Internet of Things (IoT): The Third Wave?

Internet of Things (IoT): The Third Wave?

The Internet of Things (IoT) is the network of physical objects accessed through the Internet. These objects contain embedded technology to interact with internal states or the external environment. In other words, when objects can sense and communicate, it changes how and where decisions are made, and who makes them. For example Nest thermostats.
The Internet of Things (IoT) is emerging as the third wave in the development of the Internet. The 1990s’ Internet wave connected 1 billion users while the 2000s’ mobile wave connected another 2 billion. The IoT has the potential to connect 10X as many (28 billion) “things” to the Internet by 2020, ranging from bracelets to cars. Breakthroughs in the cost of sensors, processing power and bandwidth to connect devices are enabling ubiquitous connections right now. Smart products like smart watches and thermostats (Nest) are already gaining traction as stated in Goldman Sachs Global Investment Research’s report.

IoT has key attributes that distinguish it from the “regular” Internet, as captured by Goldman Sachs’s S-E-N-S-E framework: Sensing, Efficient, Networked, Specialized, Everywhere. These attributes may tilt the direction of technology development and adoption, with significant implications for Tech companies – much like the transition from the fixed to the mobile Internet shifted the center of gravity from Intel to Qualcomm or from Dell to Apple.

Source: Goldman Sachs Global Investment Research.

A number of significant technology changes have come together to enable the rise of the IoT. These include the following:

  • Cheap sensors – Sensor prices have dropped to an average 60 cents from $1.30 in the past 10 years.
  • Cheap bandwidth – The cost of bandwidth has also declined precipitously, by a factor of nearly 40X over the past 10 years.
  • Cheap processing – Similarly, processing costs have declined by nearly 60X over the past 10 years, enabling more devices to be not just connected, but smart enough to know what to do with all the new data they are generating or receiving.
  • Smartphones – Smartphones are now becoming the personal gateway to the IoT, serving as a remote control or hub for the connected home, connected car, or the health and fitness devices consumers are increasingly starting to wear.
  • Ubiquitous wireless coverage – With Wi-Fi coverage now ubiquitous, wireless connectivity is available for free or at a very low cost, given Wi-Fi utilizes unlicensed spectrum and thus does not require monthly access fees to a carrier.
  • Big data – As the IoT will by definition generate voluminous amounts of unstructured data, the availability of big data analytics is a key enabler.
  • IPv6 – Most networking equipment now supports IPv6, the newest version of the Internet Protocol (IP) standard that is intended to replace IPv4. IPv4 supports 32-bit addresses, which translates to about 4.3 billion addresses – a number that has become largely exhausted by all the connected devices globally. In contrast, IPv6 can support 128-bit addresses, translating to approximately 3.4 x 1038 addresses – an almost limitless number that can amply handle all conceivable IoT devices.

Advantages and Disadvantages of IoT

Roberto I. Belda explained it well in his article about IoT: Many smart devices like laptops, smart phones and tablets communicate with each other through the use of Wi-Fi internet technology. Transfer these technological capabilities into ordinary household gadgets like refrigerators, washing machines, microwave ovens, thermostat, door locks among others, equip these with their own computer chips, software and access to the Internet and a “smart home” now comes to life.

The Internet of Things can only work if these gadgets and devices start interacting with each other through a networked system. The AllSeen Alliance, a nonprofit organization devoted to the adoption of the Internet of Things, is facilitating to make sure that companies like Cisco, Sharp and Panasonic are manufacturing products compatible with a networked system and to ensure that these products can interact with each other.

The advantages of these highly networked and connected devices mean productive and enhanced quality of lives for people. For example, health monitoring can be rather easy with connected RX bottles and medicine cabinets. Doctors supervising patients can monitor their medicine intake as well as measure blood pressure, sugar levels and alert them when something goes wrong to their patients online.

In the aspect of energy conservation, household appliances can suggest optimal setting based on the user’s energy consumption like turning the ideal temperature just before the owner arrives home as well as turning on and off the lights whenever the owner is out on vacation just to create the impression that somebody is still left inside the house to prevent burglars from attempting to enter.

Smart refrigerators, on the other hand, can suggest food supplies that are low on inventory and needs immediate replenishment. The suggestions are based on the user’s historical purchasing behavior and trends. Wearable technology are also part of this Internet of Things, where these devices can monitor sleeping patterns, workout measurements, sugar levels, blood pressure and connecting these data to the user’s social media accounts for tracking purposes.

The most important disadvantage of the Internet of Things is with regard to the privacy and security issue. Smart home devices have the ability to devour a lot of data and information about a user. These data can include personal schedules, shopping habits, medicine intake schedule and even location of the user at any given time. If these data fall into the wrong hands great harm and damage can be done to people.

The other disadvantage is the fact that most devices are not yet ready to communicate with another brand of devices. Specific products can only be networked with their fellow products under the same brand name. It is good that AllSeen Alliance is making sure connectivity happens but the reality of a “universal remote control” for all these devices and products is still in its infantile development.

Internet of Things (IoT): More than Smart “Things”

Internet of Things (IoT): More than Smart “Things”

By 2020, experts forecast that up to 28 billion devices will be connected to the Internet with only one third of them being computers, smartphones and tablets. The remaining two thirds will be other “devices” – sensors, terminals, household appliances, thermostats, televisions, automobiles, production machinery, urban infrastructure and many other “things”, which traditionally have not been Internet enabled.

This “Internet of Things” (IoT) represents a remarkable transformation of the way in which our world will soon interact. Much like the World Wide Web connected computers to networks, and the next evolution connected people to the Internet and other people, IoT looks poised to interconnect devices, people, environments, virtual objects and machines in ways that only science fiction writers could have imagined.

In a nutshell the Internet of Things (IoT) is the convergence of connecting people, things, data and processes is transforming our life, business and everything in between.

A fair question to ask at this point is how IoT differs from machine to machine (M2M), which has been around for decades. Is IoT simply M2M with IPv6 addresses or is it really something revolutionary?

To answer this question you need to know that M2M, built on proprietary and closed systems, was designed to move data securely in real-time and mainly used for automation, instrumentation and control. It was targeted at point solutions (for example, using sensors to monitor an oil well), deployed by technology buyers, and seldom integrated with enterprise applications to help improve corporate performance.

While, IoT, on the other hand, is built with interoperability in mind and is aimed at integrating sensor/device data with analytics and enterprise applications to provide unprecedented insights into business processes, operations, and supplier and customer relationships. IoT is therefore, a “tool” that is likely to become invaluable to CEOs, CFOs and General Managers of business units. (WPC)

The technical definition of The Internet of Things (IoT) is the network of physical objects accessed through the Internet. These objects contain embedded technology to interact with internal states or the external environment. In other words, when an object can sense and communicate, it changes how and where decisions are made, and who makes them.

Source: https://ams-ix.net/

Due to the great breadth in the number of industries which have begun to be or soon will be affected by IoT, it’s not right to define IoT as a unified “market”. Rather, in an abstract sense, as a technology “wave” that will sweep across many industries at different points in time. The Internet of Things (IoT) is emerging as the third wave in the development of the Internet. The 1990s’ Internet wave connected 1 billion users while the 2000s’ mobile wave connected another 2 billion. The IoT has the potential to connect 10X as many (28 billion) “things” to the Internet by 2020, ranging from bracelets to cars.

Breakthroughs in the cost of sensors, processing power and bandwidth to connect devices are enabling ubiquitous connections right now. Smart products like smart watches and thermostats (Nest) are already gaining traction as stated in Goldman Sachs Global Investment Research’s report.

IoT has key attributes that distinguish it from the “regular” Internet, as captured by Goldman Sachs’s S-E-N-S-E framework: Sensing, Efficient, Networked, Specialized, Everywhere. These attributes may tilt the direction of technology development and adoption, with significant implications for Tech companies.

Source: Goldman Sachs Global Investment Research.

A number of significant technology changes have come together to enable the rise of the IoT. These include the following:

  • Cheap sensors – Sensor prices have dropped to an average 60 cents from $1.30 in the past 10 years.
  • Cheap bandwidth – The cost of bandwidth has also declined precipitously, by a factor of nearly 40X over the past 10 years.
  • Cheap processing – Similarly, processing costs have declined by nearly 60X over the past 10 years, enabling more devices to be not just connected, but smart enough to know what to do with all the new data they are generating or receiving.
  • Smartphones – Smartphones are now becoming the personal gateway to the IoT, serving as a remote control or hub for the connected home, connected car, or the health and fitness devices consumers are increasingly starting to wear.
  • Ubiquitous wireless coverage – With Wi-Fi coverage now ubiquitous, wireless connectivity is available for free or at a very low cost, given Wi-Fi utilizes unlicensed spectrum and thus does not require monthly access fees to a carrier.
  • Big data – As the IoT will by definition generate voluminous amounts of unstructured data, the availability of big data analytics is a key enabler.
  • IPv6 – Most networking equipment now supports IPv6, the newest version of the Internet Protocol (IP) standard that is intended to replace IPv4. IPv4 supports 32-bit addresses, which translates to about 4.3 billion addresses – a number that has become largely exhausted by all the connected devices globally. In contrast, IPv6 can support 128-bit addresses, translating to approximately 340 trillion addresses – an almost limitless number that can amply handle all conceivable IoT devices.

Industrial Internet

“The Internet of Things will give IT managers a lot to think about,” said Vernon Turner, Senior Vice President of Research at IDC. “Enterprises will have to address every IT discipline to effectively balance the deluge of data from devices that are connected to the corporate network. In addition, IoT will drive tough organizational structure changes in companies to allow innovation to be transparent to everyone, while creating new competitive business models and products.”

IoT is shaping modern business- manufacturing to marketing. A lot has been already changed since the inception of the Internet and many more will get changed with the greater Internet connectivity and reach. The global network connecting people, data and machines are transforming the modern business is also called Industrial Internet. The so called Industrial Internet had potential of $10 to $15 trillion to global GDP in next two decades.

Source: Chip Design

The “buzz” surrounding IoT has so far been more focused on the home, consumer and wearables markets, and tends to overshadow the enormous potential of Internet Protocol (IP) connected products in industrial and business/ enterprise worlds. IoT in the consumer world is effectively a greenfield opportunity with no installed base and no dominant vendors, whereas there are many examples of connected products in this arena. the definition of the “Industrial and business/enterprise Internet” for IoT purposes refers to all non-consumer applications of the Internet of Things, ranging from smart cities, smart power grids, connected health, retail, supply chain and military applications. The technologies and solutions needed for creating smart connected products and processes share many common attributes across industrial and business verticals.

 Source: Cisco (smart cities)

The IoT Value Chain

The IoT value chain is broad, extremely complex and spans many industries including those as diverse as semiconductors, industrial automation, networking, wireless and wireline operators, software vendors, security and systems integrators. Because of this complexity, very few companies will be able to successfully solve all of the associated problems or exploit the potential opportunities. (WPC)

 Source: WPC

Internet of Things Predictions

According to IDC , IoT will go through a hug growth in the coming years in many directions:

  1. IoT and the Cloud. Within the next five years, more than 90% of all IoT data will be hosted on service provider platforms as cloud computing reduces the complexity of supporting IoT “Data Blending”.
  2. IoT and security. Within two years, 90% of all IT networks will have an IoT-based security breach, although many will be considered “inconveniences.” Chief Information Security Officers (CISOs) will be forced to adopt new IoT policies.
  3. IoT at the edge. By 2018, 40% of IoT-created data will be stored, processed, analyzed, and acted upon close to, or at the edge, of the network.
  4. IoT and network capacity. Within three years, 50% of IT networks will transition from having excess capacity to handle the additional IoT devices to being network constrained with nearly 10% of sites being overwhelmed.
  5. IoT and non-traditional infrastructure. By 2017, 90% of datacenter and enterprise systems management will rapidly adopt new business models to manage non-traditional infrastructure and BYOD device categories.
  6. IoT and vertical diversification. Today, over 50% of IoT activity is centered in manufacturing, transportation, smart city, and consumer applications, but within five years all industries will have rolled out IoT initiatives.
  7. IoT and the Smart City. Competing to build innovative and sustainable smart cities, local government will represent more than 25% of all government external spending to deploy, manage, and realize the business value of the IoT by 2018.
  8. IoT and embedded systems. By 2018, 60% of IT solutions originally developed as proprietary, closed-industry solutions will become open-sourced allowing a rush of vertical-driven IoT markets to form.
  9. IoT and wearables. Within five years, 40% of wearables will have evolved into a viable consumer mass market alternative to smartphones.
  10. IoT and millennials. By 2018, 16% of the population will be Millennials and will be accelerating IoT adoption due to their reality of living in a connected world.

Challenges facing IoT

IoT is shaping human life with greater connectivity and ultimate functionality through ubiquitous networking to the Internet. It will be more personal and predictive and merge the physical world and the virtual world to create a highly personalized and often predictive connected experience. With all the promises and potential, IoT still has to resolve three major issues, unified standards for devices, privacy and security. Without the consideration of strong security at all joints of the IoT and protection of data, the progress of IoT will be hindered by litigation and social resistance. The expansion of IoT will be slow without common standards for the connected devices or sensors .

Additional Reading

 

The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits

The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits

The idea of a smarter world where systems with sensors and local processing are connected to share information is taking hold in every single industry. These systems will be connected on a global scale with users and each other to help users make more informed decisions. Many labels have been given to this overarching idea, but the most ubiquitous is the Internet of Things (IoT). The IoT includes everything from smart homes, mobile fitness devices, and connected toys to the Industrial Internet of Things (IIoT) with smart agriculture, smart cities, smart factories, and the smart grid.

The Industrial Internet of Things (IIoT) is a network of physical objects, systems, platforms and applications that contain embedded technology to communicate and share intelligence with each other, the external environment and with people. The adoption of the IIoT is being enabled by the improved availability and affordability of sensors, processors and other technologies that have helped facilitate capture of and access to real-time information.

The IIoT can be characterized as a vast number of connected industrial systems that are communicating and coordinating their data analytics and actions to improve industrial performance and benefit society as a whole. Industrial systems that interface the digital world to the physical world through sensors and actuators that solve complex control problems are commonly known as cyber-physical systems. These systems are being combined with Big Data solutions to gain deeper insight through data and analytics.

Imagine industrial systems that can adjust to their own environments or even their own health. Instead of running to failure, machines schedule their own maintenance or, better yet, adjust their control algorithms dynamically to compensate for a worn part and then communicate that data to other machines and the people who rely on those machines. By making machines smarter through local processing and communication, the IIoT could solve problems in ways that were previously inconceivable. But, as the saying goes, “If it was easy, everyone would be doing it.” As innovation grows so does the complexity, which makes the IIoT a very large challenge that no company alone can meet.

At its root, the IIoT is a vast number of connected industrial systems that communicate and coordinate their data analytics and actions to improve performance and efficiency and reduce or eliminate downtime. A classic example is industrial equipment on a factory floor that can detect minute changes in its operations, determine the probability of a component failure and then schedule maintenance of that component before its failure can cause unplanned downtime that could cost millions of dollars.

The possibilities in the industrial space are nearly limitless: smarter and more efficient factories, greener energy generation, self-regulating buildings that optimize energy consumption, cities that adjust that can adjust traffic patterns to respond to congestion and more. But, of course, implementation will be a challenge.

IIoT, IoT and M2M

The main difference between IoT and IIoT is that where consumer IoT often focuses on convenience for individual consumers, while, Industrial IoT is strongly focused on improving the efficiency, safety, and productivity of operations with a focus on return on investment. M2M is a subset of IIoT, which tends to focus very specifically on machine-to-machine communications, where IoT expands that to include machines-to-objects/people/infrastructure. The IIoT is about making machines more efficient and easier to monitor

IIoT Challenges

  • Precision
  • Adaptability and Scalability
  • Security
  • Maintenance and Updates
  • Flexibility

IIoT Requirements

  • Cloud Computing
  • Access (anywhere, anytime)
  • Security
  • Big Data Analytics
  • UX (User Experience)
  • Assets Management
  • Smart Machines

IIoT Benefits

  • Vastly improved operational efficiency (e.g., improved uptime, asset utilization) through predictive maintenance and remote management
  • The emergence of an outcome economy, fuelled by software-driven services; innovations in hardware; and the increased visibility into products, processes, customers and partners
  • New connected ecosystems, coalescing around software platforms that blur traditional industry boundaries
  • Collaboration between humans and machines, which will result in unprecedented levels of productivity and more engaging work experiences

The Future of the Industrial Internet of Things

Accenture estimates that it could add more than $10 trillion to the global economy by 2030. And that number could be even higher if companies were to take bolder actions and make greater investments in innovation and technology than they are doing today.

The good news is the Industrial Internet of Things is already here, at least among the most forward-thinking companies. The challenge is that most businesses are not ready to take the plunge. According to an Accenture survey of more than 1,400 business leaders, only one-third (36 percent) claim they fully grasp the implications of the IIoT. Just seven percent have developed a comprehensive IIoT strategy with investments to match.

One of the reasons is the as-yet limited ability to leverage machine intelligence to do more than enhance efficiencies on the factory floor and evolve to create entirely new value-added services, business models and revenue streams.

So far, businesses have made progress in applying the Industrial Internet of Things to reduce operational expenses, boost productivity or improve worker safety. Drones, for example, are being used to monitor remote pipelines, and intelligent drilling equipment can improve productivity in mines. Although these applications are valuable, they are reminiscent of the early days of the Internet, when the new technology was limited primarily to speeding up work processes. As with the Internet, however, there is more growth, innovation and value that can be derived with smart IIoT applications.

Imagine a building management company charging fees based on the energy savings it delivers to building owners. Or an airline company rewarding its engine supplier for reduced passenger delays resulting from performance data that automatically schedules maintenance and orders spare parts while a plane is still in flight. With IIoT there will be no more missing planes , information is live and up-to-date about the plane and the need for the black box will diminish. These are the kinds of product-service hybrid models that can provide new value to customers.

This transformation in business will also have dramatic implications for the workforce. Clearly, the Industrial Internet of Things will digitize some jobs that have, until now, resisted automation. But the vast majority of executives we surveyed believe that the IIoT will be a net creator of jobs. Perhaps more importantly, routine tasks will be replaced by more engaging work, as technology allows workers to do more. As the focus shifts from products to customers, knowledge-intensive work will be required to handle exceptions and tailor solutions. Virtual teams will be able to collaborate, creating and experimenting in more spontaneous and responsive environments.

The transformation in business models draws a parallel with those sparked by the emergence of electricity. It took decades to move from lighting streets to creating the electric grid. The mass assembly line soon became commonplace, requiring an entirely new set of skills, management approaches and factory design. The U.S. was the first country to seize that opportunity and create an economy-wide impact with electricity. That helped the nation develop and lead subsequent innovations that became entirely new sectors: Domestic appliances, the semiconductor industry, software and the Internet itself.

Additional Reading

Internet of Things (IoT) : Myths and Facts

Internet of Things (IoT) : Myths and Facts

Any new technology involves a certain amount of uncertainty and business risk. In the case of the Internet of Things, however, many of the risks have been exaggerated or misrepresented. While the IoT vision will take years to mature fully, the building blocks to begin this process are already in place. Key hardware and software are either available today or under development; stakeholders need to address security and privacy concerns, and collaborate to implement the open standards that will make the IoT safe, secure, reliable and interoperable, and allow the delivery of secured services as seamlessly as possible. (Push Technology)

The Internet of Things (IoT) is a concept that describes a totally interconnected world. It’s a world where devices of every shape and size are manufactured with “smart” capabilities that allow them to communicate and interact with other devices, exchange data, make autonomous decisions and perform useful tasks based on preset conditions. It’s a world where technology will make life richer, easier, safer and more comfortable.

Cisco is expecting the industry to gross over $19 trillion over the next few years. However, the problem is that these ‘things’ have myths surrounding them, some of which are impacting how organizations develop the apps to support them.

 #1 IoT and Sensors

According to Cisco, “The fundamental problem posed by the Internet of Things is that network power remains very centralized. Even in the era of the cloud, when you access data and services online you’re mostly communicating with a relative few massive datacenters that might not be located particularly close to you. That works when you’re not accessing a ton of data and when latency isn’t a problem, but it doesn’t work in the Internet of Things, where you could be doing something like monitoring traffic at every intersection in a city to more intelligently route cars and avoid gridlock. In that instance, if you had to wait for that chunk of data to be sent to a datacenter hundreds of miles away, processed, and then commands sent back to the streetlights, it would already be too late — the light would have already needed to change.”

Cisco says that the solution is to do more computing closer to the sensors (fog computing) that are gathering the data in the first place, so that the amount of data that needs to be sent to the centralized servers is minimized and the latency is mitigated. Cisco says that this data crunching capability should be put on the router. This, however, is only part of the story. Getting the right data from the right device at the right time is not just about hardware and sensors, instead it is about data intelligence. If you can understand data and only distribute what is important, at the application level, this is more powerful than any amount of hardware you throw at the problem.

This prioritization of data should be done at the application level where there is logic. Combine this with data caching at the network edge and you have a solution that reduces latency.

#2 IoT and Mobile Data

Smartphones certainly play a role in collecting some of this data and providing a user interface for accessing IoT applications, but they’re ill-suited to play a more central role. Consider the example of home automation: It hardly makes sense for critical home-monitoring and security applications, such as those that protect an elderly resident against an accident or illness, to rely upon a smartphone as its decision-making hub. What happens when that person travels and his smartphone goes into airplane mode? Does his home security get interrupted, or home electricity shut down?

Such examples make it clear that the IoT will, with a few exceptions (such as “wearable” technology and bio-monitoring systems) and some automobile-related applications, rely mostly upon dedicated gateways and remote processing solutions—not on smartphones and mobile apps.

Today, without any IoT services, more than 80% of the traffic over LTE networks goes through Wi-Fi access points. What happens when that data increases by 22 times? In addition, cellular networks and communication devices have serious drawbacks in areas such as cost, power consumption, coverage and reliability.

So, will the Internet of Things have a place for smartphones and cellular communications? Absolutely. But in terms of performance, availability, cost, bandwidth, power consumption and other key attributes, the Internet of Things will require a much more diverse and innovative variety of hardware, software and networking solutions.

#3 IoT and the volume of data

The IoT is going to produce a lot of data – an avalanche. As a result, some IoT experts believe that we will never be able to keep up with the ever-changing and ever-growing data being generated by the IoT because it’s just not possible to monitor it all. Amongst all the data that is produced by the IoT, not all of it needs to be communicated to end-user apps such as real-time operational intelligence apps. This is because a lot of the chatter generated by devices is useless and does not represent any change in state. The apps are only interested in state changes, e.g. a light being on or off, a valve being open or shut, a traffic lane being open or closed. Rather than bombarding the apps with all of the device updates, apps should only be updated when the state changes.

#4 IoT and datacenters

Some argue that the datacenter is where all the magic happens for IoT. The datacenter is absolutely an important factor for the IoT; after all this is where the data will be stored. But the myth here is that the datacenter is where the magic happens. What about the network? After all, IoT is nothing without the Internet actually supporting the distribution of information. So you might be able to store it or analyze it in a datacenter, but if the data cannot get there in the first place, is too slow in getting there or you cannot respond back in real time, there is no IoT.

#5 IoT is a future technology

The Internet of Things is simply the logical next step in an evolutionary process. The truth is that the technological building blocks of the IoT—including microcontrollers, microprocessors, environmental and other types of sensors, and short range and long range networking communications—are in wide-spread use today. They have become far more powerful, even as they get smaller and less expensive to produce.

The Internet of Things, as we define it, while evolving the existing technologies further, simply adds one additional capability—a secured service infrastructure—to this technology mix. Such a service infrastructure will support the communication and remote control capabilities that enable a wide variety of Internet-enabled devices to work together. (freescale)

#6 IoT and current interoperability standards

Everybody involved in the standards-making process knows that one size will not fit all— multiple (and sometimes overlapping) standards are a fact of life when dealing with evolving technology. At the same time, a natural pruning process will encourage stakeholders to standardize and focus on a smaller number of key standards. Standards issues pose a challenge, but these will be resolved as the standards process continues to evolve.

The Internet of Things will eventually include billions of interconnected devices. It will involve manufacturers from around the world and countless product categories. All of these devices must communicate, exchange data and perform closely coordinated tasks—and they must do so without sacrificing security or performance.

This sounds like a recipe for mass confusion. Fortunately, the building blocks to accomplish many of these tasks are already in place. Global standards bodies such as IEEE, International Society of Automation (ISA), the World Wide Web Consortium (W3C), OMA, IETF and IPSO alliance (to name a few) bring together manufacturers, technology vendors, policymakers and other interested stakeholders. As a result, while standards issues pose a short-term challenge for building the Internet of Things, the long-term process for resolving these challenges is already in place.

#7 IoT and privacy & security

Security and privacy are major concerns—and addressing these concerns is a top priority. These are legitimate concerns. New technology often carries the potential for misuse and mischief, and it’s vital to address the problem before it hinders personal privacy and security, innovation or economic growth. Manufacturers, standards organizations and policy-makers are already responding on several levels.

At the device level, security researchers are working on methods to protect embedded processors that, if compromised, would halt an attacker’s ability to intercept data or compromise networked systems. At the network level, new security protocols will be necessary to ensure end-to-end encryption and authentication of sensitive data, and since with the Internet of Things the stakes are higher than the Internet, the industry is looking at full system level security and optimization.

#8 IoT and limited vendors

Open platforms and standards will create a base for innovation from companies of all types and sizes:

  • Open hardware architectures. Open platforms are a proven way for developers and vendors to build innovative hardware with limited budgets and resources.
  • Open operating systems and software. The heterogeneous nature of the Internet of Things will require a wide variety of software and applications, from embedded operating systems to Big Data analytics and cross-platform development frameworks. Open software is extremely valuable in this context, since it gives developers and vendors the ability to adopt, extend and customize applications as they see fit—without onerous licensing fees or the risk of vendor lock-in.
  • Open standards. As we discussed earlier, open standards and interoperability are vital to building the Internet of Things. An environment where such a wide variety of devices and applications must work together simply cannot function unless it remains free from closed, proprietary standards.

Virtually all of the vendors, developers and manufacturers involved in creating the Internet of Things understand that open platforms will spur innovation and create rich opportunities for competition. Those that don’t understand this may suffer the same fate as those that promoted proprietary networking standards during the Internet era: They were sidelined and marginalized.

Conclusion

The reality of the IoT is that if you want to distribute data from the ‘thing’ across the network in real time over unreliable networks you need intelligent data distribution. To lighten the load on the network by reducing your bandwidth usage, you need to understand your data. By understanding it, you can apply intelligence to only distribute what’s relevant or what has changed. This means you send only small pieces of data across a congested network. The result is IoT apps with accurate, up-to date information, at scale, because you’ll be able to cope with the millions of devices connecting to your back end. You won’t be hit with huge pieces of data at once, shutting down your services.

Additional Reading

What is next for IoT?

What is next for IoT?

The Internet of things (IoT) is one of the most exciting trends in the recent history of technology so far. As connectivity, storage, and compute become more universal, we’re seeing an explosion of IoT solutions, from health care to public safety, all pointing towards one conclusion: The IoT is here to stay. As with any other trends in technology, it’s starting to required new generation of platforms, standards, regulations, and protocols to name few.

Gartner defines the Internet of Things as the network of physical objects that contain embedded technology (such as intelligent sensors) which can communicate, sense, or interact with internal or external systems. This can generate volumes of real-time data that can be used by organizations for a variety of applications, including smart appliances to monitoring equipment performance. The Internet of Things (IoT) is becoming so ubiquitous that ABI Research predicts that there will be more than 30 billion IP-connected devices and sensors in the world by 2020.

The rapid evolution of the IoT market has caused an explosion in the number and variety of IoT solutions. Additionally, large amounts of funding are being deployed at IoT startups. Consequently, the focus of the industry has been on manufacturing and producing the right types of hardware to enable those solutions. In that model, most IoT solution providers have been building all components of the stack, from the hardware devices to the relevant cloud services or the solutions (as indicated in diagram below). As a result, there is a lack of consistency and standards across the cloud services used by the different IoT solutions.

As the industry evolves, the need for standard models to perform common IoT backend tasks, such as processing, storage, and firmware updates, is becoming more relevant. In that new model, we are likely to see different IoT solutions work with common backend services, which will guarantee levels of interoperability, portability and manageability that are almost impossible to achieve with the current generation of IoT solutions.

Hurdles Facing IoT

While the initial generation of IoT solutions have focused on frameworks that enable communication with smart sensors, The new generation of platforms that enable backend capabilities for IoT solutions is about to emerge. But there are many obstacles to adoption; including the lack of differentiated platforms, outdated regulatory requirements, unclear business models, and most important no killer applications identified by businesses and consumers yet.

The challenges can be divided into 4 categories; Platform, Connectivity, Business Model and Killer Applications:

  • Platform : This category includes , form and design of the products (UI and UX) , analytics tools used to deal with the massive data streaming from all products in a secure way , and scalability which means wide adoption of protocols like IPv6 in all vertical and horizontal markets .
  • Connectivity: Connectivity includes all parts of the consumer’s day and night using wearables, smart cars, smart homes, and in the big scheme smart cities. From the business prospective we have connectivity using IIoT (Industrial Internet of Things) where M2M communications dominating the field.
  • Business Model: The bottom line is a big motivation for starting, investing in, and operating any business, without a sound and solid business models for IoT we will have another bubble , this model must satisfied all the requirements for all kinds of e-commerce; vertical markets, horizontal markets and consumer markets. This category is always a victim of regulatory and legal scrutiny. In a recent research piece, Goldman Sachs mapped out the IoT landscape and highlighted a few verticals that could be most impacted by it. Many of them are riddled with heavy regulations, which may impair disruption.
  • Killer Applications: Three functions needed in any killer applications, control “things”, collect “data”, analyze “data”.

Sensing the Future of IoT

The Internet of Things (IoT) is transforming the everyday physical objects that surround us into an ecosystem of information that will enrich our lives. From refrigerators to parking spaces to houses, the IoT is bringing more and more things into the digital fold every day, which will likely make the IoT a multi-trillion dollar industry in the near future. While the IoT represents the convergence of advances in miniaturization, wireless connectivity, increased data storage capacity and batteries, the IoT wouldn’t be possible without sensors. Sensors detect and measure changes in position, temperature, light, etc. and they are necessary to turn billions of objects into data-generating “things” that can report on their status, and in some cases, interact with their environment. Because sensor endpoints fundamentally enable the IoT, sensor investments are an early indicator of the IoT’s progress. And, according to PwC’s 6th Annual Digital IQ survey of nearly 1,500 business and technology executives, the IoT movement is underway. Maybe one day we will see “IoT as a Service” technology offered and used the same way we use other “as a service” technologies.

 

Additional Reading

Artificial Intelligence and Internet of Things

Artificial Intelligence and Internet of Things

The possibilities that IoT brings to the table are endless. IoT continues its run as one of the most popular technology buzzwords of the year, and now the new phase of IoT is pushing everyone to ask hard questions about the data collected by all devices and sensors of IoT.

IoT will produce a tsunami of big data, with the rapid expansion of devices and sensors connected to the Internet of Things continues, the sheer volume of data being created by them will increase to an astronomical level. This data will hold extremely valuable insights into what’s working well or what’s not.

Also, IoT will point out conflicts that arise and provide high-value insight into new business risks and opportunities as correlations and associations are made.

Examples of such IoT data:

  • Data that helps cities predict accidents and crimes
  • Data that gives doctors real-time insight into information from pacemakers or biochips
  • Data that optimize productivity across industries through predictive maintenance on equipment and machinery
  • Data that creates truly smart homes with connected appliances
  • Data that provides critical communication between self-driving cars

That’s the good news, but it’s simply impossible for humans to review and understand all of this data with traditional methods, even if they cut down the sample size, simply takes too much time. The big problem will be finding ways to analyze the deluge of performance data and information that all these devices create. Finding insights in terabytes of machine data is a real challenge, just ask a data scientist.

But in order for us to harvest the full benefits of IoT last mile (data), we need to improve:

  • Speed of big data analysis
  • Accuracy of big data analysis

The only way to keep up with this IoT-generated data and gain the hidden insights it holds is using AI (Artificial Intelligence) as the last mile of IoT.

Artificial intelligence (AI) and IoT

Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is an academic field of study which generally studies the goal of emulating human-like intelligence. John McCarthy, who coined the term in 1955, defines it as “the science and engineering of making intelligent machines”

In an IoT situation, AI can help companies take the billions of data points they have and boil them down to what’s really meaningful. The general premise is the same as in the retail applications – review and analyze the data you’ve collected to find patterns or similarities that can be learned from, so that better decisions can be made. To be able to call out potential problems, the data has to be analyzed in terms of what’s normal and what’s not. Similarities, correlations and abnormalities need to be quickly identified based on the real-time streams of data. The data collected, combined with AI, makes life easier with intelligent automation, predictive analytics and proactive intervention.

AI in IoT applications:

  • Visual big data, for example – will allow computers to gain a deeper understanding of images on the screen, with new AI applications that understand the context of images.
  • Cognitive systems will create new recipes that appeal to the user’s sense of taste, creating optimized menus for each individual, and automatically adapting to local ingredients.
  • Newer sensors will allow computers to “hear,” gathering sonic information about the user’s environment.

These are just a few promising applications of Artificial Intelligence in IoT. The potential for highly individualized services are endless and will dramatically change the way people live, for example helping Pandora to determine what other songs you may like, Amazon.com to suggest other books and movies to you and your doctor would receive notification if a certain condition was met – your heart rate increased to an unsafe level.

Challenges facing AI in IoT

  1. Compatibility
  2. Complexity
  3. Privacy/Security
  4. Safety
  5. Ethical and legal Issues
  6. Artificial Stupidity

What is next …?

Gartner predict that by 2018, 6 billion connected objects will be requesting support – meaning that strategies, technologies and processes will have to be in place to respond to them. It will become necessary to think of connected devices less as ‘things’, but more as customers and consumers of services in themselves – and as such in need of constant support. The need for AI will be more prominent at that stage under the pressure of the huge number of devices and sensors.

IoT implementation and Challenges

IoT implementation and Challenges

The Internet of Things (IoT) is the network of physical objects—devices, vehicles, buildings and other items which are embedded with electronics, software, sensors, and network connectivity, which enables these objects to collect and exchange data. Implementing this concept is not an easy task by any measure for many reasons including the complex nature of the different components of the ecosystem of IoT. To understand the gravity of this task, we will explain all the five components of IoT Implementation.

Components of IoT implementation

  • Sensors
  • Networks
  • Standards
  • Intelligent Analysis
  • Intelligent Actions

Sensors

According to (IEEE) sensors can be defined as: An electronic device that produces electrical, optical, or digital data derived from a physical condition or event. Data produced from sensors is then electronically transformed, by another device, into information (output) that is useful in decision making done by “intelligent” devices or individuals (people).

Types of Sensors: Active Sensors & Passive Sensors.

The selection of sensors greatly impacted by many factors, including:

  • Purpose (Temperature, Motion, Bio…etc.)
  • Accuracy
  • Reliability
  • Range
  • Resolution
  • Level of Intelligence (dealing with noise and interference)

The driving forces for using sensors in IoT today are new trends in technology that made sensors cheaper, smarter and smaller.

Challenges facing IoT sensors:

  • Power consumption
  • Security
  • Interoperability

Networks

The second step of this implantation is to transmit the signals collected by sensors over networks with all the different components of a typical network including routers, bridges in different topologies, including LAN, MAN and WAN. Connecting the different parts of networks to the sensors can be done by different technologies including Wi-Fi, Bluetooth, Low Power Wi-Fi , Wi-Max, regular Ethernet , Long Term Evolution (LTE) and the recent promising technology of Li-Fi (using light as a medium of communication between the different parts of a typical network including sensors)

The driving forces for wide spread network adoption in IoT can be summarized as follows:

  • High Data rate
  • Low Prices of data usage
  • Virtualization (X – Defined Network trends )
  • XaaS concept (SaaS, PaaS, and IaaS)
  • IPv6 deployment

Challenges facing network implementation in IoT

  • The enormous growth in number of connected devices
  • Availability of networks coverage
  • Security
  • Power consumption

Standards

The third stage in the implementation process includes the sum of all activities of handling, processing and storing the data collected from the sensors. This aggregation increases the value of data by increasing, the scale, scope, and frequency of data available for analysis but aggregation only achieved through the use of various standards depending on the IoT application in used.

Types of Standards

Two types of standards relevant for the aggregation process; technology standards (including network protocols, communication protocols, and data-aggregation standards) and regulatory standards (related to security and privacy of data, among other issues).

Technology Standards

  • Network Protocols (e.g.: Wi-Fi)
  • Communications Protocols (e.g.: HTTP)
  • Data aggregation standards (e.g.: Extraction, Transformation, Loading (ETL))

Regulatory Standards

Set and administrated by government agencies like FTC, for example Fair Information Practice Principles (FIPP) and US Health Insurance Portability and Accountability Act (HIPAA) just to mention few.

Challenges facing the adoptions of standards within IoT

  • Standard for handling unstructured data: Structured data are stored in relational databases and queried through SQL. Unstructured data are stored in different types of noSQL databases without a standard querying approach.
  • Security and privacy issues: There is a need for clear guidelines on the retention, use, and security of the data as well as metadata (the data that describe other data).
  • Regulatory standards for data markets: Data brokers are companies that sell data collected from various sources. Even though data appear to be the currency of the IoT, there is lack of transparency about, who gets access to data and how those data are used to develop products or services and sold to advertisers and third parties.
  • Technical skills to leverage newer aggregation tools: Companies that are keen on leveraging big-data tools often face a shortage of talent to plan, execute, and maintain systems.

Intelligent Analysis

The fourth stage in IoT implementation is extracting insight from data for analysis, Analysis is driven by cognitive technologies and the accompanying models that facilitate the use of cognitive technologies.

With advances in cognitive technologies’ ability to process varied forms of information, vision and voice have also become usable. Below is a list of selected cognitive technologies that are experiencing increasing adoption and can be deployed for predictive and prescriptive analytics:

  • Computer vision refers to computers’ ability to identify objects, scenes, and activities in images
  • Natural-language processing refers to computers’ ability to work with text the way humans do, extracting meaning from text or even generating text that is
  • Speech recognition focuses on accurately transcribing human speech

Factors driving adoption intelligent analytics within the IoT

  • Artificial intelligence models can be improved with large data sets that are more readily avail- able than ever before, thanks to the lower storage
  • Growth in crowdsourcing and open- source analytics software: Cloud-based crowdsourcing services are leading to new algorithms and improvements in existing ones at an unprecedented
  • Real-time data processing and analysis: Analytics tools such as complex event processing (CEP) enable processing and analysis of data on a real-time or a near-real-time basis, driving timely decision making and action

 Challenges facing the adoptions of intelligent analytics within IoT

  • Inaccurate analysis due to flaws in the data and/or model: A lack of data or presence of outliers may lead to false positives or false negatives, thus exposing various algorithmic limitations
  • Legacy systems’ ability to analyze unstructured data: Legacy systems are well suited to handle structured data; unfortunately, most IoT/business interactions generate unstructured data
  • Legacy systems’ ability to manage real- time data: Traditional analytics software generally works on batch-oriented processing, wherein all the data are loaded in a batch and then analyzed

Intelligent Actions

Intelligent actions can be expressed as M2M and M2H interfaces for example with all the advancement in UI and UX technologies.

Factors driving adoption of intelligent actions within the IoT

  • Lower machine prices
  • Improved machine functionality
  • Machines “influencing” human actions through behavioral-science rationale
  • Deep Learning tools

 Challenges facing the adoption of intelligent actions within IoT

  • Machines’ actions in unpredictable situations
  • Information security and privacy
  • Machine interoperability
  • Mean-reverting human behaviors
  • Slow adoption of new technologies

The Internet of Things (IoT) is an ecosystem of ever-increasing complexity, it’s the next weave of innovation that will humanize every object in our life , which is the next level to automating every object in our life . Convergence of technologies will make IoT implementation much easier and faster, which in turn will improve many aspects of our life at home and at work and in between.