Chapter 11

The Future of the Internet of Things

Harish Viswanathan

Francis Mullany

The essential vision

Machine communication for monitoring and remote control predates the Internet, with supervisory control and data acquisition systems (SCADA) having been used to monitor and control machines since the 1960s. The deployment of devices for monitoring and control has accelerated in recent years, aided by ubiquitous wireless connectivity and declining communication costs. Nevertheless, until recently machines still communicated only with purpose-built applications and with limited data acquisition or analysis capabilities.

Connecting things to the Internet is a completely different proposition that is occurring on a massive scale. By bringing together a wide variety of devices and applications, there is the potential for a major transformation in how humans interact with the physical world, both in a personal and professional context. The future of the Internet of Things (IoT) can be viewed as bringing the physical world into the digital realm, “animating” physical objects to augment our existence and “saving time” by increasing knowledge and awareness. The essential ingredients of this vision are as follows:

1. The dawn of the era of pervasive digital automation — The world will begin to witness a revolution in human life comparable in scope to the Industrial Revolution and computerization. Sensing and control with global reach and with real-time communication and analysis will enable the physical world to become a seamless part of a sentient digital whole.
2. The network as a digital nervous system — The connectivity network will become the nervous system upon which the automation is built. The network interfaces and architecture will be reimagined to provide the control plane and data plane connectivity and processing at the required cost, energy autonomy, responsiveness and reliability. The network will have the following characteristics:
   • A massive increase in control-plane capacity to handle sporadic transmissions from a large number of new devices
   • A significant change in the traffic characteristics with the proliferation of “short-burst” type communications, in addition to large-scale upstream video streaming
   • Minimal consumption of device energy for sporadic communication so that devices with infrequent communication have battery lives in excess of 10 years
3. The rise of augmented IoT solutions – Future IoT solutions will include key functions such as augmented contextual analytics, device security verification and data privacy, as well as automated device management and control to enable the rapid deployment and easy operation of myriad devices and device capabilities in the new digital era.

In this chapter we explore these elements in detail in order to help provide a prescription for what promises to be a transformative economic reality — one in which our relationship with the physical world will become at once more global and more local, more remote and more interactive.

The past and present

The evolution of automation

Control of our environment, both natural and man-made, has been a human imperative from our earliest history. For much of that time, however, control over distances was severely limited, due primarily to the need for line-of-sight monitoring and to be within arm’s reach for actuation and control. Mechanical automation in the nineteenth century enabled men and women to reach much further control processes, but the remote-control scale was still within a building or vehicle and monitoring was still mostly limited to direct visual observation. A good example of this was the railway network; train track points were visually monitored and changed from a signal box that was always within sight.

The dawn of electrical communications technology vastly increased the scope of monitoring and control. The solutions were, however, bespoke and mostly confined to controlled environments with dedicated personnel. For example, the “engineer order telegraph” was the throttle signaling system between a ship’s bridge and the engine room. True industrial automation had to wait until the post-World-War II era, where the combination of control theory, rudimentary computing and reliable digital communications networks enabled the first long-distance monitoring and actuation. Technologies like SCADA, proportional-integral-derivative (PID) controllers, embedded electronics and long-distance wired communication opened up a range of applications from vehicular traffic control and robotics in manufacturing, to electronically automated telephony exchanges.

However, these solutions were still tailored to a specific purpose, scaled poorly and expensive to install and run. Consequently, commercial implementations were limited to only those applications with the best return on investment (for example, control and automation of large-scale industrial plants or, at the other end of the scale, the use of smart meters for better managing electricity consumption).

The first wave of IoT

With advances in technology driving down device and communication costs, the vision of pervasive digital automation began to be realized, starting with those applications with high value to end users in specific industries. Inevitably, the initial applications were those in which critical resources needed to be managed much more efficiently. These can be broadly summarized as the following:

• Energy costs in large buildings and homes have increased dramatically over the last decade. The average annual cost of direct energy consumption for a UK household in 2012 was £1,250, up from £552 in 2004 (Telegraph 2012). Optimized comfort control and energy consumption to use off-peak power can minimize the excess costs.
• Chronic (long-term) illnesses are becoming a major economic burden, with 75% of US healthcare costs being consumed by the treatment and management of chronic diseases. This equates to roughly $8,000 per unhealthy individual per annum in 2007, with the key expense being the cost of highly skilled medical personnel and hospitalized care (GSK 2015). Automated management of chronic illnesses can enable the patient to reside at home for longer periods, thereby minimizing the use of premium and scarce hospital resources.
• Water conservation is now a fact of life in most developed economies, with the average water and wastewater bill for a UK household in 2010 being £340 (Offwat 2009). This is only being exacerbated by climate change events, such as the 2015 drought in California, which has reached unprecedented severity (Guzman 2015). Effective monitoring and control of all points in the water collection, delivery and consumption chain (and the associated trend analytics) would allow superior management of this increasingly precious resource.

The common need in each of these cases is to manage distributed infrastructure, connecting and controlling scarce resources, valuable processes and assets in order to increase productivity and save time.

The growth of IoT is the subject of much speculation, and predictions abound on the number of IoT devices that will be deployed. While the projected numbers vary, they all point in the same direction: an explosion in the number of devices to multiples of tens of billions of devices by 2020 and beyond. Figure 2 shows the total number of IoT devices across all economic sectors and communications technologies as predicted by Bell Labs Consulting. It also compares with other industry estimates, with both a conservative and an aggressive view proposed. In either case, the exponential growth in IoT is immediately apparent, with more than 25 billion IoT devices expected by 2023. In the lower panel in figure 2, the number of devices connected via cellular technologies is projected. This is expected to grow rapidly to more than 3 billion devices by 2023, driven by the deployment simplicity offered by wide area connectivity — the absence of a need for a local access point as is the case for short-range radio technologies, the relative ease of configuration and management (SIM-based authentication, no passwords or user configuration required) and the intrinsic support for mobility.

The scaling of networks

Various IoT applications and devices have different connectivity requirements and thus a wide variety of networking technologies serve the needs of IoT. From a networking perspective, IoT applications can be categorized along two major dimensions: geographical spread and mobility. Geographical spread refers to whether the devices deployed are concentrated in a small area — within a few hundred feet of each other — or dispersed over a wide area. Mobility refers to whether the devices move around, and if so, whether they need to communicate while on the move. For localized devices, a short-range local area network such as Wi-Fi or Bluetooth is most appropriate as it allows the use of unlicensed spectrum and maximizes battery life while meeting the connectivity requirements. For applications such as connected cars, or freight tracking, the device moves over a wide area for which the mobile cellular network is the most suitable. In addition, for applications such as remote metering where the devices are widespread but there is little need for mobility, a wide area network is required but it does not have to support seamless mobility. Consequently, low-power wide area (LPWA) networks, which are specifically designed for low data rates and extended coverage with deep reach into buildings, have been deployed since 2013 with technologies that support long battery lives for the devices. Increasingly, mobile cellular networks that were designed for broadband traffic are also being optimized to address these non-mobile IoT applications by reducing device cost and extending coverage beyond the traditional cellular baseline. 5G systems are intended to make significant further improvements, as discussed in the next section.

Figure 3 roughly summarizes the application of different network technologies to IoT use cases in the market environment in 2015. Cellular networks are expanding from the purple category (widespread, wide area mobility) to the blue category (widespread, no mobility) and are also applied in some applications in the green and yellow categories because of the relative simplicity of deployment and management, as described above. However, there is renewed interest in the deployment of LPWA (blue bubble) due to the extended battery life and the low deployment costs. (LPWA radio towers use low data rates and can be situated as much as tens of kilometers away from the end device and therefore serve a very wide area with little infrastructure investment.)

A key additional attribute of many (non-video enabled) IoT devices is the substantially higher volume of signaling traffic that they generate, relative to data traffic. This is because such IoT devices typically transfer only a small amount of data in a given transaction, with each communication requiring signaling to set up the radio connection. Figure 4 shows the number of transactions or connections that are needed to consume 1 MB of data for video, messaging, and short-burst IoT transactions; three orders of magnitude more transactions are required compared to video applications, thus the network must be able to efficiently support significantly more control traffic than the number of attached devices.

The control software

Today the IoT ecosystem is characterized by significant market fragmentation. The wide diversity of end devices, coupled with the system complexity needed to deploy and operate end-to-end solutions, has resulted in purpose-built solutions, optimized for each application or service. Each solution typically uses a proprietary communication protocol and incorporates a customized approach to device discovery, communication, security, management, diagnostics, analytics and enterprise back-office integration.

Figure 5 shows the number of different companies across the value chain in North America providing solutions for the same function, illustrating the vertical market specialization even though the functions in these domains are largely common across the segments. The result is not one, but an ensemble of competing ecosystems with non-interoperable technologies and limited economies of scale. This must be addressed in the future if we are to achieve the optimum price/performance metrics and support the rapid adoption of IoT solutions.

Since the beginning of this decade (2010), the industry has begun to address this fragmentation issue, recognizing that many of these functions are common across multiple IoT solutions in different vertical industries. Consequently, horizontal software platforms that perform such functions and expose common application development interfaces (APIs) for applications to be built using standard web technology (such as REST2) have recently emerged in the market. Figure 6 shows the increasing level of venture capital investment in IoT and in particular, such software platforms. In the future, we expect that software platforms will consolidate around a connectivity platform, a device and service management platform and a services creation support platform, as described in the next section.

The future

The future of IoT will be driven by technology advances in wireless networking, software platforms and device technologies. In this section, we capture some key innovations that we believe will be instrumental in shaping the future of IoT.

The future of IoT networking

Wireless communications has advanced significantly in the last few decades turning the Internet into a mobile Internet. We envision a future where multiple wireless technologies further evolve to efficiently and cost effectively connect the billions of things to the Internet. In this section we discuss how cellular, short-range, and low-power wireless technologies are being optimized to create massive-scale connectivity in an IoT world.

The evolution of LTE

Traditionally, wide-area wireless networks, such as LTE, have been focused on enabling wireless broadband connectivity with technology enhancements introduced over multiple releases targeting increased spectral efficiency, user throughput and system capacity. Once it became clear that IoT devices would form the next wave of wireless network growth, the 3GPP standards body began focusing on optimizing LTE standards for narrowband IoT devices, as well.

Consequently, since 2013, LTE has included features specific to IoT that:

• Significantly reduce device costs by defining limited capability device categories. These new devices operate in a narrow bandwidth of 1.4 MHz within the LTE carrier, support only low-peak rates compared to broadband devices, are single antenna without multiple input-multiple output (MIMO) support, and operate in half-duplex (only transmit or receive at any given time) mode.
• Extend coverage by 20 dB to reach devices deployed in the basements of buildings. This is primarily achieved by introducing repetition in physical signaling and data channels to increase the link budget.
• Improve battery life by introducing a new power-saving state in which the devices are in sleep mode for an extended period without monitoring the paging channel.
• Prevent congestion in the network because of IoT devices. This is achieved by creating a new “low-priority” indicator that can be sent by IoT devices or set in the device subscription to indicate to the network that scheduling these devices can be delayed under overload situations, and the network can selectively bar access to such low-priority devices.
• Include APIs for applications to trigger or send notifications to the devices. Short message service (SMS) is currently used to transport these triggers; alternate mechanisms are under consideration for standardization.

We expect deployment of LTE-M (containing additional IoT features) to begin in 2017 and continue for the next decade into the 5G releases.

In parallel to the evolution of radio access, we expect network functions virtualization (NFV) of the core network to play a major role in supporting the rapid expansion of IoT. Virtualization of mobile core network elements — the mobility management entity (MME), serving gateway (SGW) and packet network gateway (PGW) — allows operators to create dedicated networks for IoT cost effectively. These dedicated core networks for IoT have several advantages over a single network for all traffic types:

• Virtualization allows on-demand network scalability using available data center computing resources. This is particularly useful for IoT as the bulk provisioning of devices for a service and the correlated behavior of devices (in time and location) can result in a rapid increase in the number of devices in the network.
• Different IoT applications have different traffic profiles, especially with respect to the proportion of signaling to data traffic. As noted earlier, many IoT applications have a disproportionately large amount of signaling compared to consumer broadband devices. A virtualized core network element such as PGW or gateway GPRS support node (GGSN) can be optimized for IoT by allowing for more bearer contexts, more signaling traffic to be processed and less packet throughput (bearer radio resources) for the same amount of computing and memory resources compared to the corresponding instance for consumer traffic.
• Enterprise service level agreements (SLAs) for IoT may be quite different from those for consumer services. So, network operators will need to expose parts of their evolved packet core (EPC) for automating on-boarding and diagnostics through enterprise portals. Having a dedicated network or a network slice restricts this exposure to allow enterprise control to enterprise devices only. Other enterprise-specific services such as virtual private networks, static IP addressing and more detailed call-data records are also more easily provisioned on a separate core network.
• A dedicated core or network slice provides isolation across different sets of devices, thus preventing failure of network services to all devices when certain network functions fail. In particular, with IoT devices initiating connections in an automated fashion, anomalous device behavior could result in unexpected traffic scenarios that can impair the network; separation of this traffic onto a separate core network helps to isolate the larger network from such occurrences.

Figure 7 illustrates the concept of a virtualized core network for IoT operating in parallel with the physical “consumer” network and sharing the same radio access layer. The set of separate core network functions deployed for IoT could range from only the virtualized packet network gateway (vP-GW) to all functions of the EPC.

The evolution to 5G

The 5G system is expected to be further optimized for IoT devices and improve significantly on battery life and network efficiency compared to LTE, as discussed in detail in chapter 6, The future of wireless access. The basic framework, such as the signaling and radio waveform in LTE, was designed for long-lived data flows, such as video streaming and web services, and is not optimized for small packet transfer between IoT devices and their applications. Thus the extent to which LTE can be optimized for IoT while being backwards compatible is limited. Without the constraint of complete backwards compatibility, 5G will be designed from the beginning not only for smartphones but also for IoT devices and thus will be better optimized for IoT. In particular, the fact that IoT involves significant number of short duration short-burst sessions will be taken into account to ensure small packet transfers do not generate significant amounts of network signaling.

We expect the following technologies to be part of 5G IoT:

• Asynchronous uplink communications using some filtered versions of orthogonal frequency division mutiplexing (OFDM) waveform such as the universal filtered OFDM (UF-OFDM) to enable devices to avoid the closed loop synchronization signaling that consumes control plane processing resources and reduces device battery life
• A “connectionless” mode of transmission in which devices can send user packets without establishing radio bearers, thereby minimizing excess signaling
• Radio resource allocation mechanisms designed to handle the transfer of a small number of packets from a very large number of devices
• Multiple symbol and frame durations to support different latency requirements efficiently — in particular, we expect support for very low-latency that will enable mission-critical IoT in vertical industry segments, such as public safety, smart grids and vehicle safety

The role of low-power wireless access (LPWA)

An alternative to mobile cellular networks for wide-area IoT are LPWA networks that are designed specifically to meet the communication requirements of low-throughput, stationary or nomadic IoT devices.4 These networks are designed to cost little to deploy. They are typically based on proprietary technologies and are deployed in (small) slices of unlicensed spectrum in the low-frequency (<1 GHz) bands. As a result, they deliver only very low data rates in the order of a few 100 b/s. This enables low-power devices (for example, 14 dBm transmit power, which is about 9 dB less than that of typical cellular devices) to communicate over a range of tens of kilometers in suburban environments. In addition, the low-signaling overheads make it possible to achieve a 10-year battery life for devices and support a few transactions per day.

Given the suitability of these networks for a subset of IoT applications, we expect some adoption of LPWA networks by network operators and enterprises/industries, despite the following limitations of such approaches:

• Remote device management solutions, such as firmware upgrades, are not practical because of limited downlink capacity.
• Only a narrow range of IoT devices and applications can be addressed due to the very low data rate, insufficient downlink communication and no mobility support.
• The inability to provide guaranteed service availability using unlicensed spectrum bands. Flexible sharing of licensed bandwidth between IoT and consumer devices is not possible and spectrum acquisition would be uneconomical.
• Some LPWA networks have poor support for localization of devices, so locale-specific analysis or spatial mapping of a measured value are not possible.

So we believe LWPA will remain a niche networking solution for IoT, especially if LTE-M and 5G can meet the promise of low-cost and long battery life for IoT devices.

The role of short-range local area networks

A large number of IoT applications involve devices that are deployed within the confines of a building or home, and involve sensors that are within a short range of a concentrator or a gateway device connected to the Internet. Therefore, such sensor devices only need a short-range (~100 feet) wireless connection to connect to this gateway. A number of short-range wireless technologies such as IEEE 802.11 (Wi-Fi), IEEE 802.15.4 (the MAC and PHY for technologies, such as ZiGigEe) and Bluetooth are being used to address the short-range communication needs for such devices. New technologies being standardized in several IEEE working groups are also expected to improve each of these existing short-range solutions in the future:

• An ultra-low-power physical layer with peak total device power consumption of less than 15 mW, allowing energy-harvesting devices to be used (IEEE 802.15.4 — discussed later in this chapter)
• Peer-to-peer direct device communication providing features such as discovery of peer information, with a scalable number of devices (up to 10) during discovery, and scalable data transmission rates of ~10 Mb/s
• A new version of Wi-Fi, 802.11h, for sensor devices operating in unlicensed bands below 1 GHz

The future of IoT software platforms

IoT solutions have a number of common functions across different applications and verticals. First, the devices have to be provisioned and activated in the network, which involves provisioning in systems such as the home subscriber server (HSS) in the case of a mobile network. Once the device is on the network, device management and diagnostics become critical for smooth operation of the device and associated service. In the data plane, protocol translation proxies that perform protocol conversion and perform routing to appropriate application servers may be needed to collect data and send commands to the device. Analytics and additional processing functions are also required in almost all applications to derive useful information from streams of data. The need for such common functions across different IoT use cases has led to the development of horizontal software functions that we believe will become increasingly important in the future of IoT, even if they do not achieve the “holy grail” of complete unification across all verticals. Some key emerging software platforms are described below.

The connectivity management platform

The primary function of connectivity management platforms is automation of the provisioning life cycle of the IoT devices in the mobile network, including SIM order management, activation, suspension, deactivation in the network and over-the-air provisioning. Specialized rating and billing functions for IoT are also sometimes included in the connectivity management platform.

An emerging new functionality is over-the-air personalization of so-called “white label” SIMs, also known as machine identification modules (MIMs) when used in a machine. Currently, device or machine manufacturers have to employ operator-specific embedded SIMs in the machines at the time of manufacturing or install removable SIMs at the time of shipping. This is cumbersome for multinationals such as car manufacturers that do not want their machines to be tied to a particular operator before it is sold to the end customer. They prefer to have the flexibility to choose the operator after the machine is deployed in the field, and also want the option of changing operators at a later time. In the solution standardized by the GSM Alliance (GSMA), the SIM cards can be provisioned with security credentials of a subscription manager that can then install operator credentials when the operator is selected. This approach is being called subscription management and will likely become a significant element of future IoT connectivity platforms.

The device and service management platform

To scale IoT applications to a large number of devices, it is essential to be able to remotely manage the devices, to troubleshoot and fix issues as they occur. This is particularly important for IoT deployments, since IoT devices are deployed by vertical enterprises, often with infrequent or no human involvement. Since truck rolls to the device location would make IoT services cost prohibitive, there must be a set of remote-management functions, including device configuration for new services or reconfiguration, remote device diagnostics, remote device reboots and firmware upgrades in the device. Such device and service management platforms will therefore be an integral part of future IoT solutions.

The services creation support platform

The third emerging software platform cutting across several IoT verticals is a platform that enables the device data to be accessible to the Internet, permitting web application APIs to expose data, and allowing web services to enable rapid new service creation and usability on multiple end-user device platforms. These platforms will typically include the following:

• A common communications platform, abstracting different device types, and the protocols supported by different devices, and providing normalization of data so it can be used by multiple applications
• Enablement of cross-vertical and multi-tenant rapid deployment of new services, by providing a common services layer with catalogs of resource models and templates based on device, data and service primitives that are made available to applications through APIs
• Common application creation and execution capabilities that include tools for application creation and debugging; a set of simple, base applications and application templates; simulators and sand-boxes for testing; and utilities for data generation with real-time data visualization

A streaming analytics and edge cloud platform

One of the primary goals of IoT is the generation of business intelligence that can make business processes more efficient and save time. Big data analytics technologies are increasingly being used to extract useful information from myriad data sources accumulated as part of business operations. IoT has a dramatic effect on the volume, variety and rate of data processing as billions of devices sense and push information back at an ever-increasing rate. As video sensing takes hold, the volume of data will increase by several orders of magnitude. Increasingly, a combination of historical and real-time streaming analytics will be required for organizations to achieve resource optimization, to improve operational efficiency and to achieve real-time situational and contextual awareness.

The current practice of IoT data being transported to a central location for processing does not scale well and will not meet the real-time latency requirements of some key use cases. Processing of data in an edge cloud (small, highly distributed data centers) will be key to meeting the new requirements. The emerging stream processing frameworks will process the data as it is ingested and typically split analysis into independent modules that run on separate servers. This will allow parallel nodes to be added on the fly, scaling up processing resources as and where required. A future architecture is presented in figure 8; a hierarchical aggregation network is composed of edge clouds responsible for processing events originating from sensors in a specific geographical area. These edge clouds are physically located between the event sources (sensors) and the back-office (centralized) data center.

In this architecture, each edge cloud handles raw data streaming from a limited number of sensors to which they are directly connected. They pre-process events into a reduced data set that is forwarded to the central cloud — as much as possible, without losing information. In cases where real-time analytics can be performed by the edge cloud, avoiding the time delay of a round trip to the core network significantly reduces latencies.

The future of device technology

Pervasive digital automation will also be enabled by major leaps forward in device technology. Deployments of tens of billions of devices will only happen with devices that deliver new information and control functionality at a cost point significantly lower than that for low-end mobile handsets. We see six key technologies that will drive this revolution:

• Integrated circuitry — Moore’s Law continues to play a critical role in increasing sophistication of control equipment and objects. Declining computing costs will enable sensing and automation over a broader range of processes or use cases, with low-power electronics that support extended battery lifetimes.
• Micromechanical devices (MEMS) — The rapid maturing of electronically controlled mechanics at the micrometer scale will allow for the control of a much wider range of small objects and components and the conversion of mechanical actions into an electronic signature. This increases both the scope of IoT (new objects connected) and the sophistication of the control enabled, such as in vehicular systems.
• Miniaturized biological/chemical platforms — The modes of interaction with the analog, physical world will proliferate beyond today’s limited range of transducers and mechanical devices. Biological and chemical “lab-on-a-chip” devices, using technologies such as microfluidics and nanotechnology-based engineering, open up direct sensing and manipulation of biological systems, including the human body, in situ and with complete freedom of movement.
• Device packaging — Rapid miniaturization of these electronic and sensing components will result in the device size depending more on integration and packaging technologies. SiP (system-in-a-package) solutions and ultimately SoC (system-on-a-chip) solutions will be increasingly important, with the movement from 2D-chip integration to more flexible and compact 3D integration within the packaging giving rise to a significant reduction in device size. On a larger scale, flexible and stretchable printed circuits (Kim 2008) open up new applications that will play an increasingly important role (for example, conformal devices for instrumentation of biological organs or 3D printing of simple devices and electronic/mechanical substrates).
• Energy harvesting and storage — Energy autonomy can be defined as the elimination of battery replacement over a device lifetime. This could result in a major reduction in the per-device operational costs of an IoT device. Ongoing advances in energy storage and harvesting (solar, vibrational or electromagnetic) will extend the effective lifetime of the energy supply beyond the device’s lifetime. This will help drive the massive growth of IoT devices for which recharging is unfeasible or uneconomical. Figure 9 shows an example of a mechanical energy-harvesting device that could be used to power any device that has the requisite size and motion.
• Virtualized devices — For many objects, adding processing, memory or displays will be cost prohibitive. In such cases, only the essential sensing functionality and a wireless interface will be supported, and the remainder of the device logic will be virtualized and run in the cloud. Such device virtualization is described further in chapter 12, The future of the home.

Future devices and applications

While the pervasive digital automation brought about by IoT will be transformational in all walks of life, a few key applications and devices warrant a separate discussion. By far the largest segment of the wide-area wireless IoT — the connected vehicle — is set to expand further with self-driving cars and drones; these two will likely dominate IoT in economic value and introduce substantially new requirements on communications networks.

The use of drones for commercial activities is growing rapidly. Mary Meeker in her “Internet Trends 2015” report (Meeker 2015) shows more than a doubling of consumer drones each year for the last two years, and a Bell Labs projection in figure 10 shows rapid growth of commercial drones over the next decade. Drones are being used in a variety of industries such as agriculture, oil and gas, utilities and for disaster relief. In many cases, the drones are used for aerial photography, and the data is then analyzed to extract information about faults or other abnormal situations. As drones become more common and more sophisticated, the communications requirements will also increase. We expect real-time streaming of high-resolution video from the drones, rather than the capture and store approach that is typical today. We also expect the need for fast, real-time drone-to-drone communication, as well drone-to-ground station communication. These will ensure optimization of flight paths and dynamic control from ground stations to modify mission objectives based on real-time processing of gathered data. The latter will be especially relevant for public-safety applications such as fire fighting and disaster recovery after major incidents.

Self-driving cars rely on a large number of onboard sensors and cameras to automate the process of driving. While today’s autonomous cars do not assume any special infrastructure or vehicle-to-vehicle communication, major benefits will be realized from ultra-low-latency vehicle-to-vehicle and vehicle-to-roadside communication. The benefits will come from better use of roads and improved accident avoidance through “platooning” — organizing vehicles to be closely spaced with respect to each other like a platoon as they travel at high-speeds. Platooning requires low-latency, direct vehicle-to-vehicle communication and broadcast communication among vehicles to maintain appropriate vehicle speeds under various road conditions. Low-latency vehicle-to-vehicle communication also eliminates the need for street signals, thereby minimizing stopped times, and localized broadcast of emergency notifications between vehicles, which can help to significantly reduce accidents by warning drivers or control systems of the occurrence of an incident in their proximity.

Both drones and self-driving cars are among the new applications that call for low-latency and highly reliable mission-critical communication that will dominate our lives in the future, to allow the real-time remote control, warning or reconfiguration of these “digital things” to respond to their environment or address software, system or security issues, as discussed further in chapter 5, The future of the cloud. Similarly, remote robotic or industrial machine control and some critical infrastructure sensing applications (such as for an impending critical event) are other examples of the new class of applications that will be enabled by ultra-low-latency and high-reliability networks.

The net effect will be the realization of a broad and affordable range of options for connecting and interfacing with the physical world. This will result in the proliferation of ubiquitous digital automation in a multitude of areas where we are only able to scratch the surface today, as imagined in figure 11.

Sensors in the home and office will be connected to gateway nodes through short-range wireless personal-area networks or Wi-Fi access points. Some low-mobility sensors will also be connected through long-range LPWA to remove the dependence on local Internet connectivity. High-mobility sensors and other outdoor sensors will be connected through cellular networks, and some Internet gateways (connecting mission-critical services) will also use cellular interfaces as backup for the wireline Internet connection. The access connection will frequently terminate in a local-edge cloud where real-time processing and streaming analytics will occur. The resulting data will then be routed through the wide area network to a more centralized cloud where the key IoT software platforms manage and control devices, expose APIs to web-based applications and integrate with enterprise applications and processes.

The future begins now

The automation of our physical world has been ongoing for more than 50 years, and communications networks have played an integral part in the connection of these automated systems to allow remote control over ever-increasing distances. Network operators, web companies, software and hardware developers, and enterprises in specific industry sectors are all currently investing in new technologies and capabilities and experimenting with new services and business models, proofs-of-concept and limited-scale trials, and even new commercial offerings. These industry activities span all three of the major technology areas, namely IoT network technologies, software platforms and device technologies, as well as the integration of IoT into business processes:

• Telecommunications equipment vendors have announced the availability of LTE-M technology for deployment in 2016. They have also announced the availability of a smart-band IoT device using the LTE-M technology (Le Maistre 2015).
• Worldwide, mobile network operators are partnering with automotive suppliers to create the “connected” car. In North America, a major operator has announced a simple device for the car that can turn the car into a Wi-Fi hotspot and allow Wi-Fi enabled devices in the car to connect to the Internet and consume media and other applications (Goldstein 2015). A number of IoT services such as remote car diagnostics, automatic emergency crash notification, stolen vehicle tracking, roadside assistance, locating the car in a parking lot, sending directions to the car, and starting the car remotely to warm up on a cold day are also provided to the connected car.
• A European operator and a pharmaceutical company announced a partnership to provide mobile health services to patients (Vodafone 2014). The patients will be empowered to manage their conditions as a part of their daily routine using advanced technology.
• A startup network vendor acquired funding to deploy its LPWA network in the Belgian market (Sigfox 2015). In 2015, the company raised an additional 100 million euros in extra funding that is expected to finance network rollouts in the US, Latin America, Japan and South Korea following the signing of commercial agreements in these markets (Morris 2015).
• The mobile network operator forum, Next Generation Mobile Network (NGMN), has identified massive machine communication as a critical use case for 5G. In their white paper on 5G, they report that 5G should target connection densities of up to 200,000 devices per sq km in dense areas, battery life up to 15 years, low data rates of 1 to 100 kb/s and transaction latencies ranging from several seconds to hours.
• In 2015, the Federal Aviation Administration (FAA) approved over 500 companies to operate commercial drones in the United States. The drone applications include agriculture (mapping and assessment of crop damage), surveillance of pipes and other infrastructure in oil and gas, utilities and mining industries, and photography and videography for film production, real estate and mapping (Popper 2015).
• Innovation in wearables is also accelerating with numerous new devices targeting a range of applications across health, fitness, tracking and convenience. On the launch day of their range of smart watches, one of the leading device manufacturers also announced a software platform for large-scale eHealth studies enabled by the smart watch (New Scientist 2015). The instrumentation of the body will yield masses of public health data on a scale and speed never before attempted.

On software platforms, the following announcements suggest that the industry will transition to a more horizontal platform approach to building IoT solutions:

• A major vendor of IT hardware, software and services has announced a $3 billion investment in IoT technologies. Their investment is targeted at enabling the use of their data centers and sophisticated analytics software to crunch huge volumes of data streaming in from billions of connected devices (wind turbines, jet engines, building climate-monitoring systems, pacemakers and refrigerators) and encouraging application developers to use their platforms as a service upon which to build applications (Miller 2015).
• A major North American operator is opening their application development environment platform and services as part of an IoT developer program, to enable their customers to take their IoT applications from concept to production quickly and easily. The platform has been used for a wide range of vertical applications, such as farm-to-fork solutions, smart vending, mining site and equipment monitoring, building-energy management systems, medical device monitoring, and manufacturing site monitoring, demonstrating the horizontal nature of the platform (Verizon 2015).
• A leading European telecom vendor and Global M2M Association (GMA), an association of six tier-one operators worldwide, announced the deployment of the vendor’s connectivity management platform for “multi-domestic” service. This platform incorporates the subscription-management solution that allows field-configurable embedded SIMs to operate in any of the operator’s networks. In addition, the platform provides real-time connectivity management so that enterprises can manage, monitor, troubleshoot and support their connected devices operated globally from a single source (Allevan 2015).

Beyond individual industry segments, communities and cities are beginning to transform their infrastructure to become “smart”. The term “smart city” refers to an urban area where basic infrastructure, utilities and the environment are instrumented using IoT technology and a cross-application platform is used on which local government operations, planning staff, utility providers, businesses and individual citizens can build services and applications.

• Santander in Spain is an example smart city that has taken a comprehensive approach to IoT spanning multiple dimensions of a city. As part of a European Union-supported Future Internet Research and Experimentation project named SmartSantander, an extensive network of 12,000 sensors over 8 square kilometers have been deployed with a comprehensive software platform opening up APIs to third-party application developers. The range of applications in Santander is impressive, targeting timesaving for individual citizens (car park availability), informing city planners about the environment (environmental monitoring), and managing resources by local government operations (control of street lighting).
• While SmartSantander is clearly at the level of a limited-area pilot, other cities such as Singapore are now embarking on full-scale smart city deployments, with even more ambitious plans for transforming services used on a day-to-day basis by its citizens and businesses. The city is planning to deploy a Smart Nation Platform (SNP) that will include a connectivity layer and an IoT layer to facilitate sensing and data collection within the city with a view to making the environment more intelligent and interactive. The government is working with an ecosystem of partners to ensure that devices and applications interoperate (Fai 2015, IDA 2015).
• As the world’s premier sporting event, the Olympics have typically also been an opportunity for showcasing new technology, and the upcoming 2020 Olympics in Tokyo will be no exception. We can expect new IoT technology such as drones and self-driving cars equipped with five cameras, five laser sensors and an electronic map (Williams 2013) to be deployed to provide a phenomenal out-of-the-world experience for attendees. IoT technologies have already been used for several applications at the Sochi Olympics in 2014, including surveillance, facial recognition, digital signage and timekeeping (Ramsey 2014), and we can expect more at the Winter Olympics in Korea in 2018 and the Tokyo Olympics in 2020.

Summary

Humanity is on a never-ending journey to manage the world using technologies that save time and increase the ease with which we can perform tasks or acquire knowledge. In the panoply of human technological marvels, it is clear that pervasive digital automation of the physical world in the coming decade will likely loom large. The technologies needed to embed multiple dimensions of sensing and connectivity into billions of objects are maturing rapidly, with remarkable innovation around the globe. In addition, the set of networking innovations required to connect these digitally interfaced objects to the cloud, along with the software platforms and analytical techniques required to process streams (and reams) of data in real time and to turn it into valuable information and knowledge, are also being developed.

Further research and development is still needed to overcome remaining challenges in cost, massively increasing control plane capacity, dramatically increasing battery life and processing massive amounts of information in real time. But we have moved beyond the question of “if we will instrument and digitize our world?” to “how quickly?” We are entering the first phase of pervasive digitization, resulting in a sea change in how we monitor, control, live and work, using devices and things to “augment our existence” in every way imaginable. Geographic distance and economic circumstance will cease to matter and humanity will be changed in ways that make prior technological revolution waves seem more like ripples.

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1 - Data analysis by Bell Labs Consulting from various sources (Beecham 2008, Machina 2011a-e, Pyramid 2011, 2014).

2 - Representational state transfer, sometimes REsT, an architecture for designing network applications.

3 - Data analysis by Bell Labs Consulting from various sources (Magee 2014, Postscapes 2015)

4 - For example, the Sigfox network is an LPWA network. Details can be found at www.sigfox.com.