2.1.1 Wearable Computing Pioneers

There are several individuals who may be credited as pioneers of modern Wearable Computing. The following is a partial listing of such computer scientists, along with brief highlights of their contributions.

Edward O. Thorpe and Claude Shannon, both MIT Ph.D. mathematicians, have been widely credited for designing the first Wearable Computer in the early 1960s. Thorpe pioneered the application of probability theory in various arenas including hedge fund techniques in financial markets as well as the mathematics of gambling. Thorne and Shannon developed the first Wearable Computer and used it as a gambling aid when playing the game of blackjack, purportedly as a purely academic exercise (at a casino in Las Vegas, Nevada, where gambling was and continues to be legal). Subsequently, laws in the state of Nevada were revised to outlaw the use of wearables and other computing devices to predict the outcomes in betting and gambling.

Steve Mann is a Ph.D. researcher and inventor whose work since the 1980s has contributed immensely toward modern Wearable Computing technologies. Mann designed a backpack-mounted computer to control photographic equipment in the early 1980s while still in high school. Mann was one of the founders of the Wearable Computing Lab at MIT, and he continues to be an active contributor in the field of Wearable Computing.

Thad Stamer, a Ph.D. researcher and professor, has been actively contributing to the field of Wearable Computing and the associated topics of contextual awareness, pattern recognition, human–computer interaction (HCI), and artificial intelligence since the 1990s. Stamer was one of the founders of the MIT’s Wearable Computing Project and has a key role with the Google Glass project.

Edgar Matias and Mike Rucci from the University of Toronto have been credited with building a wrist computer in the 1990s. Mik Lamming and Mike Flynn at Xerox PARC demonstrated in the 1990s a wearable device, the Forget-me-not, that could record interactions with people and store them for later reference. Alex “Sandy” Pentland, a Ph.D. computer scientist, is an active faculty member at MIT Media Labs and one of the pioneers of wearable and data sciences. His work has focused on wearables, human, and social dynamics using data analytics.

As with any arena of complex technology and research, the knowledge base and ecosystem have been built based on the contributions from a multitude of dedicated researchers, professionals, enthusiasts, and hobbyists.

2.1.2 Academic Research at Various Universities

Wearable Computing has been a theoretical subject of academic research for several decades. A wide variety of pioneering work has been done at the MIT Media Lab, which focuses on the convergence of technology, multimedia, science, art, and design. HCI and wearable technologies are some of its core arenas of research. Columbia University too has pioneered work on augmented reality since the 1990s. Numerous universities continue to conduct research in the field of Wearable Computing and related fields of virtual reality and augmented reality. Much of the innovations seen in consumer market wearables today have originated from the academic research of years and decades ago.

At a fundamental level, Wearable Computing and research has a correlation with both virtual reality and augmented reality. “Virtual reality” provides the user with a simulated, unreal, or virtual sensory input.

Augmented reality on the other hand enhances the real world with additional computer-generated information such as audio, video, and other data, such that the user’s current perception of reality is enhanced. Augmented reality provides additional input that overlays and co-exists with the user’s real-time experience of their real-world environment. Augmented reality often uses computer vision and object recognition. Using virtual reality, NASA astronauts can “experience” being at a beach during the long periods of time in space, and get some relief from the psychological and physical demands of being in space, away from their home planet. The same astronauts benefit from augmented reality-based systems that are typically used while carrying out critical physical missions and maneuvers in space.

2.2.1 Machine to Machine (M2M)

The term Machine to Machine is associated with and commonly used along with the term IoT. M2M and IoT are associated and have significant overlap of concepts and applications. M2M refers to the direct two-way connectivity between a computing device and a “fellow” computing device. In the world of M2M, devices typically have a network address directly on the Internet, and devices are peers on the network. M2M was originally used in specialized industrial segments including automation, instrumentation, and process control. M2M devices are generally characterized by small devices having their own IP address directly on the Internet.

2.3.1 “ARM-ed” revolution

The ARM family of processors power the vast majority of mobile devices such as mobile phones, tablets, and small embedded devices including the majority of the IoT devices. ARM processors also power set-top boxes, televisions, and netbook computers. The ARM family processors have typically required significantly less power compared to the x86 family of processors. ARM processors are light, portable, and small in size. The success of mobile devices has hinged on the availability of low-cost, lightweight, compact, and power-efficient ARM processors. ARM has played a key role in the last many years in the success of affordable mobile devices that can run on battery power for hours on end.

Over 50 billion ARM processors have been manufactured as of 2014, and this appears to be only the beginning. The availability of wearable devices hinges for the most part on the ARM-based processors and system on chip (SoCs) covered in the next section. Incidentally, ARM processors have recently made an entry into the market segment of servers that reside in data centers on the cloud.

ARM Holdings plc is the British company that bears the ARM name and develops the architecture and design of processors. ARM Holdings licenses the technology to other companies for purposes of production and manufacturing. ARM licensees include companies such as Qualcomm, Broadcom, Marvel, Freescale, Amtel, Nvidia, Texas Instruments, NXP, ST Microelectronics, Applied Micro, AMD, Samsung, and Apple. These are the companies that make ARM processors or chips; some of these companies also manufacture and market mobile devices as well.

2.3.2 System on Chip (SoC)

Although the CPU is the heart of any computing device, the CPU works not in isolation but in conjunction with several other key components such as memory, graphics processing unit (GPU), audio chips, wireless radios (Wi-Fi, 4G), USB controllers, and so on. A system on chip (SoC) integrates the CPU with the other key components such as memory, GPU, USB controller, wireless radio, etc. into a single integrated chip.

While a computer cannot be built based on a single CPU chip alone, it can be built based on a single SoC chip. In recent years, the trend has been in the direction of SoC-based consumer devices, coincident with the proliferation of mobile devices and the success of the ARM-based processors.

The SoC has the advantage of its highly compact size, lower cost, and less wiring. SoCs have now begun to appear inside larger systems such as netbooks and even server systems. The limitation of the SoC can be that it is not conducive toward the upgrade or replacement of individual constituent components, as they have all been integrated upfront.

The mass production and availability of low-cost wearable devices hinges on the availability of SoCs in an innovative and competitive market. Today, there are well over 50 SoC manufacturers who manufacture SoCs based on ARM-, MIPS-, or Intel-based processors.

2.3.3 Human Dependence on Computing

Consumer interaction and dependence on computing started with the personal computer (PC), but it was the success of the smartphone that deepened this dependency on and appreciation of computing devices on a more engaging, intimate and somewhat “constant” basis. Now that the smartphone has become an integral part of most users’ lives and the value from computing in their daily lives adequately appreciated, there is greater interest and potential value from the enhanced functions and specialized use cases that wearables can provide.

2.3.4 Smartphone extensions

In general, smartphones have tended to provide a software solution and a software-based replacement for many hardware gadgets. At first, and since well over a decade ago, the mass adoption of feature phones and later smartphones tended to cause a progressive decline in the use of hardware devices such as digital watches, alarm clocks, cameras, scanners, simple level instruments, and so much more. In a way and to some extent, the introduction of wearables into the consumer computing ecosystem today seems to run contrary to this trend. Today, our appreciation of and dependence on the smartphone paves the way for devices such as a wearable smart watch. Users experience some of the limitations of the much utilized smartphone—in terms of their intrusiveness toward the user’s real-world activities—and this helps justify wearable devices, some of which aim to elegantly extend the smartphone and act somewhat like an accessory and extension of the smartphone. Still other wearables aim to provide specialized functionality such as fitness sensors and health monitoring.

2.3.5 Sensors

Many smartphones have sensors for motion, position, environment (temperature, pressure, humidity, and light), and so on. Fitness devices have sensors for fitness-related parameters such as heart rate, step counters, etc. Sensors play a key role in the world of wearables and IoT. The inference of the user’s context and access to fitness readings—which tend to make wearable applications more useful to consumers—are possible due to the availability of low-cost, power-efficient sensors.

2.4.1 Human–Computer Interface: over the years

The human–computer interface refers to the interaction between human and computer. The computer receives input data from the human via various mechanisms such as keyboard, soft keyboard, mouse, touch, gestures, speech, audio, video, vision, and so on. The computer responds with output data such as screen displays, printouts, audio, video, and more.

Until the 1970s, most of the input and output—the interaction between human and computer—was mostly based on “punch cards.” A punch card is a thick paper card that encodes programs and data. Computer scientists, programmers, and operators used a keypunch, a typewriter-like device to write data that was fed to the mainframe computer via a punch card reader. This was the era of the “mainframe” computer that was used in the corporate, industrial, military, and academic worlds. This punch card-based interaction kept the use of computers limited to computer scientists, programmers, and operators and as far as possible from the consumer. At that time, consumers typically had no interaction with or direct use of such computers or any computers at all. The advent of the PC era, which began in the late 1970s and 1980s, changed that model, slowly but profoundly. Incidentally as of 2012, some voting machines in the United States reportedly used punch card based mainframe computers.

In the PC era of the 1980s through to the recent decade, the computer and the consumer interacted via the keyboard, monitors, and mouse and to some degree via speakers and microphones. In this PC era, the users’ computer was a located in their home or office, perched on their desk. Soon, the laptop arrived and was easier to carry around on business and leisure.

In the post-PC world of today—the era of mobile and cloud—consumers interact with their mobile computing devices via intuitive mechanisms such as soft keyboards, touch, gestures, voice, audio, video, and so on. Computing resources on the cloud are also typically an important part of this interaction; however, these cloud computing resources are somewhat abstracted out in terms of their location, specification, and power needs. The consumer cares about the quality of experience and service but typically neither knows nor particularly cares where the cloud-based computers that serve their needs physically reside nor what their specifications of CPU, memory, etc. look like. In retrospect, the PC was not all that personal since it was not that close at hand, compared to today’s mobile devices which are close at hand all day and thus are more personal.

2.4.2 Human Computer Interaction (HCI): Demand and Suggest

Two important paradigms in modern human computer interaction (HCI) design are the “Demand” and “Suggest,” which are covered in this section.

2.4.3 Evolution of the Human–Computer Relationship

The human–computer relationship has evolved over time in the direction of “progressively deepening intimacy.” For consumers, the computer itself had become smaller in size and weight, and its shape has become more elegant. From being located on a desk in front of the human—at arm’s length—the computing devices moved closer by being perched on human laps and closer still by being housed in human pockets and purses or held in human hands for extended periods of time. The next step in the progression of this trend brings us to computing devices that are in contact with the human body for extended periods of time.

2.5.1 Spatial Scope of Computing: Devices near and Devices far

In a world of a multitude of devices, networks, and services that a user interacts with, we find that there are some computers and networks that reside closer to the user and some progressively farther away from the user. Proximate networks include interconnected devices close to the user, while wider networks include a company or college campus, a citywide metro network, the Internet, and so on.

By organizing and categorizing the devices and networks in this manner and seeing computing from this perspective, it is easier to see how these various devices and networks can be made to work together and provide synergistic value.

In Figure 2-3, the smaller circles or ellipses represent devices and networks that are “proximate”—physically situated nearer to the user—such as the user’s mobile phone, tablet, and smart watch. The ever-expanding larger ellipses represent computing resources such as cloud-based computing resources that reside farther away from the user, which the user nonetheless interacts with—via their proximate devices. Not all devices that are spatially closest to the user will necessarily connect to the Internet—which is why we find that the smallest ellipse is not wholly contained within the larger ones.

In such a nomenclature and categorization, the devices that the user may wear on their person are denoted as the body area network (BAN), while devices that reside within the user’s home are denoted as the home area network (HAN).

2.5.2 Body Area Network (BAN)

A Body Area Network (BAN) is a wireless network of wearable computing devices that are centered around the human body. Such devices may be surface mounted or even embedded inside the body and are typically connected wirelessly over this BAN to a mobile smartphone or tablet device. The mobile devices can collect data from the body-worn devices and store such data; they may also, in turn, interconnect the BAN to the Internet. Thus, it is technically feasible for such body sensor data to be made available for remote monitoring by medical systems and so on.

Also, consumer fitness sensors and applications can help the user get insight into the various commonly understood metrics such as temperature, resting heart rate, average resting heart rate, and so on. Consumers can potentially share their fitness data with their doctors and health care providers. With the mass consumer usage of bodily fitness sensors in conjunction with cloud-based storage, there is potential for the power of large-scale computation to provide significant prediction, inferences, and forecasting. There is promise of a path to the much needed, affordable, and proactive health care—via use of Internet-based technology. Medical devices and applications are regulated by particular governmental agencies and need to comply with applicable laws, and these generally vary by country. Medical devices and applications are distinct from fitness sensor devices and applications, especially from a legal and regulatory perspective.

Some medical devices and applications merely monitor particular bodily parameters and are technologically quite similar to fitness devices and applications, but legally, they are distinct—fitness devices and applications are not regulated by the governmental agencies, that medical devices and applications are.

Other medical devices and applications regulate, actuate, or control some bodily parameters and functions and these are significantly distinct from fitness devices/applications, which do not control or actuate any bodily function. In this sub-arena, medical devices and fitness devices are technologically dissimilar.

The rate at which technology is evolving makes it somewhat difficult for laws and legislation to catch up or keep up. Legislation can often become the bottleneck in the path of innovation and progress in the health care arena. There is a lot of promise and potential for a more fundamental transformation in the delivery, management, and cost-effectiveness of health care that leverages the technological advances of lower-cost sensors, diagnostic software Apps that can run on generic lower-cost handheld (phone and tablet) devices, and beyond.

2.5.3 Personal Area Network (PAN)

The personal area network (PAN) is a network of interconnected devices that are centered around the user’s living space; it includes devices that users carry with them including mobile devices such as smartphones, tablets, Chromebooks, netbooks, etc.; devices on the desk and devices in the home including home automation; and smart networked devices such as washers, dryers, refrigerators, and so on. The PAN can be considered to include the BAN, but it can also be relevant to think of the PAN as distinct from the BAN. In any case, the PAN and the BAN are spatially proximate and have opportunity for meaningful interconnection.

Bluetooth and IrDA are two of the common technologies that help interconnect the BAN and the PAN. IrDA has been around since the 1990s and is an industry standard and a set of protocols that address communication and data transfer over the “last one meter” by using infrared light. Bluetooth is a set of protocols that addresses wireless communication over distance of a few feet. Bluetooth Low Energy (LE), also known as Bluetooth Smart, aims to reduce the power consumption. A recent update to the Bluetooth specifications (version 4.2) addresses the direct connectivity of Bluetooth Smart devices to the Internet.

2.5.4 Home Area Network (HAN)

The Home Area Network (HAN) is a local area network (LAN) that interconnects devices that are within the home or within close proximity to the home. Such a network may include mobile devices and wired computers, televisions and entertainment devices, printers, scanners, thermostats, lamps, sprinklers, and so on. Most Internet service providers provide one IP address for the external network facing router. All the devices within the network typically have a local private IP address. The router that connects to the Internet service providers’ network represents the boundary at which the Internet service provider’s network ends and the home network begins. While the user is at home, the HAN may typically include the PAN and the BAN.

Network address translation (NAT) is a technique that hides the local IP address of a device behind a single device such as a router—which may have a public/external IP address. NAT is closely associated with IP masquerading—wherein one device such as a router masquerades as several other devices behind it—that have a local private IP address but appear as a single public/external IP address to the external public network. Such devices are able to initiate connections to the Internet, but are not directly addressable on the Internet. Most home networks use a NAT-based arrangement.

2.5.5 Automobile Network

There are devices and networks associated with our automobiles such as entertainment, locks, keys, and diagnostics. These form part of the automobile network and may overlap with the home network, while the automobile is parked within range of the home wireless network. The PAN and the BAN can become part of this automobile network when the user is within the vehicle.

2.5.6 Near-Me Area Network (NAN)

A near-me area network (NAN) is a logical communication network that focuses on communication among wireless devices in close proximity. Unlike LANs, in which the devices are in the same network segment and share the same broadcast domain, the devices in a NAN can belong to different proprietary network infrastructures (e.g., different mobile carriers). So, even though two devices are geographically close, the communication path between them might, in fact, traverse a long distance, going from a LAN, through the Internet, and to another LAN. NAN applications focus on two-way communications among people within a certain proximity to each other.

2.5.7 Campus Area Network

A campus area network is a network made of LANs that are interconnected within a geographical area and owned by a single entity such as a corporation or a university. Such a network typically has various relevant network services.

2.5.8 Metro Area Network

A metro area network is a network that spans a metropolitan area such as an entire city and is managed by a single, coordinating organization. Most networks are now aligning with the Ethernet-based metro Ethernet, which is used to connect subscribers to the larger networks including the Internet. There is tremendous potential to leverage metro area networks in many dimensions such as emergency management, community, and services. At a grand scale, the devices on the network and their activity and location provide a reflection of the current state, en masse of the human population, pets, resources, energy conservation, and so on. Such opportunities for efficiency and optimization of human activity, resources, safety, and so on can help realize the vision of the “smart city.”

2.5.9 Wide Area Network

A wide area network networks include telecommunication networks that span national and international boundaries. The Internet, too, can be considered to be a wide area network.

2.5.10 Internet

The Internet is the global, interconnected network of networks that is based on the standard TCP/IP communication protocol. It consists of millions of public, government, academic, and business networks linked by a wide range of electronic, wireless, and optic fiber technologies.

There are two main name spaces in the Internet—the Internet Protocol (IP) address space and the Domain Name System (DNS) maintained by the Internet Corporation for Assigned Names and Numbers (ICANN). The technical standardization of the core IPV4 and IPV6 protocols are managed by the Internet Engineering Task Force (IETF), which is a nonprofit organization.

The modern Internet came into being sometime around the mid-1980s and initially was used predominantly in academic institutions. Commercialization occurred in the 1990s. However, the origins of the modern Internet date back to the 1960s and the research conducted by the US government as well as UK and France.

2.5.11 Interplanetary Network

Even though an interplanetary, galactic network seems a little like science fiction, an initial form of such a network already exists—the International Space Station is already connected to planet earth’s Internet.

A wider interplanetary network requires a specialized set of protocols to address more of a store and forward approach that handles the delays and interruptions that could range from minutes to hours in view of the distances. One of such initiatives is the delay-tolerant networking (DTN), which is an architecture that endeavors to address technical issues in heterogeneous networks that lack continuous network connectivity including networks in space. At the core of DTN is the Bundle Protocol family—very similar to the Internet Protocol (IP)—which has been designed to account for the delays and disruptions expected in space communications.

2.7.1 Importance of the User Centricity and the User Context

User centricity in conjunction with a user context that transcends the existence or uptime of any particular device is particularly important and relevant. The transdevice user context is one of the key foundations of a more interactive, intelligent agent-based, ubiquitous model of computing.

As was the case decades ago, a given user interacted with about one personal device, that is, on a one-to-one basis such that device centricity happened to be mostly coincident with user centricity. But today, each user interacts with a multitude of devices, that is, on a one-to-many basis, so it becomes important to align with the user-centric model of data and context. A device-centric model tends to become obsolete in a world of many devices per user.

2.7.2 Distributed Intelligent Personal Assistant

An intelligent personal agent performs tasks, autonomously on an ongoing basis, in order to make human lives more convenient and safer. In a world of a multitude of diverse devices and in order to serve a user’s needs at all times, the intelligent agent ideally runs not on any particular device, but as a distributed intelligent agent that runs across collaborating devices, which are user context aware at all times. The cloud is certainly the ideal candidate for the “headquarters” for such a distributed intelligent personal agent. The devices that reside close to the user also have great importance due to their ability to provide sensor signals that are the basis for the inferences about the user’s current activity, context, and environment.

2.8.1 Google / Cloud-Based Intelligent Personal Agent

Google, as the search engine, initially started out providing us access to information and knowledge. After having started out providing access to the world’s information, Google has over the years become a prominent repository of the world’s information. Over time, by virtue of mass usage and analysis of patterns and distribution in search terms, Google Insights acquired deep predictive capabilities. For many years, Google was able to predict an outbreak of the flu earlier and more accurately than the Centers for Disease Control and Prevention (CDC).

Google, as the cloud repository of the users’ email, documents, photos, calendar, and location history stored on Google’s secure cloud infrastructure, has the advantage of the best data and the best algorithms to create intelligent computing value for the consumers.

2.9.1 Enhanced Computer Vision / Subtle Change Amplification

While computer vision started out with the “modest” goal of duplicating human vision, researchers at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, which include Professor William T. Freeman and Michael (Miki) Rubinstein (Ph.D.), have made progress in the arena of analysis and amplification of subtle motion and color changes.

Freeman and Rubinstein share with us the big world of small motions and changes in color, which when detected and amplified can give us “superhuman” vision. Rubinstein—as part of his Ph.D. research, with Freeman as his advisor—developed methods to extract and amplify subtle motion and color changes from videos. The beating heart results in the rhythmic flow of blood in the human body, which causes corresponding subtle, rhythmic changes in the color of the human skin. These color changes are generally invisible to human eye. Using the video signal from a regular camera and by detecting these subtle color changes via signal processing algorithms, it is possible to infer the heart rate. By creating a change amplified version of the video, it becomes easy to perceive the heart rate visually. This is an instance of vision enhancement via color change amplification. The human breath results in subtle elevation and movement of the chest and stomach area. Neonatal infants typically need to be monitored for vital signs while minimizing disturbing or touching them. The subtle motion of the belly after amplification yields a modified video which makes their breathing and the rate, thereof, visually obvious—without needing to touch or disturb them. Rubinstein also demonstrates other applications of this technology such as recreating a conversation by amplifying the movements of a crumpled bag of chips while a conversation is occurring in the vicinity. By zooming in on small motions of the crumpled bag and amplifying them in the order of a 100 times and after converting the motions into sound, the conversation can be constituted. A TED talk by Michael Rubinstein “A Big World of Small Motions” as well as other videos on this technology is available at:

• https://www.youtube.com/watch?v=fenV3W7hQtw
• https://www.youtube.com/watch?v=3rWycBEHn3s

Such amplification of subtle motion and color changes can be effectively applied to other arenas such as industrial, transportation, agricultural, and more. In one approach, a grid of moisture sensors embedded into the soil in a section of farmland provide useful input that can be used to time and control the periodicity of watering of the crop. In another approach, the video feed from a camera that “observes the crop” can be analyzed, and the subtle motions of the crop such as the swaying motion in the wind or any slight color changes or wilting can be amplified to detect commencement of crop dehydration and making it more visible and detectable for timing the watering accordingly.

Thus, the ordinary camera’s video feed can be used to infer and reveal various measurements indirectly via sophisticated algorithms and computation.

2.10.1 Human History of Tool Use and Computation

What we see today is, probably, merely an acceleration of a trend that was established and has been in place for tens or hundreds of thousands of years. Although technology has advanced in recent decades, there is no fundamental shift from our fundamental dependence on tools and computation to improve our daily lives and even our chances of survival.

Humans and their ancestors have been a tool maker and computational species. Long ago, tracking the movements of the sun, moon, planets, stars, and constellations helped our ancestors understand and predict celestial and astronomical cycles and the seasons; build clocks and calendars; and plan hunting, migration, and planting.

Observations of various patterns and associated predictions were the factor that enhanced the chances to human survival. Long ago, the rock chip gave human ancestors the competitive edge for survival. Tool use actually caused an increase in brain size and that bigger brain helped in building the next generation of more sophisticated tools.

The use of tools for hunting helped provide adequate meat more easily, which helped nourish the brain and improve its size and intelligence and provide more time to think and ponder and gaze at the skies and create rock art.

Not too much has changed, it would seem, because today it is the silicon “chip” that gives us the competitive edge, individually and as a species. It extends our memory, helps us consume, manage, create, and share information. It helps predict many aspects of human interest such as weather, finances, health, and more, to help us live more comfortably, safely, and efficiently.

Today, with the highest human population in recorded history inhabiting planet earth, perhaps the computing ecosystem of wearables, IoT, and artificial intelligence can solve many of the problems of infrastructure and resource management, energy efficiency, health monitoring, manufacturing efficiency, city and township management, and so much more.

2.10.2 Communication Networks in Nature

There are numerous examples of networks in nature that enable communication. It turns out that plants interconnect their roots with other plants—via the “mycelium,” the branching threadlike, vegetative part of mushrooms (fungi) that grows in the soil—thereby forming a communication network via which information such as warning signals of pathogen and aphid attacks are transmitted between plants. Mycelium can be really tiny, and they can also be quite massive.

Mycelium is useful in nature and to the ecosystem in various roles—including the role of a communication network. Paul Stamets—the renowned mycologist and author of Mycelium Running: How Mushrooms Can Help Save the World—shares some of his insight into the world of mycelium, which form large 2000 plus acre networks in the forests of the Pacific northwest of the great North American continent. The mycelial network helps the overall health of the forest by distributing nutrition and information for the overall good of the forest. The mycelial network thrives in a healthy forest, and it strives to keep the forest healthy. Stamets points out in his writing and talks on TED (http://www.ted.com) that fungi are sentient beings that can sense the environment, human presence, and much more and that the mycelial network makes it possible for particular trees that do not receive adequate sunlight to receive nutrition via the mycelial network’s ability to access and transport needed mineral nutrition.

Similar to the networks in nature, the important foundations of modern human civilization include the advanced systems for transportation, power transmission, water distribution, and information superhighway. Computation and communications have an important place in human civilization and are not necessarily all that artificial in concept. IoT and wearables have an important role of the sensor–actuator network, which addresses the sensing and detection, and feedback to the periphery of this network. The periphery of this computational network is what engages people and their relevant, significant “things” of interest directly.

2.10.3 Consumption of Power: by computational systems, biological and artificial

Our computational and artificial “intelligence” is built by, and is an extension of, our human biological brain. It turns out that the Internet somewhat resembles a massive organism and also our nervous system by demonstrating self-healing behavior, adaptation to changes in the flow of packets based on dynamic changes in available routes, redundant connections, and so on.

The smartphones and other user-interacting devices such as IoT and wearables lie on the periphery of this organism-like nervous system of the computational Internet.

The human brain comprises less than 3% of the total body weight, yet it accounts for over 18% of the energy consumption. Much like the human brain has this density of storage and processing, civilization’s data centers have a density of storage and computational power as well as the need for massive amounts of energy to power this processing and data storage.

The subject of the power consumption by the cloud/data centers and the overall information technology industry has attracted much attention in recent years. It is estimated that if one were to count the energy consumption that goes into manufacturing the processors and devices, running the network infrastructure, and the data centers put together, then as much as 10% of the world’s generated electricity is consumed in powering information technology.

It turns out that, much like the human brain has tremendous need for power, oxygen, and nutrition—compared to the rest of the body—the huge computational data centers, networks, and devices that run human civilization have huge needs of power and energy. The energy needs of the computational resources to run our human civilization have perhaps begun to mirror the relative power needs of the human brain with respect to the human body.

2.11.1 Use Awareness and complete end-to-end Transparency

It is important that users are aware of what data their IoT devices are generating, and to which cloud-based endpoints the data is being sent to, as applicable.

There have been many news reports in the media about household smart gadgets that record data and send it to the cloud without the user’s knowledge and function like spyware.

Complete end-to-end transparency makes it very clear to the user what data is being collected and who the data is being sent to, how that data is being used, how securely the data is stored on the cloud, and if it is shared with external parties.

2.11.2 User Control and Choice

It is important that the users have control over the data collection with the ability to turn off the data collection per their needs and preferences—as well as the choice to opt in or opt out of data collection or sharing with external parties.

2.11.3 User Access to Collected Data and Erasure capability

It is important that the user has access to all of their data that is collected and stored on the cloud. It is also important that the user has the ability to erase the data stored on the cloud permanently and also export it out in standard open formats of their choice.

2.11.4 Device side, transit, and cloud side protection: Data Anonymization

It is important that the user is aware of what data is collected, who collects and stores it, the degree of protection that their data enjoys in terms of security on the device side, the encryption standards used, and the algorithmic protection the cloud side infrastructure provides in order to protect their data from unauthorized access and cyberattack. Strong infrastructure boundary protection prevents or reduces the chances of a data breach or unauthorized access. Strong algorithmic protection detects failed attempts promptly and intelligently in real time and blocks further attempts by malicious entities.

It’s also important that the stored data be anonymized. Data anonymization is a technique of encryption and removal of personally identifiable information from sets of data. Anonymization maintains certain data centered around a random ID, rather than a identifiable individual. Sensitive data such as passwords, credit card numbers, and social security numbers need to be stored with strong encryption rather than as “plain text.” Hashing algorithms such as MD5, which is often used for hashing passwords, is relatively easy to break. The National Institute of Standards and Technology (NIST) recommends PBKDF2 for one-way hashing.

2.11.5 Practical Considerations: User Centricity

It is impractical for users to have login account credentials on a per device and cloud/website basis—especially in a world of such a multitude of devices and cloud accounts. It is important that users use strong passwords that are not re-used across different realms. At the same time, it is important that users are able to securely access the history data collected on the Internet cloud endpoints and websites, control data access and sharing, and delete the data if they so desire. One of the solutions to address this problem is OpenID.

2.12.1 PhoneBloks: Waste Reduction

PhoneBloks is a modular smartphone design concept created by Dutch Designer Dave Hakkens. “Bloks” are modular components that can be attached to the main board of the phone. Such “Bloks” can be upgraded and replaced, while retaining the rest of the device. Since many users end up replacing their entire phone every few years, there is a huge volume of electronic waste that is generated. By selectively upgrading a functional “Blok” such as camera, battery, storage, and so on, users can upgrade particular modules without giving up the entire device, thereby reducing electronic waste. PhoneBloks is an independent organization with the general mission of electronic waste reduction. More information on PhoneBloks can be found at https://phonebloks.com.

2.12.2 Google Cardboard: inexpensive Virtual Reality

Google Cardboard is an inexpensive cardboard headset designed by Google that works along with stereoscopic vision and display software on the Android smartphone—in order to provide users with 3-dimensional, virtual reality App experiences. Consumers can fold their own based on the designs provided by Google or purchase a ready-made version from various manufacturers listed on their site. The prices start at about US $15. More information can be found at https://www.google.com/get/cardboard. Google also has an associated virtual reality Cardboard SDK that simplifies the development of virtual reality Apps, the coverage of which is outside of the scope of this book.