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Internet of Things

In: Computers and Technology

Submitted By pragyav
Words 13930
Pages 56
| Internet of Things |

2014| Pragya Vaishwanar | Aricent Marketing Research Report |


It’s fair to say that more people have heard of the “internet of things” than have experienced it. More objects are becoming embedded with sensors and gaining the ability to communicate. The resulting information networks promise to create new business models, improve business processes, and reduce costs and risks. There is breathless press coverage of the phenomenon—always patiently re-explained by tech pundits as the trend by which all of one’s most mundane possessions will become internet-connected. These are invariably coupled with estimates that the internet of things will be a multi-trillion dollar business. 2014 is really, finally the year that the “internet of things”—that effort to remotely control every object on earth —becomes visible in one’s everyday lives. In a sense the internet of things is already with us. For one thing, anyone with a smartphone has already joined the club. The average smartphone is brimming with sensors—an accelerometer, a compass, GPS, light, sound, altimeter. It’s the prototypical internet-connected listening station, equally adept at monitoring our health, the velocity of our car, the magnitude of earthquakes and countless other things that its creators never envisioned.
Yet despite repeated declarations one of the most successful sellers of baubles that help make your home “smart,” Smart-things, has only shipped 10,000 or so units since its debut a year ago. (Compare that to, say, the 360 million smartphones sold in China in 2013 alone.) Remotely-operated light switches and weather-aware fridges may sound fun, but people have yet to be convinced that they can solve any pressing problems. Almost everyone who is actually connecting “things” to the internet remains a hobbyist or hard-core geek—the sort of person whose itch for novelty is satisfied by internet-connected Christmas lights that change color when you tweet at them.
The widespread adoption of the Internet of Things will take time, but the time line is advancing thanks to improvements in underlying technologies. Advances in wireless networking technology and the greater standardization of communications protocols make it possible to collect data from these sensors almost anywhere at any time. Ever-smaller silicon chips for this purpose are gaining new capabilities, while costs, following the pattern of Moore’s Law, are falling. Massive increases in storage and computing power, some of it available via cloud computing, make number crunching possible at very large scale and at declining cost.
The internet of things will be about the convergence of ever-smarter smartphones and connected “things” that are cheaper and easier to use. In 2014, there will be countless ways to join the internet of things. What remains to be seen is how many of us are ready to take the plunge.
Table of Contents

Summary 2 Definition 5 Current Wireless Landscape 7 Internet of Things’ Trends and Characteristics 9 “Smart” 10 Architecture 10 Complex System 11 Size Considerations 11 Time Considerations 11 Space Considerations 11 Applications 12 Building Blocks of the Internet of Things 13 Sensing Nodes 13 Layers of Local Embedded Processing Nodes 13 Gateways and Networks 15 Management Service Layer 15 Application Layer 16 What’s in it for OEMs? 17 Information and Analysis 17 Automation and Control 19 Software to Automate Tasks 21 Remote Embedded Processing Nodes (Access to Cloud Computing) 21 What’s in it for Operators? 22 Top Players 24 VC Funding for Startups 26 Key Internet of Things Market Adoption Drivers 28 Miniaturization of Devices 28 Radio Frequency Identification (RFID) 30 Internet Protocol version 6 (IPv6) 30 Increasing Communication Throughput and Lower Latency 31 Real-Time Analytics 32 Cloud Computing 32 Security and Privacy 33 Key Internet of Things Market Adoption Hurdles 35 Standardization and Integration 35 Cost Versus Usability 35 Privacy and Security 36 Interoperability 36 Network Capacity Constraints 37 Future of Internet of Things 38 Coolest Internet of Things Innovations 39 Latest News 41 Top Communities 42 Twitter Trending: 42 Forums 42 Groups 42 References 44


The Internet of Things (or IoT for short) refers to uniquely identifiable objects and their virtual representations in an Internet-like structure. The term Internet of Things was proposed by Kevin Ashton in 1999. The concept of the Internet of Things first became popular through the Auto-ID Center at MIT and related market analysis publications. Radio-frequency identification (RFID) was seen as a prerequisite for the Internet of Things in the early days. If all objects and people in daily life were equipped with identifiers, they could be managed and inventoried by computers. Besides using RFID, the tagging of things may be achieved through such technologies as near field communication, barcodes, QR codes and digital watermarking.
Equipping all objects in the world with minuscule identifying devices or machine-readable identifiers could transform daily life. For instance, business may no longer run out of stock or generate waste products, as involved parties would know which products are required and consumed. A person's ability to interact with objects could be altered remotely based on immediate or present needs, in accordance with existing end-user agreements.
A thing, in the Internet of Things, can be a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low - or any other natural or man-made object that can be assigned an IP address and provided with the ability to transfer data over a network. So far, the Internet of Things has been most closely associated with machine-to-machine (M2M) communication in manufacturing and power, oil and gas utilities. Products built with M2M communication capabilities are often referred to as being smart.
Depending on who you talk to, IoT is defined in different ways, and it encompasses many aspects of life—from connected homes and cities to connected cars and roads (yes, roads) to devices that track an individual’s behavior and use the data collected for “push” services. Some mention one trillion Internet-connected devices by 2025 and define mobile phones as the “eyes and ears” of the applications connecting all of those connected “things.” Depending on the context, others give examples that are less phone-centric, speak of a class of devices that do not exist today or point to Google’s augmented-reality smart glasses as an indication of things to come. Everyone, however, thinks of the IoT as billions of connections (a sort of “universal global neural network” in the cloud) that will encompass every aspect of our lives. All of this public discussion suggests the IoT is finally becoming a hot topic within the mainstream media. Many recent articles point to the IoT as the interaction and exchange of data (lots of it) between machines and objects, and now there are product definitions reflecting the same concept. Hence, from a technology perspective, IoT is being defined as smart machines interacting and communicating with other machines, objects, environments and infrastructures, resulting in volumes of data generated and processing of that data into useful actions that can “command and control” things and make life much easier for human beings .

Current Wireless Landscape

The IoT will encompass all aspects of one’s everyday life, hence there is no limit to the distances for which command and control communication can/will be used.
If one were to design wired and wireless technologies for the IoT from the ground up, they may or may not end up with the communications landscape as is known today. However, many of the companies offering wireless and wired solutions are positioning their products as “the communication engine of choice” for the IoT market. The IoT will also add the concept of wireless sensor and actuator networks (WSANs), which are networks that contain sensing and embedded processing nodes that can control their environment. As with any emerging market, a transition period before system optimization takes place and technologies become better-suited for the end IoT-related applications is likely. Based on typical product life cycles and the role of software, it would be safe to say that if a technology takes hold in an IoT segment now, that technology (or an optimized-to-purpose version of it) will be in place for at least the next five to eight years. There are some battle lines already drawn that may be solidifying. For example, it seems as though Bluetooth® Low Energy (BTLE) is being adopted by the health care industry for portable medical and lifestyle devices. On the other hand, the battle between ZigBee® and low-power Wi-Fi® technologies for industrial control and automation has just begun. Operators are urgently looking for new revenue streams, and machine-to-machine communication and location-based services seem to be good places to make a bet. Both can use existing infrastructure and are very much a part of the emerging IoT market.

Major volumes for the IoT market will likely not happen for another 10-12 years, and, at that time, the communications technologies may be completely different from those being considered today, or new revisions of existing standards may have emerged. Wi-Fi technologists already are working on 802.11ah (Wi-Fi on ISM bands below 1 GHz) to tailor it for infrastructure independent ad-hoc, mesh networking and longer-range control of sensor networks. Alternatively, there could be brand-new technologies better suited for certain aspects of IoT communication that displace the existing standards for the IoT. One thing about the connectivity needs of the future IoT market is clear—it is so diverse, large and cost-conscious that a range of different technologies will be needed (possibly including WAN, LAN, WPAN, WBAN, etc.), and one size will not fit all. Requirements for communication functions are almost the same as for embedded processing nodes: * Cost-effectiveness * Low power * Quality and reliability * Security

Internet of Things’ Trends and Characteristics

Today, there is an electrification of the world. Almost any manufactured good now includes an embedded processor (typically a microcontroller, or MCU), along with user interfaces, that can add programmability and deterministic “command and control” functionality. According to ABI Research more than 30 billion devices will be wirelessly connected to the Internet of Things (Internet of Everything) by 2020. Cisco created a dynamic "connections counter" to track the estimated number of connected things from July 2013 until July 2020. This concept, where devices connect to the internet/web via low power radio is the most actively researched area in the IoT space. IoT has evolved from the convergence of wireless technologies, micro-electromechanical systems (MEMS) and the Internet.

The electrification of the world and the pervasiveness of embedded processing are the keys to making objects “smart.” After a device becomes smart through the integration of embedded processing, the next logical step is remote communication with the smart device to help make life easier. Communication capability and remote manual control lead to the next step – to automate things and, based on one’s settings and with sophisticated cloud-based processing, make things happen without their intervention. That’s the ultimate goal of some IoT applications. And, for those applications to connect with and leverage the Internet to achieve this goal, they must first become “smart” (incorporate an MCU/embedded processor with an associated unique ID) then connected and, finally, controlled. Those capabilities can then enable a new class of services that makes life easier for their users. For the network, sophisticated cloud-based processing requires a new generation of communications processors that can keep track of all of those connected devices, communicate with them and translate their functionality into useful services, all with nonlinear improvement to their performance and efficiency. The challenge will be to build secure networks that keep up with demand, while simultaneously reducing energy consumption and cost of equipment.
Embedded intelligence presents an “AI-oriented” perspective of Internet of Things, which can be more clearly defined as: leveraging the capacity to collect and analyze the digital traces left by people when interacting with widely deployed smart things to discover the knowledge about human life, environment interaction, as well as social connection/behavior.
The system will likely be an example of event-driven architecture, bottom-up made (based on the context of processes and operations, in real-time) and will consider any subsidiary level. Therefore, model driven and functional approaches will coexist with new ones able to treat exceptions and unusual evolution of processes (Multi-agent systems, B-ADSc, etc.).
In an Internet of Things, the meaning of an event will not necessarily be based on a deterministic or syntactic model but would instead be based on the context of the event itself: this will also be a semantic web. Consequently, it will not necessarily need common standards that would not be able to address every context or use: some actors (services, components, avatars) will accordingly be self-referenced and, if ever needed, adaptive to existing common standards (predicting everything would be no more than defining a "global finality" for everything that is just not possible with any of the current top-down approaches and standardizations). Some researchers argue that sensor networks are the most essential components of the Internet of Things.

Complex System
In semi-open or closed loops (i.e. value chains, whenever a global finality can be settled) it will therefore be considered and studied as a Complex system due to the huge number of different links and interactions between autonomous actors, and its capacity to integrate new actors. At the overall stage (full open loop) it will likely be seen as a chaotic environment (since systems have always finality).
Size Considerations
The Internet of objects would encode 50 to 100 trillion objects, and be able to follow the movement of those objects. Human beings in surveyed urban environments are each surrounded by 1000 to 5000 trackable objects.
Time Considerations
In this Internet of Things, made of billions of parallel and simultaneous events, time will no more be used as a common and linear dimension but will depend on each entity (object, process, information system, etc.). This Internet of Things will be accordingly based on massive parallel IT systems (Parallel computing).
Space Considerations
In an Internet of Things, the precise geographic location of a thing—and also the precise geographic dimensions of a thing—will be critical. Currently, the Internet has been primarily used to manage information processed by people. Therefore, facts about a thing, such as its location in time and space, have been less critical to track because the person processing the information can decide whether or not that information was important to the action being taken, and if so, add the missing information (or decide to not take the action). The GeoWeb and Digital Earth are promising applications that become possible when things can become organized and connected by location. However, challenges that remain include the constraints of variable spatial scales, the need to handle massive amounts of data, and an indexing for fast search and neighbour operations. If in the Internet of Things, things are able to take actions on their own initiative, this human-centric mediation role is eliminated, and the time-space context that we as humans take for granted must be given a central role in this information ecosystem. Just as standards play a key role in the Internet and the Web, geospatial standards will play a key role in the Internet of Things.

While there are literally hundreds of applications being considered and identified by different industries, they can be categorized in a simple, logical way. Fields of applications include: waste management, urban planning, environmental sensing, social interaction gadgets, sustainable urban environment, continuous care, emergency response, intelligent shopping, smart product management, smart meters, home automation and smart events. One key issue with the Internet of Things is the ability to rapidly create Internet of Things applications. An approach taken by the Media and Graphics lab at the University of British Columbia (Canada) focuses on a lightweight toolkit for developing Internet of Things applications and targets rapid development using Web technologies and protocols.
Category One: Aware Applications
Category one encompasses the idea of millions of heterogeneous “aware” and interconnected devices with unique IDs interacting with other machines/objects, infrastructure, and the physical environment. In this category, the IoT largely plays a remote track, command, control and route (TCC&R) role. As with all aspects of the IoT, safety and security are paramount. These applications are not about data mining of people’s behaviors (along the lines of “big brother watching”) but rather they extend the automation and machine-to-machine (M2M), machine-to-infrastructure (M2I) and machine-to-nature (M2N) communications that can help simplify people’s lives.
Category Two: Data Applications
The second category is all about leveraging the data that gets collected by the end nodes (smart devices with sensing and connectivity capability) and data mining for trends and behaviors that can generate useful marketing information to create additional commerce. Credit card companies and membership shopping clubs already track and use people’s behavior, to an extent, to come up with offers that may promote incremental sales. Now, the question is how far will this data mining go? Use cases could include a store tracking which aisles one visited, where one spent the most time within those aisles and even what type of items they lifted and browsed. This scenario is easily possible using a mobile phone’s GPS capability, RFID and smart tags in stores and wireless tags. The result could be as simple as providing email offers or “push” services at the point of sale. Or, it could go further, with one’s car insurance company tracking their driving habits and places traveled to assign risk factors that help determine one’s monthly premium, for example. It is visible how this category can become a slippery slope and how the IoT can enable data collection in every aspect of one’s everyday life and assign a “category” to a person, with pleasant or unpleasant consequences.
When others become aware of the context associated with an entity, a person or a group (hence, knowing identity, location, activity and time), to what extent can that data be used, and to what extent should have a say in how that data gets used? This second category, especially, spurs discussions about privacy, security, governance and the social responsibility that comes along with such a “self-aware,” connected world.
Building Blocks of the Internet of Things

Sensing Nodes
The types of sensing nodes needed for the IoT vary widely, depending on the applications involved. Sensing nodes could include a camera system for image monitoring; water or gas flow meters for smart energy; radar vision when active safety is needed; RFID readers sensing the presence of an object or person; doors and locks with open/close circuits that indicate a building intrusion; or a simple thermometer measuring temperature. The bottom line is that there could be many different types of sensing nodes, depending on the applications. These nodes will all carry a unique ID and can be controlled separately via a remote command and control topology. Use cases exist today in which a smartphone with RFID and/or NFC and GPS functionality can approach individual RFID/NFC-enabled “things” in a building, communicate with them and register their physical locations on the network. Hence, RFID and NFC will have a place in remote registration, and, ultimately, command and control of the IoT.
Layers of Local Embedded Processing Nodes
Embedded processing is at the heart of the IoT. Local processing capability is most often provided by hybrid microcontrollers/microprocessors (MCUs/MPUs) or integrated MCU devices, which can provide the “real-time” embedded processing that is a key requirement of most IoT applications. Fully addressing the real-time embedded processing function requires a scalable strategy (using a scalable family of devices), as one size will not fit all. There are a few requirements that make an MCU ideal for use in the IoT: * Energy efficiency: First and foremost, the MCU needs to be energy-efficient. In many cases, the sensing nodes are battery-operated satellite nodes, so a low-power spec is a basic requirement. Integrated circuit (IC) designers have many ways to reduce power consumption, including low-leakage process technologies, best-in-class low-power non-volatile memory/flash memory technologies, architectural innovations and various clocking schemes. For battery operated nodes, all of those techniques are needed to achieve the lowest possible power consumption. * Embedded architecture with a rich software ecosystem: The wide variety of potential IoT applications needs a software development environment that ties together the applications, the command, control and routing processing and the security of the node and system. While the importance of software in MCU solutions has increased during the past few years, for MCUs supporting the IoT, even more software, tools and enablement will be needed. A broad ecosystem with easily accessible support is key to enabling the development of embedded processing nodes and IoT applications. * Portfolio breadth that enables software scalability: The ability to reuse software and leverage existing software investment is a key success factor for companies developing IoT applications. Software reuse enables the rapid rollout of multi-layered architectures (in which the embedded processor is tasked with different layers and levels of tracking, command, control and routing functions). * Portfolio breadth that cost-effectively enables different levels of performance and a robust mix of I/O interfaces: The diversity of things to be controlled in the IoT, along with the different use cases, the number of things in a micro-network, different levels of service required and different interfaces in a heterogeneous environment will lead to the need for different tiers of devices, with diverse I/Os required for the various applications. A “one size fits all” approach will not be cost- or performance-optimized enough to satisfy the needs of this market. * Cost-effectiveness: As with any other market, mass adoption will not take place until a certain price point for the solutions is reached. Like all other systems, the overall cost is the sum of the parts of the system plus the cost of the services required for the system. The overall system cost must be affordable for the paradigm shift to take hold in everyday life, so product cost is a very relevant factor. * Quality and reliability: Unlike a mobile phone, laptop or other electronic device that one may change every two years, product life cycles in the industrial market are at least 10-15 years. Even inside a home, certain devices, such as thermostats, aren’t changed that often. When one adds the automotive market to the mix, more stringent reliability requirements and harsh environmental conditions must be supported. Hence, quality, reliability and longevity requirements for these markets are keys to the success of the IoT paradigm shift. Although shifting the bulk of heavy-duty data processing and analysis to remote supercomputing nodes in the network cloud is available and allows the local nodes “live longer” (not become obsolete as fast), there is still a balance between how much local vs. remote processing will be needed. This is especially important for time-critical applications that prefer local processing. * Security: For the local embedded processing node at the physical layer, there are a variety of cryptographic engines and security accelerators to support data encryption (e.g. DES, AES, etc.) and authentication (e.g. SHA, etc.). Additional layers of security software, as well as best practices related to boot-up routines, are among the variety of security approaches available.
Gateways and Networks
Massive volume of data will be produced by these tiny sensors and this requires a robust and high performance wired or wireless network infrastructure as a transport medium. Current networks, often tied with very different protocols, have been used to support machine-to-machine (M2M) networks and their applications. With demand needed to serve a wider range of IoT services and applications such as high speed transactional services, context-aware applications, etc, multiple networks with various technologies and access protocols are needed to work with each other in a heterogeneous configuration. These networks can be in the form of a private, public or hybrid models and are built to support the communication requirements for latency, bandwidth or security.
A possible deployment could consist of a converged network infrastructure that resolves the fragmentation by integrating disparate networks into a single network platform. Converged network layer abstraction allows multiple organisations to share and use the same network independently for their information to be routed without compromising their privacy, security and performance requirements. Each organisation thus utilises the network as if it is a private network resource to them.
Management Service Layer
The management service renders the processing of information possible through analytics, security controls, process modelling and management of devices.
One of the important features of the management service layer is the business and process rule engines. IoT brings connection and interaction of objects and systems together providing information in the form of events or contextual data such as temperature of goods, current location and traffic data. Some of these events require filtering or routing to post-processing systems such as capturing of periodic sensory data, while others require response to the immediate situations such as reacting to emergencies on patient’s health conditions. The rule engines support the formulation of decision logics and trigger interactive and automated processes to enable a more responsive IoT system. In the area of analytics, various analytics tools are used to extract relevant information from massive amount of raw data and to be processed at a much faster rate. Analytics such as in-memory analytics allows large volumes of data to be cached in random access memory (RAM) rather than stored in physical disks. In-memory analytics reduces data query time and augments the speed of decision making. Streaming analytics is another form of analytics where analysis of data, considered as data-in-motion, is required to be carried out in real time so that decisions can be made in a matter of seconds. For example, this requirement is typical in the transportation sector where real-time traffic information enables drivers to optimise their routes and travelling times.
Analytics can be carried out at other layers within the IoT architecture. For example, analytics may be carried out in the smart object layer, i.e., local hub or edge device, so that subsets of the information can be carried through the network for further processing. At this layer, analytics helps to reduce the stress placed on the network layer, reduce power needs of sensors by less frequent communication backend and allow faster responses to data received by the sensors.
Data management is the ability to manage data information flow. With data management in the management service layer, information can be accessed, integrated and controlled. Higher layer applications can be shielded from the need to process unnecessary data and reduce the risk of privacy disclosure of the data source. Data filtering techniques such as data anonymisation, data integration and data synchronisation, are used to hide the details of the information while providing only essential information that is usable for the relevant applications. With the use of data abstraction, information can be extracted to provide a common business view of data to gain greater agility and reuse across domains. Lastly, security must be enforced across the whole dimension of the IoT architecture right from the smart object layer all the way to the application layer. Security is of the utmost importance as the integrity of the data must be protected as data travels across the entire system. The integrity of data enables reliable and authentic decisions to be made. Moreover, security of the system prevents system hacking and compromises by unauthorised personnel, thus reducing the possibility of risks.
Application Layer
There are various applications from industry sectors that can leverage on IoT. Applications can be verticalised ones that are specific to a particular industry sector, and other applications such as Fleet Management, Asset Tracking, and Surveillance can cut across multiple industry sectors.

What’s in it for OEMs?

Nothing about IoT is news to technology companies and those on the frontier of adoption. But as these technologies mature, the range of corporate deployments will increase. Now is the time for executives across all industries to structure their thoughts about the potential impact and opportunities likely to emerge from the Internet of Things. There are six distinct types of emerging applications, which fall in two broad categories: first, information and analysis and, second, automation and control.
Information and Analysis
As the new networks link data from products, company assets, or the operating environment, they will generate better information and analysis, which can enhance decision making significantly. Some organizations are starting to deploy these applications in targeted areas, while more radical and demanding uses are still in the conceptual or experimental stages. 1. Tracking behavior: When products are embedded with sensors, companies can track the movements of these products and even monitor interactions with them. Business models can be fine-tuned to take advantage of this behavioral data. Some insurance companies, for example, are offering to install location sensors in customers’ cars. That allows these companies to base the price of policies on how a car is driven as well as where it travels. Pricing can be customized to the actual risks of operating a vehicle rather than based on proxies such as a driver’s age, gender, or place of residence. Or consider the possibilities when sensors and network connections are embedded in a rental car: it can be leased for short time spans to registered members of a car service, rental centers become unnecessary, and each car’s use can be optimized for higher revenues. Zipcar has pioneered this model, and more established car rental companies are starting to follow. In retailing, sensors that note shoppers’ profile data (stored in their membership cards) can help close purchases by providing additional information or offering discounts at the point of sale. Market leaders such as Tesco are at the forefront of these uses. In the business-to-business marketplace, one well-known application of the Internet of Things involves using sensors to track RFID (radio-frequency identification) tags placed on products moving through supply chains, thus improving inventory management while reducing working capital and logistics costs. The range of possible uses for tracking is expanding. In the aviation industry, sensor technologies are spurring new business models. Manufacturers of jet engines retain ownership of their products while charging airlines for the amount of thrust used. Airplane manufacturers are building airframes with networked sensors that send continuous data on product wear and tear to their computers, allowing for proactive maintenance and reducing unplanned downtime. 2. Enhanced situational awareness: Data from large numbers of sensors, deployed in infrastructure (such as roads and buildings) or to report on environmental conditions (including soil moisture, ocean currents, or weather), can give decision makers a heightened awareness of real-time events, particularly when the sensors are used with advanced display or visualization technologies. Security personnel, for instance, can use sensor networks that combine video, audio, and vibration detectors to spot unauthorized individuals who enter restricted areas. Some advanced security systems already use elements of these technologies, but more far-reaching applications are in the works as sensors become smaller and more powerful, and software systems more adept at analyzing and displaying captured information. Logistics managers for airlines and trucking lines already are tapping some early capabilities to get up-to-the-second knowledge of weather conditions, traffic patterns, and vehicle locations. In this way, these managers are increasing their ability to make constant routing adjustments that reduce congestion costs and increase a network’s effective capacity. In another application, law-enforcement officers can get instantaneous data from sonic sensors that are able to pinpoint the location of gunfire. 3. Sensor-driven decision analytics: The Internet of Things also can support longer-range, more complex human planning and decision making. The technology requirements—tremendous storage and computing resources linked with advanced software systems that generate a variety of graphical displays for analyzing data—rise accordingly. In the oil and gas industry, for instance, the next phase of exploration and development could rely on extensive sensor networks placed in the earth’s crust to produce more accurate readings of the location, structure, and dimensions of potential fields than current data-driven methods allow. The payoff: lower development costs and improved oil flows. As for retailing, some companies are studying ways to gather and process data from thousands of shoppers as they journey through stores. Sensor readings and videos note how long they linger at individual displays and record what they ultimately buy. Simulations based on this data will help to increase revenues by optimizing retail layouts. In health care, sensors and data links offer possibilities for monitoring a patient’s behavior and symptoms in real time and at relatively low cost, allowing physicians to better diagnose disease and prescribe tailored treatment regimens. Patients with chronic illnesses, for example, have been outfitted with sensors in a small number of health care trials currently under way, so that their conditions can be monitored continuously as they go about their daily activities. One such trial has enrolled patients with congestive heart failure. These patients are typically monitored only during periodic physician office visits for weight, blood pressure, and heart rate and rhythm. Sensors placed on the patient can now monitor many of these signs remotely and continuously, giving practitioners early warning of conditions that would otherwise lead to unplanned hospitalizations and expensive emergency care. Better management of congestive heart failure alone could reduce hospitalization and treatment costs by a billion dollars annually in the United States.
Automation and Control
Making data the basis for automation and control means converting the data and analysis collected through the Internet of Things into instructions that feed back through the network to actuators that in turn modify processes. Closing the loop from data to automated applications can raise productivity, as systems that adjust automatically to complex situations make many human interventions unnecessary. Early adopters are ushering in relatively basic applications that provide a fairly immediate payoff. Advanced automated systems will be adopted by organizations as these technologies develop further. 1. Process optimization: The Internet of Things is opening new frontiers for improving processes. Some industries, such as chemical production, are installing legions of sensors to bring much greater granularity to monitoring. These sensors feed data to computers, which in turn analyze them and then send signals to actuators that adjust processes—for example, by modifying ingredient mixtures, temperatures, or pressures. Sensors and actuators can also be used to change the position of a physical object as it moves down an assembly line, ensuring that it arrives at machine tools in an optimum position (small deviations in the position of work in process can jam or even damage machine tools). This improved instrumentation, multiplied hundreds of times during an entire process, allows for major reductions in waste, energy costs, and human intervention. In the pulp and paper industry, for example, the need for frequent manual temperature adjustments in lime kilns limits productivity gains. One company raised production 5 percent by using embedded temperature sensors whose data is used to automatically adjust a kiln flame’s shape and intensity. Reducing temperature variance to near zero improved product quality and eliminated the need for frequent operator intervention. 2. Optimized resource consumption: Networked sensors and automated feedback mechanisms can change usage patterns for scarce resources, including energy and water, often by enabling more dynamic pricing. Utilities such as Enel in Italy and Pacific Gas and Electric (PG&E) in the United States, for example, are deploying “smart” meters that provide residential and industrial customers with visual displays showing energy usage and the real-time costs of providing it. (The traditional residential fixed-price-per-kilowatt-hour billing masks the fact that the cost of producing energy varies substantially throughout the day.) Based on time-of-use pricing and better information residential consumers could shut down air conditioners or delay running dishwashers during peak times. Commercial customers can shift energy-intensive processes and production away from high-priced periods of peak energy demand to low-priced off-peak hours. Data centers, which are among the fastest-growing segments of global energy demand, are starting to adopt power-management techniques tied to information feedback. Power consumption is often half of a typical facility’s total lifetime cost, but most managers lack a detailed view of energy consumption patterns. Getting such a view isn’t easy, since the energy usage of servers spikes at various times, depending on workloads. Furthermore, many servers draw some power 24/7 but are used mostly at minimal capacity, since they are tied to specific operations. Manufacturers have developed sensors that monitor each server’s power use, employing software that balances computing loads and eliminates the need for underused servers and storage devices. Greenfield data centers already are adopting such technologies, which could become standard features of data center infrastructure within a few years. 3. Complex autonomous systems: The most demanding use of the Internet of Things involves the rapid, real-time sensing of unpredictable conditions and instantaneous responses guided by automated systems. This kind of machine decision making mimics human reactions, though at vastly enhanced performance levels. The automobile industry, for instance, is stepping up the development of systems that can detect imminent collisions and take evasive action. Certain basic applications, such as automatic braking systems, are available in high-end autos. The potential accident reduction savings flowing from wider deployment could surpass $100 billion annually. Some companies and research organizations are experimenting with a form of automotive autopilot for networked vehicles driven in coordinated patterns at highway speeds. This technology would reduce the number of “phantom jams” caused by small disturbances (such as suddenly illuminated brake lights) that cascade into traffic bottlenecks. Scientists in other industries are testing swarms of robots that maintain facilities or clean up toxic waste, and systems under study in the defense sector would coordinate the movements of groups of unmanned aircraft. While such autonomous systems will be challenging to develop and perfect, they promise major gains in safety, risk, and costs. These experiments could also spur fresh thinking about how to tackle tasks in inhospitable physical environments (such as deep water, wars, and contaminated areas) that are difficult or dangerous for humans.

Software to Automate Tasks
Getting all segments of the IoT to communicate and work together is key to the success of the technology rollout, and that means deploying a lot of software (and middleware) that will enable various heterogeneous devices to talk with each other and the infrastructure around them.
Remote Embedded Processing Nodes (Access to Cloud Computing)
Since there are not yet industry-wide IoT best practices agreed upon and deployed, many component providers are approaching the connection between devices and the cloud as a connection to their niche cloud, as opposed to the cloud. Some companies promote that all devices will be “dumb nodes,” with all processing and decision-making done within “their cloud.” Alternatively, some believe only minimal access to the cloud for basic Internet related services will be required, with most of the “thinking” done locally. Flexibility will be needed to optimize system-level performance. Software enables the various services the IoT will provide. Services are the means by which the IoT will address certain needs.

What’s in it for Operators?

IoT and Machine-to-machine (M2M) technology can revolutionize the way a lot of things get done. But one must address the technical complexity that is IoT and M2M development, deployment and operation. Today, IoT and M2M are simply too costly for serious deployment consideration by too many companies. The Internet of Things is likely to have a staggering impact on our daily lives and become an inherent part of areas such as electricity, transportation, industrial control, retail, utilities management, healthcare, water resources management, and petroleum. It can greatly improve productivity and lives. And unsurprisingly, its great market potential is attracting investments from governments, telecom operators, manufacturers, and industry users.
Operators, system integrators and service providers are seeking to maximize profits. Generally, operators are involved in M2M services either by leasing network capacity to independent M2M providers or by providing the services themselves, which is more profitable. As most operators now provide pipes only, profits from M2M services are low. Realistically, a central role in platform construction and standardization is the only viable way out.
A number of carriers are engaged, committed even, to being a central part of IoT and M2M rollout. Publicly they are bullish and investing to create value. But privately, they are confronting a harsh reality: The fractional average revenue per user (ARPU) in M2M compared to smartphones is 1 to 3. 1/3. For this reason alone we think M2M/ IoT might be an entirely new business, and not merely an extension of their ongoing operations. But can carriers realistically sustain profitable growth with their current strategies? Can they securely, reliably, profitably scale IoT/ M2M to a moderate degree – 10 billion nodes during the next 10 years – with their current approaches?
Perhaps the wireless infrastructure issue would be lessened if one only used smartphones, but increasingly, people are buying other types of devices with wireless capabilities; the average U.S. or Canadian consumer has 1.3 cellular connections, for example. Smartphones are the obvious leader of the pack in terms of sheer numbers— but laptop data cards, portable hotspot devices and e-book readers are eating up the wireless pie, too. Even feature phones, are nibbling away at the broadband supply.
The combination of mobile, cloud, social, big data and the “Internet of things” is driving company efforts from many different industries, and telecom operators are in a good position to take advantage of these trends. Indeed, telecom operators have already started to embrace M2M solutions.
Telefónica has stepped further into M2M to help utilities meet monitoring and supervision challenges. Telefónica has developed an integrated solution, called the Connected Metering Platform that allows both communications and utility operators to enhance smart metering deployments by integrating M2M communications and metering infrastructure management.
In Brazil, Jasper Wireless announced an agreement with Claro to connect M2M and consumer electronic devices wirelessly in the country. Under the agreement, Jasper Wireless will provide Claro Brazil with global visibility of all SIMs connected to the mobile network and self-service tools for provisioning, real-time diagnostics and usage controls.
Smart cities could be the next stage in the Internet of things. In Germany, IBM and Deutsche Telekom, the carrier behind the T-Mobile brand, are working together on creating smart city systems. The deal allows IBM to plug its data-wrangling capabilities into Deutsche Telekom’s established global M2M ecosystem.
China Mobile has developed and upgraded the Wireless M2M Protocol (WMMP) and standardized the communication protocols between GPRS terminals, the Internet of Things operation platform, and terminals' communication modules. The operator requires that all GPRS data traffic related to devices should pass through the Internet of Things operation platform to encourage terminal manufacturers to use the WMMP for product certification. China Telecom is actively pushing household appliance manufacturers to standardize terminal interfaces, and will soon expand its partnerships to other terminal sectors for broader standardization. Now the operator is leading standardization for the interfaces between the home gateway and the Internet of Things management platform and those between the home gateway and collection devices.

Top Players
This has been a breakout year for the Internet of Things industry, with many new investments, mainstream press coverage, and new product lines being created.
ARM: ARM creates sensors, controllers, and other embedded intelligence in devices.ARM’s technology designs enable the current and future IoT applications and services to become truly ubiquitous and intelligent. ARM’s comprehensive product offering includes 32-bit RISC microprocessors, graphics processors, enabling software, cell libraries, embedded memories, high-speed connectivity products, peripherals and development tools.
Atmel: Today, Atmel is right at the heart of The Internet of Things, a highly intelligent, connected world where Internet-enabled devices will outnumber people. Their technologies are fueling M2M communications and the “industrial Internet. Atmel is a worldwide leader in the design and manufacture of microcontrollers, capacitive touch solutions, advanced logic, mixed-signal, nonvolatile memory and radio frequency (RF) components.
Bosch: In the near future, more and more devices and systems will be capable of sending and receiving data automatically via the internet. According to their estimates, by the year 2015 more than six billion devices and systems will be connected to each other and exchanging data via the internet. The Internet of Things and Services (IoTS) isn’t just a distant vision of the future, however – it’s already very real and is having an impact on more than just technological developments.The Bosch Group is a leading global supplier of technology and services, active in the fields of automotive technology, energy and building technology, industrial technology, and consumer goods.
Cisco: Cisco defines the Internet of Everything (IoE) as bringing together people, process, data, and things to make networked connections more relevant and valuable than ever before-turning information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries. Cisco hardware, software, and service offerings are used to create the Internet solutions that make networks possible-providing easy access to information anywhere, at any time.
Ericsson: Ericsson has a vision of 50 billion connected devices by 2020. Included in this vision is the Networked Society where all aspects of people's lives, the operations of enterprises and society in general are impacted by the proliferation of communications. The Internet of Things will be a major cornerstone of an emerging networked society. Ericsson is the world’s leading provider of technology and services to telecom operators.
Freescale: At Freescale, the Internet of Things (IoT) is seen as billions of intelligent connections that will encompass every aspect of our lives and make the world smarter, greener and safer. Freescale believes that the biggest opportunities within the IoT will be in the transformational shift from the computing nexus to highly intelligent nodes - when intelligence massively scales, and the nodes have the power to learn, adapt and communicate. Freescale is a leader in embedded processing solutions for the automotive, consumer, industrial and networking markets. From microcontrollers and microprocessors to sensors, analog ICs and connectivity, their technologies are fueling the next great wave of innovation.
GE: New GE technology merges big iron with big data to create brilliant machines. This convergence of machine and intelligent data is known as the Industrial Internet, and it's changing the way we work. GE builds appliances, lighting, power systems and other products that help millions of homes, offices, factories and retail facilities around the world work better.
IBM: Over the past century, IBM has seen the emergence of a kind of global data field. The planet itself—natural systems, human systems, physical objects—have always generated an enormous amount of data, but until recent decades, they weren't able to hear it, to see it, to capture it. Now one can, because all of these things have been instrumented with microchips, UPC codes and other technologies. And they're all interconnected, so one can actually have access to the data. In effect, the planet has grown a central nervous system and is developing intelligence. It's becoming a much smarter planet. IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers.
Intel: The Internet of Things is transforming the world from disconnected, isolated systems to Internet-enabled devices that can network and communicate with each other and the cloud, providing the opportunity for businesses to enhance productivity and efficiency, develop new services and improve real-time decision making. Intel is working to accelerate the development and deployment of the IoT through building intelligent devices, creating systems of systems by connecting legacy devices to the cloud, and enabling end-to-end analytics. Intel Corporation designs, manufactures, and sells integrated digital technology platforms worldwide.
Texas Instruments: IoT is quickly growing with the expectation of 50 billion connected devices by 2020 to provide smart, invisible technology that works for people based on their preferences. With the industry's broadest portfolio of embedded wireless connectivity technologies, microcontrollers, processors and analog solutions, Texas Instruments offers many cloud-ready system solutions for the IoT. Texas Instruments is a global analog and digital semiconductor IC design and manufacturing company.

VC Funding for Startups

IMRSV: IMRSV aims to be an information layer for the real world. IMRSV is a Data-as-a-Service business, anonymously measuring attention and emotional reactions to what's being watched across multiple devices. IMRSV is generating revenue and has a signed contract to measure emotional response to media. Content is increasingly fragmented and people react differently. With IMRSV, creators can for the first time measure scalably and accurately how people respond when they look at products, watch movies and ads on their phone, tablet or TV. Brands and advertisers need a way to tell precisely how they react, in real time, incredibly cheaply, at scale.
TempoDB: TempoDB is the time series database service. Available as a hosted or deployed solution, TempoDB makes it possible to store and analyze the massive streams of time series data generated by connected devices and sensors that break traditional databases.
Ube: Control your lights and appliances from your smartphone - Ube (“yoo-bee”) makes lighting and appliance control easy and affordable. Their Wi-Fi enabled Smart Dimmers, Smart Plugs and Smart Outlets are competitively priced, easy to install, and provide the convenience of controlling one’s lights from their smartphone from anywhere in the world.
Building Robotics: Building Robotics is changing the way people interact with commercial buildings by developing cutting-edge software solutions that increase comfort and optimize building systems. Their main product, Comfy, is software that enables a better relationship between people and their workspaces. Comfy provides instant streams of warm or cool air to people, while using machine learning in the background to reduce energy use. It can be installed quickly, connecting to an existing building’s hardware and software, providing users with a simple web and mobile interface.
Placemeter: Placemeter uses public video feeds and computer vision algorithms to create the first ever, real time layer of data about places, streets and neighborhoods. Using proprietary computer vision algorithms, Placemeter can count the number of people that walk by a billboard or estimate how many people are in a restaurant, at a beach or park, or in a store. Placemeter can even detect speeding cars in a neighborhood. Information like weather and local events are factored in to refine predictions pertaining to these measurements.
Weaved: Weaved lets one create a secure private TCP/IP networks within the Internet for their connected devices. Packaged as Networking as a Service (NaaS) the company's solutions have been adopted by household brands and products using the solution are available in mass retailers now.
Spotnik: Spotnik makes the Internet of things simple by providing everything necessary to connect the world's devices, manage their information and build intelligent solutions.
People Power: ‘Presence’ by People Power transforms old smartphones and tablets into free WiFi video cameras, connecting people with the things that matter most to them. In addition to real-time video monitoring from anywhere in the world, users obtain motion detection alerts with videos, and expand the app organically by adding on other devices to manage the rest of their home. There are tens of millions of old, unused smartphones and tablets in the world (increasing exponentially each year) capable of running Presence.
Scout: Next-generation home security made sleek, smart and affordable, solutions from scout. Home security is a commodity and most of the 17% of the country that has security is dissatisfied with their provider. Scout is changing the game by offering a system with no long term contracts, the latest technology and a modern design that is worthy of a modern home. It's an affordable, renter-friendly solution for the other 80% of the country.
Amulyte: Amulyte is an emergency response and activity tracking system that connects seniors with their friends, family and caregivers - providing them help when they need it, freedom when they don’t. The Amulyte device, worn by seniors, uses cell networks, GPS and WiFi for indoor positioning to work anywhere. It contains a speaker and microphone to allow for 2-way voice communication via the pendant, a battery indicator light, and a help button. The Amulyte Portal is an online web app used by family members and caregivers to find location, monitor activity level and trends, check battery life and ensure everything is working.

Key Internet of Things Market Adoption Drivers

Within IoT, the technical and business perspectives merge at several levels. At the most profound level, the trends affecting IoT businesses concern, from the business perspective, digitalization of services, and from the technical perspective, cloudification of services. At the broader levels, the analysis and description of the business and physical domains, as well as the discussion concerning the ecosystems and solution lifecycles, provide a backdrop for discussing business.
Several technology trends will help shape IoT. Here are seven identified macro trends: the miniaturisation of devices, advances in RFID technologies, Internet Protocol version Six (IPv6), improvements in communication throughput and latency, real-time analytics, adoption of cloud technologies and security.
Miniaturization of Devices
IoT uses technologies to connect physical objects to the Internet. The size (and cost) of electronic components that are needed to support capabilities such as sensing, tracking and control mechanisms, play a critical role in the widespread adoption of IoT for various industry applications. The progress in the semiconductor industry has been no less than spectacular, as the industry has kept true to Moore's Law of doubling transistor density every two years.
In 2000, the state of the art was 1,000 nanometers (nm) but from 2010 to 2011, the industry shifted to commercially available System-on-Chip (SoC) chip solutions that utilise 28 nm - 45 nm lithography to achieve a 2-3 chipset package that can integrate an entire radio transceiver complete with digital signal processing, baseband microprocessors or graphic accelerators. Many applications such as remote healthcare and environmental monitoring require these integrated chipsets to be not only small but also concealable and to act as “tiny” computers to sense the physical subjects. Fortunately, the miniaturisation of devices has been taking place at lightning speed and the number of transistors manufactured per die has increased exponentially over the years. Today, wafer chip manufacturing technology is predominantly driven by planar metal oxide semiconductor field-effect transistor (MOSFET) technology. Advances in the areas of chip design and architecture have allowed semiconductor industries to reduce the size, density and cost of production of transistors. Technologies such as lithography, metrology and nanotechnology are used (and explored) to dramatically increase the number of transistors to be fabricated on a single chip. For example, semiconductor manufacturing processes have also improved from the current 32 nanometer (nm) node in 2010 to the 22nm node in late 2011, moving to 16nm by 2013 and 11 nm by 2015. Intel, in April 2012, officially launched the world’s first commercial microprocessor - “Ivy Bridge” on the 22nm wafer, using 3-D Tri-Gate technology. This 22nm wafer is capable of fitting more than 2.9 billion transistors with 37% improvements in performance and more than 50% power reduction, compared to its predecessor transistors. Just as the size of the chips is getting smaller, the costs of sensing components are also dropping to become more affordable. Gartner has forecast that most technology components such as radio, WiFi, sensors and global positioning systems (GPS), could see a drop in cost of 15% to 45% from 2010 to 2015. With the decreasing size and falling cost of technology components, organisations will see greater savings and opportunities in pursuing IOT in the next one to three years.

Radio Frequency Identification (RFID)
Radio Frequency Identification (RFID) technology is of particular importance to IoT as one of the first industrial realizations of IoT is in the use of RFID technology to track and monitor goods in the logistics and supply chain sector. RFID frequency bands range from 125 kHz (low frequency/LF) up to 5.8 Ghz/super high frequency (SHF) and the tags have at least three basic components: * The chip holds information about the object to which it is attached and transfers the data to reader wirelessly via an air interface. * The antenna allows transmission of the information to/from a reader. * The packaging encases chip and antenna, and allows the attaching of the tag to an object for identification.
Today, the one dimension bar (ID) code has made a significant contribution to the supply chain and other businesses such as asset management. Two dimension (2D) bar codes have provided a richer source of data but, once printed, are not up-datable. RFID, with its ability to permanently collect and process data in its environment, is proving to be the next technology for the identification of goods. Many industry verticals, especially in the logistics and supply chain, have been using RFID as tagging solutions to improve their tracking and monitoring processes.
Moving into the future, RFID has the potential to provide streams of data that will provide information systems with real-time, item-specific data and be flexible enough to be placed in extremely small spaces and locations, i.e., coil-on-chip technology. With technology developments in areas such as chip design, energy usage and preservation, RF technologies and manufacturing, new ways of RFID usage will emerge for applications such as automatic meter reading, remote home automation and real-time vehicle tracking.
Internet Protocol version 6 (IPv6)
The IPv4 address pool is effectively exhausted, according to industry accepted indicators. The final allocations under the existing framework have now been made, triggering the processes for the Internet Assigned Numbers Authority (IANA) to assign the final five IPv4/8 blocks, one to each of the five regional registries. With the exhaustion of the IANA pool of IPv4 addresses, no further IPv4 addresses can be issued to the regional registries that provide addresses to organisations.
IPv6 is the next Internet addressing protocol that is used to replace IPv4. With IPv6, there are approximately 3.4×1038 (340 trillion trillion trillion) unique IPv6 addresses, allowing the Internet to continue to grow and innovate. Given the huge number of connected devices (50 billion), IPv6 can potentially be used to address all these devices (and systems), eliminating the need of network address translation (NAT) and promoting end-to-end connectivity and control. These features provide seamless integration of physical objects into the Internet world.
Increasing Communication Throughput and Lower Latency
IoT relies on a pervasive communication network to allow “everything and everywhere” connectivity to occur. Over the years, network operators have been enhancing their infrastructure to support data capability and improving network throughput for their existing cell sites, transceivers, and interconnection facilities. With the addition of General Packet Radio Service (GPRS) infrastructure, Global System for Mobile (GSM) operators have largely upgraded their data services to Enhanced Data rates for GSM Evolution (EDGE). Today, most operators worldwide are deploying Universal Mobile Telecommunications System (UMTS) with High Speed Packet Access (HSPA) technology for higher throughput and low latency. HSPA, also commonly known as “3G”, has also shown us the power and potential of always-on, everyplace network connectivity that has ignited a massive wave of industry innovation that spans devices and applications.
As the technology trend shifts towards providing faster data rates and lower latency connectivity, the Third Generation Partnership Project (3GPP) standards body has developed a series of enhancements to create the “HSPA Evolution”, also referred to as “HSPA+”. HSPA Evolution represents a logical development of the Wideband Code Division Multiple Access (WCDMA) approach, and is the stepping stone to an entirely new 3GPP radio platform called 3GPP Long Term Evolution (LTE). LTE offers a number of distinct advantages such as increased performance attributes, high peak data rates, low latency and greater efficiencies in using the wireless spectrum.
Low latency makes it possible for IoT applications to query or receive quicker updates from sensor devices. LTE networks have latencies on the order of 50-75 ms which will open up new types of programming possibilities for application developers. For example, wearable computers which need interactive and real-time feedback will require moving large chunks of data to be analyzed in the cloud or back-end systems to create a seamless user experience. Higher peak data rates can support applications such as Voice over IP (VoIP) and digital video that require better quality of service (QoS). With further advancements in communication technologies such as Software Define Radio (SDR) and Long Term Evolution-Advanced (LTE-A), devices will be able to communicate with better QoS and support better access to new services with more efficient use of the radio frequency spectrum.

Real-Time Analytics
In today’s decision making process, the availability of real-time, accurate information is crucial. With the growing volume of data from connected devices, social media platforms, etc, good decision making relies heavily on advances in analytic capability technologies, to bring out the intelligence in data. Traditional analytics is performed as a back-end resource and is done with the pre-creation of metadata before the actual analytics process takes place. The modelling of the metadata depends on the analytics requirements; with new project requirements, the metadata has to be re-modelled.
New forms of analytics have emerged to remove the need to pre-model metadata, resulting in faster query and more dynamic data processing. In-memory processing is a form of analytics where detailed data is loaded into the system memory from a variety of data sources. New data is analysed and stored in the system memory to improve the relevance of the analytics content to augment the speed in decision making. Companies such as SAP, Microsoft, IBM and Teradata are building in-memory database solutions that can perform high analytical and transactional processing. Another form of real-time analytics such as streaming analytics uses complex algorithms to instantaneously process streams of event data it receives from one or more sources. Some examples for IoT applications that require streaming analytics could be road traffic data and telephone conversations.
IoT creates opportunities for analytics to be performed in real time and also allows large volumes of data to be stored for analysis at a later time.
Cloud Computing
IoT connects billions of devices and sensors to create new and innovative applications. In order to support these applications, a reliable, elastic and agile platform is essential. Cloud computing is one of the enabling platforms to support IoT.
Cloud computing is an architecture that orchestrates various technology capabilities such as multi-tenancy, automated provisioning and usage accounting while relying on the Internet and other connectivity technologies like richer Web browsers to realise the vision of computing delivered as a utility. Cloud computing is seeing growing adoption and there are three commonly deployed cloud service models namely Cloud Software as a Service (SaaS), Cloud Platform as a Service (PaaS) and Cloud Infrastructure as a Service (IaaS). For example, in IaaS, the use of hardware such as sensors and actuators can be made available to consumers as cloud resources. Consumers can set up arbitrary services and manage the hardware via cloud resource access control. PaaS can provide a platform from which to access IoT data and on which custom IoT applications (or host-acquired IoT applications) can be developed. SaaS can be provided on top of the PaaS solutions to offer the provider’s own SaaS platform for specific IoT domains. Companies such as Axeda18, ThingWorx19, DeviceWise20 are already providing software development platform to build innovative M2M and IoT applications.
Security and Privacy
Today, various encryption and authentication technologies such as Rivest Shamir Adleman (RSA) and Message Authentication Code (MAC) protect the confidentiality and authenticity of transaction data as it “transits” between networks. Encryptions such as full disk encryption (FDE) is also performed for user data “at rest” to prevent unauthorised access and data tampering.
In future, new standards and technologies should address security and privacy features for users, network, data and applications. In areas of network protocol security, IPv6 is the next generation protocol for the Internet; it contains addressing and security control information, i.e., IPSec to route packets through the Internet. In IPv4, IPSec is optional and connecting computers (peers) do not necessarily support IPsec. With IPv6, IPSec support is integrated into the protocol design and connections can be secured when communicating with other IPv6 devices. IPSec provides data confidentiality, data integrity and data authentication at the network layer, and offers various security services at the IP layer and above. These security services are, for example, access control, connectionless integrity, data origin authentication, protection against replays (a form of partial sequence integrity), confidentiality (encryption), and limited traffic flow confidentiality. Other IP-based security solutions such as Internet Key Exchange (IKEv2) and Host Identity Protocol (HIP) are also used to perform authenticated key exchanges over IPSec protocol for secure payload delivery.
At the data link layer, Extensible Authentication Protocol (EAP) is an authentication framework used to support multiple authentication methods. It runs directly on the data link layer, and supports duplicate detection and re-transmission error. In order to enable network access authentication between clients and the network infrastructure, a Protocol for carrying Authentication for Network Access (PANA) forms the network-layer transport for EAP. In EAP terms, PANA is a User Datagram Protocol (UDP)-based EAP lower layer that runs between the EAP peer and the EAP authenticator.
For data privacy, policy approaches and technical implementations exist to ensure that sensitive data is removed or replaced with realistic data (not real data). Using policy approaches, Data Protection Acts are passed by various countries such as the USA and the European Union to safeguard an individual's personal data against misuse. For technical implementations, there are Privacy Enhancing Techniques (PETs) such as anonymisation and obfuscation to de-sensitize personal data. PETs use a variety of techniques such as data substitution, data hashing and truncation to break the sensitive association of data, so that the data is no longer personally identifiable and safe to use. For example, European Network and Information Security Agency (ENISA) has proposed to approach data privacy by design22, using a “data masking” platform which uses PETs to ensure data privacy.
With the IoT’s distributed nature of embedded devices in public areas, threats coming from networks trying to spoof data access, collection and privacy controls to allow the sharing of real-time information, IoT security has to be implemented on a strong foundation built on a holistic view of security for all IoT elements at various interacting layers.

Key Internet of Things Market Adoption Hurdles

Applications for the Internet of Things are still at the promotional phase and have yet to move past enterprises. Though increasingly in demand in areas such as energy, industry, finance and security, M2M applications are mainly used in the electricity and transportation sectors. The main hurdle against large-scale commercial use of the Internet of Things is the lack of standards and a mature business model.
Standardization and Integration
Any large-scale service deployment needs to be framed within a set of standards. The Internet of Things involves many manufacturers, spans multiple industries, and differs widely in application scenarios and user requirements. Standardization has been sluggish, impacting large-scale commercial deployment of related services.
Uneven competition between different types of devices is affecting the overall quality of the applications. Terminal manufacturers and solution providers have to develop M2M applications ad hoc, which reduces efficiency. As most personal applications are standardized and customized, the expansion of M2M services to individual users will be detrimentally affected if the terminals are not standardized.
The standardization for the IoT involves the horizontal common technical layer and the vertical industry application layer. The former covers common communication protocols at, for example, the carrier level; terminal description and service discovery mechanisms; and application data switching mechanisms such as technologies based on XML, SOAP, and web services. The latter covers terminals, communication protocols, and application specifications.
Fortunately, companies are beginning to prioritize standardization and enterprises and organizations across industries need to contribute for this to be successful.
Cost Versus Usability
IoT uses technology to connect physical objects to the Internet. For IoT adoption to grow, the cost of components that are needed to support capabilities such as sensing, tracking and control mechanisms need to be relatively inexpensive in the coming years. Gartner has forecast that most technology components such as radio, WiFi, sensor and GPS, could see a drop in cost of 15% to 45% from 2010 to 2015. For organizations planning to adopt IoT, the reduction in costs of these components needs to be less than the increase in revenue margins that can be gained from a better product and service. The trend forecast by Gartner could incentivize organizations to pursue opportunities in IoT in the next one to three years.
Privacy and Security
As the adoption of IoT becomes pervasive, data that is captured and stored becomes huge. One of the main concerns that the IoT has to address is privacy. The most important challenge in convincing users to adopt emerging technologies is the protection of data and privacy. Concerns over privacy and data protection are widespread, particularly as sensors and smart tags can track user movements, habits and ongoing preferences. Invisible and constant data exchange between things and people, and between things and other things, will take place, unknown to the owners and originators of such data. IoT implementations would need to decide who controls the data and for how long. The fact that in the IoT, a lot of data flows autonomously and without human knowledge makes it very important to have authorization protocols in place to avoid the misuse of data. Moreover, protecting privacy must not be limited to technical solutions, but must encompass regulatory, market-based and socio-ethical considerations. Another area of protecting data privacy is the rising phenomenon of the “Quantified Self” where people exercise access control to their own personal data e.g. food consumed, distance travelled, personal preferences. These groups of people gather data from their daily lives and grant trusted third-party applications to access their data in exchange for benefits such as free data storage and analysis. The third-party applications or providers do not have access to the raw data or usually have commercial relationships with these consumers and hence cannot use their personal data for other purposes.
In the retail/consumer example, data collected from users can range from location data, user preferences, payment information to security parameters. This data gives insight into the lives of the users and hence, appropriate privacy and security mechanisms have to be in place to protect the use and dissemination of the data.
With new IoT applications being developed from evolving data that has been processed and filtered, IoT systems must be able to resolve the privacy settings from this evolving data and also for corresponding applications.
Different industries today use different standards to support their applications. With numerous sources of data and heterogeneous devices, the use of standard interfaces between these diverse entities becomes important. This is especially so for applications that supports cross organizational and various system boundaries.

Network Capacity Constraints
With convergences brought about by connected machines and smart mobile devices, there is an increasing demand for network infrastructure to support these data “hungry” devices with a certain level of expected QoS. New mobile applications that perform contextual-aware services may require frequent bursts of small blocks of data for updating and synchronizing. These sessions will typically occur in “rapid-fire” bursts for a few seconds or minutes with size of the payload in few kilobytes. The rapidity of these sessions will have an impact on the latency and bandwidth of the network. The issue of limited network capacity has prompted many global operators to develop initiatives that leverage technologies in unlicensed spectrum such as whitespace and increase the use of WiFi to offload mobile data traffic for wireless usage. A pervasive high quality network infrastructure will be needed to support the rapid development and deployment of IoT applications for both domestic and international markets.

Future of Internet of Things

IoT is transforming the way we work, live and play. In fact, IDC estimates that in 2020 there will be 26 times more connected things than people. And earlier this year, Wikibon forecasted that $154 billion will be spent on the “Industrial Internet” in 2020. Today IoT is affecting our day-to-day interaction with “things” around us, and even opens the door of possibilities for a more sustainable work environment. In the future, we can expect IoT to generate entirely new job roles and titles and to completely change the way we commute, communicate and collaborate.
The Internet of Things has great promise, yet business, policy, and technical challenges must be tackled before these systems are widely embraced. Early adopters will need to prove that the new sensor-driven business models create superior value. Industry groups and government regulators should study rules on data privacy and data security, particularly for uses that touch on sensitive consumer information. Legal liability frameworks for the bad decisions of automated systems will have to be established by governments, companies, and risk analysts, in consort with insurers. On the technology side, the cost of sensors and actuators must fall to levels that will spark widespread use. Networking technologies and the standards that support them must evolve to the point where data can flow freely among sensors, computers, and actuators. Software to aggregate and analyze data, as well as graphic display techniques, must improve to the point where huge volumes of data can be absorbed by human decision makers or synthesized to guide automated systems more appropriately.
Within companies, big changes in information patterns will have implications for organizational structures, as well as for the way decisions are made, operations are managed, and processes are conceived. Product development, for example, will need to reflect far greater possibilities for capturing and analyzing information.
Companies can begin taking steps now to position themselves for these changes by using the new technologies to optimize business processes in which traditional approaches have not brought satisfactory returns. Energy consumption efficiency and process optimization are good early targets. Experiments with the emerging technologies should be conducted in development labs and in small-scale pilot trials, and established companies can seek partnerships with innovative technology suppliers creating Internet-of-Things capabilities for target industries.

Coolest Internet of Things Innovations

As the Internet of Things gathers more buzz, there are a number of innovations on the horizon that may help see a huge boom:
AllJoyn: Developed by Qualcomm, just consider this the Intranet of Things: As an agnostic platform network that connects P2P, this system will smartly interconnect devices and systems without the help of the internet. Using Bluetooth or WiFi to transfer a song from car speakers to one’s home.
SmartThings: Using “smart sensors” that can be affixed in the home (or elsewhere), SmartThings connects to the mobile phone so users can trigger things like turning on lights, or even shutting off the TV etc. The ideas for applications via SmartThings seem endless.
FitBit: FitBit is an ‘activity’ sensor that helps one meet your health and weight-loss goals. It stores one’s personal data and uses it to help them meet these goals. Connect to a smart TV so that one’s programming access is restricted if they haven’t yet hit the gym that day. Or have the coffeemaker start automatically to help motivate them before a workout.
EVRYTHNG: AC unit starting to give out? How cool would it be if it recommended a repairman nearby — or even compared prices? Need a new pair of jeans — how about the favorite pair Tweeting sales for similar ones? EVERYTHNG is pushing to connect products to the web — and to fit the needs of everyday people.
Freescale: Freescale is a hush-hush product that’s swallowable. That’s right. This technology aims to monitor one from the INSIDE and then taper the body’s needs to one’s outside devices. Starting to wake up? How about if your curtains help the process by opening? Fall asleep on the couch? TV is shut off. Stomach growling? How about the phone pulling up a list of takeout items one has liked in the past. iBeacon: An invisible button is simply an area in space that is “clicked” when a person or object—in this case, a smartphone—moves into that physical space. It could be as small as a two-inch square on top of a conventional credit card reader, to enable payments, or as large as a room, which might want to know that you have entered or left so that it can turn on or off the lights. Apple seems keen on the idea of invisible buttons. While the company has been relatively quiet about the technology, it recently rolled out something called iBeacon, which allows any newer iPhone or Android phone to know its position in space with centimeter precision. You can think of iBeacon as a version of GPS that works indoors, and which is also more precise. This allows the developers using Apple’s technology to define “invisible buttons” of just about any dimensions. That Apple has made iBeacon open enough to work with third-party hardware providers like Estimote shows that Apple wants the standard to spread. Notably, the signals broadcast by any iBeacon-compatible radio (which broadcast signals known as Bluetooth Low Energy) can also be picked up by Android and Windows phones, which shows that Apple is trying to dominate a technology that could become ubiquitous across phones. This means invisible spatial buttons that could be so small that touching one’s smartphone, smartwatch or other equipped device to a surface will allow them to press that “button.” There’s nothing stopping this technology from being squeezed into something as small as a credit card, or being embedded in clothing or other discrete wearable devices like fitness sensors, wristwatches or even temporary tattoos.

Latest News

Cisco, IBM Launch Internet of Things Consortium
Microsoft readies to join the ‘Internet of Things’ with Windows on Devices
Gartner claims Internet of Things will require business model shake-up
Prepping the cloud for the internet of things
Intel chooses Atom for Edison PC to capture Internet of Things explosion
Mobile made frenemies out of everyone and the internet of things will make it worse
Growing Internet Of Things Means Growing Opportunity For Solutions Providers
Internet Of Things – Or Business Of Applications?
Internet of Things: 5 tips to monetize
The Internet of Things (IoT) Will Grow To 40 Billion Devices By 2020: Are You Ready ?

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Internet of Thing Consortium: IoTC companies build internet-connected products and services and believe in a set of principles necessary to enable our connected future.

Internet of Things: Information, networking, prospective work about the Internet of Things. But also Web 3.0, Semantic Web, EPCGlobal Networks, ubiquitous networks/computing, RFID, NFC, AUTO-ID and M2M, Cyber-Physical Systems...
The Internet of Things: This group intends to bring consultancy and forecasting on the Internet of Things together in order to synch ideas on infrastructure, services and applications.
Internet of Things, Big Data and Internet of People: Internet of Things is hot. All over the world new initiatives start to offer Internet of Things products and services, but there are many obstacles to be taken before the business case becomes realistic and successful. Also the Internet of Things will create an order of magnitude more data than social networks currently do. The number of things connected to the Internet exceeded the number of people on earth in 2008 and It is projected that by 2020, there will be 50 billion. This group will cover all these aspects.
Internet of Things IoT Conference: Internet of Things Conference is the leading IoT World Forum 2014 as m2m conference in London Barcelona Europe UK for IoT applications.
The Silent Intelligence - the Internet of Things: The purpose of this group is to bring together professionals who are interested in M2M and the Internet of Things - business executives, engineers, entrepreneurs, investors and others who would like to better understand the space and make connections
Cisco Internet of Things: The Internet of Things (IoT) is the latest chapter in how the Internet will expand with connections to physical items such as machines, devices, sensors, automobiles, cameras, discrete manufacturing, process manufacturing and more. The IoT will connect new places—manufacturing floors, energy grids, healthcare facilities and transportation systems, which will create greater productivity and efficiency, better information and insights.
Internet of Things World Forum: Information on announcements and research presented at the Internet of Things World Forum will be posted here for press and analysts attending the event in Barcelona, Spain, October 29-31, 2013.
IoT-A Internet of Things Architecture: IoT-A, the European lighthouse integrated project addressing the Internet-of-Things Architecture, proposes the creation of an architectural reference model together with the definition of an initial set of key building blocks. Together they are envisioned as crucial foundations for fostering a future Internet of Things. Using an experimental paradigm, IoT-A will combine top-down reasoning about architectural principles and design guidelines with simulation and prototyping to explore the technical consequences of architectural design choices.
IEEE Internet of Things: Join the IEEE's Internet of Things Group as science moves towards highly integrated networks of sensors and embedded systems in devices incorporated into everything from appliances to clothing. The Group will be comprised of those involved in research, implementation, application, and usage in this internet-enabled vision of our future. The groundwork is being laid now, and this Group will help you stay abreast of developments in this multi-disciplinary area. The Group involvement will ensure you receive communications of news and announcements of conferences and other opportunities for keeping at the forefront of research, development, and planning.
Industrial Internet of Things: Welcome to the Industrial Internet of Things discussion group. This group is designed to encourage dialogue regarding the emerging Industrial Internet of Things. The Industrial Internet of Things (IoT) refers to the emerging practice of connecting intelligent physical entities, such as sensors, devices, machines, assets, and products, to each other, to internet services, and to applications. Industrial companies can use information from these connected devices to lower costs, optimize processes, and transform their applications, services, or business models. The IoT concept underlies emerging solutions such as GE's Industrial Internet, IBM's Smarter Planet, and Cisco's Internet of Everything.


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