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A Whirlwind Tour of Internet of Things - An Executive Insight

Issue/Publish Date: Summer/Fall 2014

IoT: Executive Summary

Human race is on a perpetual mission to up the ante on its collective global progress via boost vectors such as productivity gains, quality of life improvements, expanded collaboration, and efficient usage of precious resources. Its recent ally in this endeavor is hyper-connectivity – not just of humans, but also machines, infrastructure, and things that are in the line of sight as well as remotely situated ones. With untethered connectivity of humans declared a fait accompli, the locus of attention has shifted to bringing greater interconnectivity and intelligence to non-ubiquitously-connected “things”. This recently minted revolution of sorts is popularly known by the moniker - Internet of Things, or IoT.

This article highlights the reasons behind the colossal IoT opportunity (see Figure 1), outlines IoT drivers and challenges, and unwraps the IoT bonanza to give a clear view of its building blocks, solution creation layers, and links in its value chain. Two case studies showcase the power of IoT in contemporary and futuristic applications. A top down approach paints the big picture first, followed by drill down of key constructs.

The Big Picture: IoT Drivers

As shown in Figure 2, IoT is driven by following four business drivers, at a macro level:

  • Productivity Gains: Opportunity to realize orders of magnitude productivity gains by exploiting the “network effect” or distributed intelligence, enabled by interconnectedness of virtually everything in the new expansive network (i.e. humans, machines, things, etc.).
  • Cross-Industry Collaboration: Opportunity to unlock new sources of revenues and profits across industry and geographic borders, by cross-pollination of ideas and innovations, reuse of solution building blocks, cohesive and collaborative efforts to design products and services that are modular in nature, yet can be utilized with relative ease to create purpose-built solutions.
  • Quality of Life Improvements: Opportunity to ease the burden expected to arise from the coming tsunami of aging populations, especially in many developed economies, by advancing and improving physical, emotional, mental, and financial welfare of aging populations, via IoT fueled innovations in healthcare treatments, diagnostics, wellness, fitness, care giving, etc.
  • Satisfying Increasing Demand for Resources: Opportunity to relegate austerity measures to back seat via proactive measures to withstand any resource shortages that can potentially be triggered by increasing demands from forecasted and continuing population growth. Think of this as a pre-planned measure to get ahead of the curve to avert any demand-supply imbalances.

The Big Picture: IoT Building Blocks

A simplified view of IoT building blocks is shown in Figure 3. Horizontal layers are stacked (i.e. the higher layer builds upon the lower layer), while the vertical layers can be designed to interface across some or all the horizontal layers. We expound on the horizontal layers further in the drilldown sections below.

To aid in comprehension, layer functions’ comparison is made to the elements of the human physiology.

  • Sensing Layer is responsible for data acquisition (both real time and scheduled time). It contains sensors that are digital equivalent of skin, eyes, ears, nose, etc. In the IoT realm, number of sensors can get into billions.
  • Connectivity Layer is responsible for providing connectivity within and across layers. It contains digital infrastructure equivalent of arteries, veins, nerves, etc.
  • Services Layer is responsible for providing a finished or almost finished product, ready for consumption by the service consumers. This layer assembles all the right components, in the IoT system, necessary for accomplishing a task. (For example, just as the brain could order the arm muscles to move the arm in a certain direction by a certain amount and insert the key in the door lock to unlock the door, similarly, the service layer, that is providing an automated vehicle unlocking service for example, can instruct a digital lock to unlock the vehicle door when an authorized digital fob or wireless digital key is within a couple of feet from the vehicle door.)
  • Management Layer is responsible for providing management services in aggregate as well as for each horizontal layer of the IoT building blocks. Management functions are typically classified into five different categories - Fault, Configuration, Accounting, Performance, and Security (FCAPS).
  • Third Party APIs allow external applications, services, and products to interface with the IoT system in order to provide specialized value added services, or to augment native IoT system capabilities.

The Big Picture: IoT Value Chain

IoT value chain is shown in Figure 4. First four links are value creation links. Fifth and final link on the top left is a value consumption link. On traversing the value chain clockwise from top right to top left, value chain contributions transition from the sub-system levels (i.e. sensing layer) to the integrated-system levels (i.e. services layer). Illustrative value capture percentages for each of the four links are also shown. As one would expect, links providing greater customization (i.e. applications and services) capture larger percentages compared to their counterparts providing less customized and more standardized contributions (i.e. endpoints and connectivity). The term “standardized” as used here, is not to be equated merely to be “compliant to some de facto standard or set of standards” but also to “more siliconizable” or “hardware-centric” solutions. In other words, greater customizability stems from greater software-centricity of the solutions.

Some value chain players may be represented in more than one link, due to their organic competencies, or due to M&A.

The Drilldown: IoT Network View

IoT Network View as shown in Figure 5, provides a peek beneath the surface of the IoT big picture, from hardware and network perspectives. It consists of four layers, described below.

  • Sensors/Actuators: The Sensing Layer (shown in Figure 3 earlier) is further sliced into two layers. The bottom slice consisting of sensors and actuators is responsible for collection of data or events, and, for execution of commands (i.e. actuation), typically triggered by one or more commands from higher layers. The other slice is responsible for aggregation and protocol translation and is discussed below.
  • Aggregators/Gateways: Aggregators are network devices that support IoT solution scalability by aggregating inputs from multiple sensors before sending them northbound to upper layer. Gateways are network devices that support IoT solution interoperability by performing network protocol translation. If an IoT application uses only a small number of sensors and actuators, no aggregation is needed. When sensors and actuators are "uni-lingual", no network protocol translation is needed. Aggregators and Gateways can thus be optional, as shown in Figure 4 by a direct link-chained arrow bypassing the aggregator/gateway layer and connecting adjoining layers directly.
  • Connectivity Cloud: This layer provides wide area connectivity. Depending on the network and end-service, one or more connectivity mechanisms can be utilized - e.g. terrestrial wired, terrestrial wireless, or satellite. Wired connectivity can be based on copper wires, optical fibers, or coaxial cables. Wide area connectivity enables service intelligence to be distributed across two or more layers of the IoT Network View, resulting in improved solution design flexibility and lower overall costs. For example, a lower cost, lower footprint sensor can be produced to participate in intelligent service design architecture because the intelligence can be hosted remotely rather than within the sensor itself.
  • Backend Infrastructure: This layer is like a conductor of a symphony orchestra. It contains intelligence to command and control all layers, as well as individual units in each of the four layers. It consists of servers, storage systems, and application specific appliances, that can host, run, and control IoT applications and service intelligence software.

The Drilldown: IoT Software Solution Stack

IoT is rapidly evolving. For most modern digital systems undergoing rapid evolution, programmability is the key to unlocking the magic of adapting and thriving via flexibility to transform as new system requirements emerge. IoT software solution stack is at the crux of enabling such programmability. As shown in Figure 6, IoT software solution stack consists of seven layers.

  • PHY/MAC layer provides PHYsical transport services of bits from sender to receiver and transport Medium Access Control. Some of the things enabled by the low level software (a.k.a. firmware) at this layer include providing Quality of Service (QoS) or priority level assignment to different tasks. It also enables setting of various threshold levels (e.g. when a specific event occurs a certain number of times, then generate a notification).
  • Embedded OS layer contains small footprint operating system which can conveniently be accommodated in constrained memory, processing power, and energy level environments that are typically characteristic of devices such as sensors and actuators. Embedded OS services include resource management, task scheduling, debugging, high level programming language support, etc. Sometimes such operating system may not be embedded within individual sensors or actuators themselves, but may reside in other elements such as aggregators, gateways, etc.
  • Cloud OS layer enables unlocking the benefits of the cloud such as virtualization (i.e. hardware/software technology agnosticism), multi-tenancy (i.e. hardware/software resource sharing amongst multiple service consumers or tenants), Service Level Agreements (i.e. guaranteed service availability or uptime), etc. Sometimes this layer may also be referred to as Distributed Network OS layer or Control Plane layer.
  • Service Delivery layer provides service provisioning, activation, deactivation, etc. For example, if an IoT sensor supports cellular connectivity, its Subscriber Identity Module (SIM) card can be activated by service provided by this layer. If the device is a machine, then MIM (or Machine Identity Module) card activation can be used. Such SIM/MIM activations/deactivations can be done locally or remotely, and individually or in bulk. Other services supported by this layer could include service billing, remote software and firmware updates on devices, etc. Software platforms known as Service Delivery Platforms (SDPs) are typically off-the-shelf software platforms that with minimal customization can deliver functionality expected of a Service Delivery layer. Sometimes SDPs may also be referred to as Service Enablement Platforms.
  • Application Enablement layer provides services to make applications scalable and technology agnostic by decoupling "data/message producers" and "data/message subscribers". It provides clearinghouse type facility for transport and delivery of data across multiple applications. This layer is also referred to as IoT middleware, or IoT Integration Platform, or IoT Message Bus.
  • Business Logic layer is where intelligence specific to final IoT service gets programmed in. For example, business processes or workflows, business policies or rules, etc., are coded per the end service desired.
  • Application User Interface layer is where information is presented to the service consumer in terms of insights, knowledge, etc. that is processed from multitude of underlying sources of data or messages or events. Some examples of presentation formats are visual graphs, custom reports or dashboards, control panels, etc. Customization capabilities can be provided in terms of scripting languages, application stores containing dynamically updatable application catalogs, Application Programming Interfaces (APIs), etc.

Conclusion: IoT Opportunities, Challenges, and Key Takeaways

IoT driven mega opportunity decade is coming into focus. Rising IoT tide is expected to lift all stakeholder boats - from hardware manufacturers to software developers, component providers to system integrators, service providers to service consumers, developed economies to emerging economies, civilian sectors to military complexes, residential dwellings to enterprises of all sizes and sectors.

Open hardware and open software platforms are bending the cost curve lower and fostering prototyping of IoT products and services. Lines are continuing to blur across consumer and enterprise grade applications (e.g. productivity apps), devices (e.g. Bring Your Own Device or BYOD), and technologies (e.g. cloud, big-data, social networks, analytics, web services, wireless internet devices, etc.), creating new economies of scale driven opportunities for IoT services. Rapid growth/adoption of speedier internet connectivity, devices, and real-time information sharing networks are sidelining slow-movers and conferring premium valuations to deeper end-to-end insight providers.

As the saying goes, with privilege comes responsibility, similarly, with opportunity comes challenge. One major challenge dampening off-the-charts IoT growth is the IoT standardization conundrum. There are over 140 standards bodies engaged in IoT standardization. IoT is too big (or too fragmented) a space currently, to be dominated by a single vendor or standard. Since IoT cuts across multiple technology domains, it is unrealistic to expect a single IoT standard for the whole stack. Rather one can expect dominant standard to be established for each layer of the stack, each of which may then be further tuned to interoperate more finely with both its northbound and southbound neighbors as appropriate, thus achieving better and better end-to-end operability ultimately.

Key IoT takeaways are shown in Figure 7.

IoT Case Study #1: Remote Patient Monitoring (Healthcare Application)

Summary: Remote Patient Monitoring (RPM) for patients with Congestive Heart Failure (CHF) is an IoT technology enabled care delivery model that extends continuum of care by building a bridge between healthcare delivery network and patient’s home by delivering monitoring data to clinicians from remotely monitored patients diagnosed with CHF condition. RPM provides significant benefits to all stakeholders including patients, caregivers, payers, service providers, solution enablers, etc.

Situation: Heart failure is a chronic condition. Patients with CHF have heart failure that results in impaired blood pumping function of their heart due to congestion in breathing caused by fluid buildup in their chest area. Globally, about 1 billion people are diagnosed with different chronic conditions with combined spend on chronic care exceeding $1 trillion annually. Aging populations are expected to further exacerbate the statistics. In US alone, about 6 million people have CHF, and annual spend on treatment of heart related conditions exceeds $100 billion. By 2020, about 15 million deaths are forecasted from heart disease alone in US.

Challenges: Currently there is a lack of solutions for obtaining objective, frequent, and automated measurements to track CHF progression for out-of-hospital CHF patients. Non-connected and non-interoperable monitoring devices are compounding the situation further in terms of increasing costs and value-chain complexity. Shortage of skilled workers and increasingly aging populations are putting strain on healthcare resources and services. Government fiscal reforms (e.g. Accountable Care Act (ACA) in US) have created significant cost pressures on public and private payers creating a dire need to improve productivity of healthcare delivery system as well as linking healthcare payments to value and outcomes (e.g. lower hospital readmission rates for CHF patients).

Solution: Increases in body weight are associated with hospitalization for CHF, and begin at least one week before admission. Daily information about patients’ body weight identifies a high-risk period during which interventions can be implemented to avert acute rescue events related to CHF. Connected device such as scale can immediately log and communicate the programmed threshold weight gain crossed information via connected home gateway to its off-premise interfacing element, alerting clinical personnel to activate necessary intervention action. Though weight gain monitoring is pivotal in early detection and intervention in CHF patients, other dimensions are important too (see Figure 8). Collectively such a solution is referred to as Remote Patient Monitoring solution.

Benefits: Studies have shown that patients suffering heart attack have 48% chance of survival if they are being monitored at the time of event compared to 6% survival chance otherwise. IoT solutions can enable continuous monitoring of CHF patients. Savings of more than $10 billion is forecasted annually for US CHF patients being remotely monitored due to fewer and shorter hospital stays, and reduced CHF related mortality rates.

IoT Case Study #2: Connected Smart Car (Transportation Application)

Summary: Automotive technologies have come a long way. Advanced Driver Assistance System (ADAS) boasting sophisticated capabilities such as adaptive cruise control, blind spot detection, night vision, etc. is proof of noteworthy progress. To move the needle further on safety and driving experience, shifting gears from ultimate-driving-machine to ultimate-self-driving-machine may be in order. Meeting new or updated regulatory mandates for higher fuel efficiency, rapid emergency notification capabilities, and stricter emissions levels are additional signals to do the shift.

Situation: Despite advances in transportation technologies, every year there are still over 1.25 million road related deaths worldwide, of which about 35,000 are in US alone. Aging population trends continue to build pressure to offload drivers’ driving duties onto their vehicles. Growing middle class in emerging economies has car ownership high on the wish list, but such geographies neither have nor can yet afford sophisticated traffic management systems, well-paved road infrastructure, robust pollution control and enforcement capabilities. Even an advanced country like US spends over $75 billion annually on roads, highways, and bridges, yet faces a funding shortfall in excess of 50% to adequately meet its real funding needs for the same.

Challenges: A self driving car has to mimic human cognition and control skills using a multitude of technologies. Integrated-system level testing of many new technologies, for umpteen use cases, is a herculean undertaking, fraught with risk of missing out on testing of some boundary conditions that may prove costly and even fatal. Interoperability with existing, multi-vendor, multi-standard, or even proprietary technology based vehicles is another obstacle to overcome. Creation and adoption of new governance framework and policies are also a challenge to overcome (e.g. legal and liability issues from autopilot originated errors, errors triggered by command and control transfer from autopilot to human and vice-versa).

Solution: Though self-driving or autonomous car is an end goal that is a few years out, Connected Smart Car is a march towards that goal. Figure 9 shows four major functional classifications of connected smart car – C2C, C2I, C2P, and C2X. Major objectives of each of these classifications are co-operation, co-ordination, crash-containment, and collaboration, respectively.

C2C technology enables exchange of anonymous, vehicle data regarding position, speed, and location with other vehicles in the proximity using a suite of short and long range communications (e.g. Dedicated Short Range Communications (DSRC), Cellular, and Satellite), detection (e.g. Ultrasonic, Laser Radar (i.e. LIDAR), and Radar), positioning (e.g. GPS), and vision (Optical Camera) technologies (see Figure 10).

C2I technology enables communications between vehicles and road-side units and transportation infrastructure (e.g. traffic signals, road-side units such as speed cameras, surveillance camera data, weather related data, highway signs and associated traffic management messages, toll booths, electric vehicle charging stations, etc.).

C2P technology is employed primarily for collision avoidance via detection and notification of humans in the vicinity of the vehicle, both within and outside its line of sight.

C2X is a catch-all term, but is used here for scenarios other than those covered by C2C, C2I, and C2P. For example, relaying vehicle diagnostics and health status as captured by the on-board unit to an authorized service center; scheduling auto-update or maintenance appointment; auto-reporting in-progress vehicle theft event to law enforcement authority; summoning roadside assistance on vehicle breakdown; searching and locating a parking garage with available parking space and self-parking.

With advances powered by IoT related technologies and standards, dream of creation and mass adoption of self driving cars will become a reality in near future. Synergies between connected smart car and other IoT verticals such as connected home, connected health, connected grid, and connected cities, offer additional opportunities to leverage.

Benefits: A self driving car with radio-waves, ultrasonic, and optical vision technologies can see about 600 feet in all directions - using sensors such as LIDAR, Radar, Sonar, and Optics - eliminating blind spots, avoiding crashes, and fatalities. Real-time communications, co-operation, and co-ordination between vehicles and the roadside equipment will allow closer packing of vehicles to move in a platoon or convoy formation, increase efficiency of road utilization, improve fuel efficiency due to drag reduction, and cut maintenance costs due to adherence to speed limits. Insurance premiums will be lower due to fewer fatalities and vehicle breakdown payouts. Offloading the driving function from human to vehicle will boost productivity and improve travel experience.

With 1.2 billion cars on the road around the world, and about 85 million new cars sold each year, market size opportunity for both pre-market and after-market products, apps, and services for connected smart vehicle is tremendous.

Editor's Note: The article above provided a sneak peek into the research we conduct on Internet of Things and beyond. If you are an IoT ecosystem stakeholder, or contemplating becoming one, our staff can help you with strategy, technology, or other relevant business aspects. Please browse our Services page to learn more about the services we offer. To get in touch with us, please use the Contact page.