.” A simple way to do so would be to install a WSN to monitor something like the room temperature in different areas, informing the building’s maintenance staff if the heating or air-conditioning systems aren’t working. Another example would be to monitor patients to keep them from leaving their rooms when they shouldn’t. All this information can be sent to a central system, where the data can be visualized. Deploying a network like this one the traditional way would be complicated. On the other hand, using WSN to cover the whole hospital would be as simple as adding sensors to the corridors and rooms. By doing so, you could build a mesh network that you can grow as much as needed.
As you can imagine, this way of transferring data does not support high speeds, because the data packages make multiple jumps between devices before reaching their destination. But it is good enough for scenarios like the ones described here.
Bluetooth Versus ZigBee
Both ZigBee and the latest version of Bluetooth can deploy mesh networks. Meshed networks have been implemented over WiFi, but not many vendors support it. ZigBee and Bluetooth were specifically designed with this “meshed network” scenario in mind.
ZigBee and Bluetooth operate in the same part of the open radio frequency spectrum (around 2.4GHz, a band where anyone can transmit without having to request special permissions from the authorities) and handle multiple channels in a similar way. Unlike WiFi, they take tiny portions of the spectrum and transmit for short periods of time. Then they jump to a different channel to continue transmitting there. This technique is called frequency hopping and allows technologies to be combined.
In this way, even if you have a WiFi network on 2.4GHz, you can also have a series of Bluetooth or ZigBee devices on the same portion of the spectrum. Bluetooth takes larger portions of the signal space but at lower energy averages, whereas ZigBee devices take smaller fractions of the spectrum but use more energy. The average interference of Bluetooth or ZigBee on WiFi can be cleaned easily via software. At the same time, the noise produced by WiFi on the others is too far below the threshold to be noticed.
Both ZigBee and Bluetooth are low-power techniques. Sensors running on either of these technologies can run on coin batteries for years if their refresh rate is low (a couple of times per minute).
Bluetooth has been around longer than ZigBee and is available in most mobile devices and laptops. This makes it likely to win in the long run. However, Bluetooth’s mesh capabilities have only been available for about a year. This means that some companies have already invested in deploying ZigBee networks. Therefore, it is hard to know at this point which one will be used more in the future within WSNs.
One of the best possible uses of WSNs are smart cities, as described in the next section.
Most people live in cities, allowing them to share resources efficiently through infrastructure such as water utilities and highways. Infrastructure also helps residents get access to human resources such as doctors, education, and meeting other people for recreation.
What makes a city “smart” is its ability to connect the infrastructure to a network so that services can be created to better inform citizens about the availability of resources. An example is the public transportation system. If the buses report their locations, intelligent bus stops will know when the next bus is expected. Another example is detecting amounts of nighttime traffic to decide how many streetlights are needed to keep the streets safe while keeping energy consumption low. Rental cars could act as a moving sensor network to report traffic jams or even pollution levels.
As you can see, the possibilities are endless. The question with smart cities is whether data gathered by public systems should be made public. If it isn’t, this is usually because sharing the data requires infrastructure. If the data is made public, individuals and companies could study it and use it to propose changes or new services.
This chapter introduced the Internet of Things and the relationship of this field to wearable technology. You read about the vision of a connected future as interpreted by different companies. You learned terms such as the Internet of Everything, big data, and smart cities.
All of these topics are related in some way. For example, it is hard to imagine a scenario where you would have smart devices but not be part of a smart city infrastructure. The main vision to keep in mind is that there will be a network of automatically connected devices—this is part of IoT evolving from the Machine to Machine (M2M) business. At the same time there will be a network of personal devices that are connected, and the wearable devices fall within this category. It is like having a cloud of devices in parallel to a cloud of people.
The next chapter introduces the software tools (SDK) needed to write code for wearable devices running Android. Get closer to an Internet connection, because you will need to download some software!
1. “More than 50 billion connected devices.” Whitepaper by Ericsson. February 2011. http://david.cuartielles.com/files/2014/2011_Ericsson-More-than-50-billion-connected-devices.pdf
2. Tim Bajarin. “The next big thing for tech: the Internet of Everything.” Time. January 13, 2014. http://time.com/539/the-next-big-thing-for-tech-the-internet-of-everything/