Why IoT Needs Fog Computing?

Source: vector

The Internet of Things (IoT) is one of the hottest mega-trends in technology – and for good reason , IoT deals with all the components of what we consider web 3.0 including Big Data Analytics, Cloud Computing and Mobile Computing .

The Challenge

The IoT promises to bring the connectivity to an earthly level, permeating every home, vehicle, and workplace with smart, Internet-connected devices. But as dependence on our newly connected devices increases along with the benefits and uses of a maturing technology, the reliability of the gateways that make the IoT a functional reality must increase and make uptime a near guarantee. As every appliance, light, door, piece of clothing, and every other object in your home and office become potentially Internet-enabled; The Internet of Things is poised to apply major stresses to the current internet and data center infrastructure. Gartner predicts that the IoT may include 26 billion connected units by 2020.

The popular current approach is to centralize cloud data processing in a single site, resulting in lower costs and strong application security. But with the sheer amount of input data that will be received from globally distributed sources, this central processing structure will require backup. Also most enterprise data is pushed up to the cloud, stored and analyzed, after which a decision is made and action taken. But this system isn’t efficient, to make it efficient, there is a need to process some data or some big data in IoT case in a smart way, especially if it’s sensitive data and need quick action.

To illustrate the need for smart processing of some kind of data, IDC estimates that the amount of data analyzed on devices that are physically close to the Internet of Things is approaching 40 percent, which supports the urgent need for a different approach to this need.

 

Source: Cisco

The Solution

To deal with this challenge, Fog Computing is the champion.

Fog computing allows computing, decision-making and action-taking to happen via IoT devices and only pushes relevant data to the cloud, Cisco coined the term “Fog computing “and gave a brilliant definition for Fog Computing: “The fog extends the cloud to be closer to the things that produce and act on IoT data. These devices, called fog nodes, can be deployed anywhere with a network connection: on a factory floor, on top of a power pole, alongside a railway track, in a vehicle, or on an oil rig. Any device with computing, storage, and network connectivity can be a fog node. Examples include industrial controllers, switches, routers, embedded servers, and video surveillance cameras.”

 

Source : Cisco

To understand Fog computing concept, the following actions define fog computing:

• Analyzes the most time-sensitive data at the network edge, close to where it is generated instead of sending vast amounts of IoT data to the cloud.
• Acts on IoT data in milliseconds, based on policy.
• Sends selected data to the cloud for historical analysis and longer-term storage.

Benefits of using Fog Computing

• Minimize latency
• Conserve network bandwidth
• Address security concerns at all level of the network
• Operate reliably with quick decisions
• Collect and secure wide range of data
• Move data to the best place for processing
• Lower expenses of using high computing power only when needed and less bandwidth
• Better analysis and insights of local data

Keep in mind that fog computing is not a replacement of cloud computing by any measure, it works in conjunction with cloud computing, optimizing the use of available resources. But it was the product of a need to address two challenges, real-time process and action of incoming data, and limitation of resources like bandwidth and computing power, another factor helping fog computing is the fact that it takes advantage of the distributed nature of today’s virtualized IT resources.  This improvement to the data-path hierarchy is enabled by the increased compute functionality that manufacturers are building into their edge routers and switches.

Real-Life Example:

A traffic light system in a major city is equipped with smart sensors. It is the day after the local team won a championship game and it’s the morning of the day of the big parade. A surge of traffic into the city is expected as revelers come to celebrate their team’s win. As the traffic builds, data are collected from individual traffic lights. The application developed by the city to adjust light patterns and timing is running on each edge device. The app automatically makes adjustments to light patterns in real time, at the edge, working around traffic impediments as they arise and diminish. Traffic delays are kept to a minimum, and fans spend less time in their cars and have more time to enjoy their big day.

After the parade is over, all the data collected from the traffic light system would be sent up to the cloud and analyzed, supporting predictive analysis and allowing the city to adjust and improve its traffic application’s response to future traffic anomalies. There is little value in sending a live steady stream of everyday traffic sensor data to the cloud for storage and analysis. The civic engineers have a good handle on normal traffic patterns. The relevant data is sensor information that diverges from the norm, such as the data from parade day.

The Dynamics of Fog Computing

Fog computing, thought of as a “low to the ground” extension of the cloud to nearby gateways, and proficiently provides for this need. As Gartner’s Networking Analyst, Joe Skorupa puts it: “The enormous number of devices, coupled with the sheer volume, velocity and structure of IoT data, creates challenges, particularly in the areas of security, data, storage management, servers and the data center network with real-time business processes at stake. Data center managers will need to deploy more forward-looking capacity management in these areas to be able to proactively meet the business priorities associated with IoT.”

For data handling and back-haul issues that shadow the IoT’s future, fog computing offers a functional solution. Networking equipment vendors proposing such a framework, envisions the use of routers with industrial-strength reliability, running a combination of open Linux and JVM platforms embedded with vendor’s own proprietary OS. By using open platforms, applications could be ported to IT infrastructure using a programming environment that’s familiar and supported by multiple vendors. In this way, smart edge gateways can either handle or intelligently redirect the millions of tasks coming from the myriad sensors and monitors of the IoT, transmitting only summary and exception data to the cloud proper.

Source: Cisco

Fog Computing and Smart Gateways

The success of fog computing, hinges directly on the resilience of those smart gateways directing countless tasks on an internet teeming with IoT devices. IT resilience will be a necessity for the business continuity of IoT operations, with the following task to insure that success:

• Redundancy
• Security
• Monitoring of power and cooling
• Failover solutions in place to ensure maximum uptime

According to Gartner, every hour of downtime can cost an organization up to $300,000. Speed of deployment, cost-effective scalability, and ease of management with limited resources are also chief concerns.

Conclusion

Moving the intelligent processing of data to the edge only raises the stakes for maintaining the availability of these smart gateways and their communication path to the cloud. When the IoT provides methods that allow people to manage their daily lives, from locking their homes to checking their schedules to cooking their meals, gateway downtime in the fog computing world becomes a critical issue. Additionally, resilience and failover solutions that safeguard those processes will become even more essential.

 

References

http://www.biztechmagazine.com/article/2014/08/fog-computing-keeps-data-right-where-internet-things-needs-it

http://www.datacenterknowledge.com/archives/2015/04/08/fog-computing-for-internet-of-things-needs-smarter-gateways/

http://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-overview.pdf

 

 

10 Predictions for the Future of IoT

A Google search for “Internet of Things” term reveals over 280,000,000 results, thanks to the media making the connection between the smart home wearable devices, and the connected automobile, IoT has begun to become part of the popular parlance. But that’s not the complete picture, according to Gartner’s Nick Jones, vice president and distinguished analyst “The IoT demands an extensive range of new technologies and skills that many organizations have yet to master,” he  added “A recurring theme in the IoT space is the immaturity of technologies and services and of the vendors providing them. Architecting for this immaturity and managing the risk it creates will be a key challenge for organizations exploiting the IoT. In many technology areas, lack of skills will also pose significant challenges.”

In the coming years, IoT will look completely different than it does today. IoT is a greenfield market. New players, with new business models, approaches, and solutions, can appear out of nowhere and overtake incumbents. But business is the key market. While there is talk about wearables and connected homes, the real value and immediate market for IoT is with businesses and enterprises. The adoption of IoT will be much more similar to the traditional IT diffusion model (from businesses to consumers) than the consumer-led adoption of social media and personal mobility.

The top 10 trends of IoT according to Gartner:

1.Platforms. The platform is the key to success. The “things” will get increasingly inexpensive, applications will multiply, and connectivity will cost pennies.  Keeping in mind that IoT platforms bundle many of the infrastructure components of an IoT system into a single product. The services provided by such platforms fall into three main categories:

• Low-level device control and operations such as communications, device monitoring and management, security, and firmware updates.
• IoT data acquisition, transformation and management.
• IoT application development, including event-driven logic, application programming, visualization, analytics and adapters to connect to enterprise systems.

2.Standards and Ecosystems. Gartner noted that as IoT devices proliferate, new ecosystems will emerge, and there will be “commercial and technical battles between these ecosystems” that “will dominate areas such as the smart home, the smart city and healthcare. Organizations creating products may have to develop variants to support multiple standards or ecosystems and be prepared to update products during their life span as the standards evolve and new standards and related APIs emerge,” according to Gartner. There will be a battle for IoT application mindshare. With billions of devices projected to be spewing out petabytes of data, application developers will have a field day launching thousands, or even millions, of new and cool apps. But, similar to the smartphone world, all of these apps will be fighting for mindshare, and only a few will rise to the top to be valued by businesses and consumers.

3.Event Stream Processing. According to Gartner: “Some IoT applications will generate extremely high data rates that must be analyzed in real time. Systems creating tens of thousands of events per second are common, and millions of events per second can occur in some telecom and telemetry situations. To address such requirements, distributed stream computing platforms (DSCPs) have emerged. They typically use parallel architectures to process very high-rate data streams to perform tasks such as real-time analytics and pattern identification.”

4.Operating Systems. There’s a wide range of systems out there that have been designed for specific purposes.

5.Processors and Architecture. Designing devices with an understanding of those devices’ needs will require “deep technical skills.”

6.Low-Power, Wide-Area Networks. Current solutions are proprietary, but standards will come to dominate. According to Gartner: “Traditional cellular networks don’t deliver a good combination of technical features and operational cost for those IoT applications that need wide-area coverage combined with relatively low bandwidth, good battery life, low hardware and operating cost, and high connection density. The long-term goal of a wide-area IoT network is to deliver data rates from hundreds of bits per second (bps) to tens of kilobits per second (Kbps) with nationwide coverage, a battery life of up to 10 years, an endpoint hardware cost of around $5, and support for hundreds of thousands of devices connected to a base station or its equivalent. The first low-power wide-area networks (LPWANs) were based on proprietary technologies, but in the long term emerging standards such as Narrowband IoT (NB-IoT) will likely dominate this space.”

7.Low-Power, Short-Range IoT Networks. Short-range networks connecting IT devices will be convoluted. There will not be a single common infrastructure connecting devices.

8.Device (Thing) Management. IoT things that are not ephemeral — that will be around for a while — will require management like every other device (firmware updates, software updates, etc.), and that introduces problems of scale.

9.Analytics. According to Gartner, IoT will require a new approach to analytics. “New analytic tools and algorithms are needed now, but as data volumes increase through 2021, the needs of the IoT may diverge further from traditional analytics,” according to Gartner. The currency of IoT will be “data.” But, this new currency only has value if the masses of data can be translated into insights and information which can be converted into concrete actions that will transform businesses, change people’s lives, and effect social change.

10.Security. According to Gartner, threats extend well beyond denial of sleep attacks: Those are attacks using malicious code, propagated through the Internet of Things, aimed at draining the batteries of your devices by keeping them awake. According to Gartner “The IoT introduces a wide range of new security risks and challenges to the IoT devices themselves, their platforms and operating systems, their communications, and even the systems to which they’re connected. Security technologies will be required to protect IoT devices and platforms from both information attacks and physical tampering, to encrypt their communications, and to address new challenges such as impersonating ‘things’ or denial-of-sleep attacks that drain batteries. IoT security will be complicated by the fact that many ‘things’ use simple processors and operating systems that may not support sophisticated security approaches.”

What is next?

The market is endless. It’s exciting but you need to build great software and hardware with a sophisticated backend with multiple security levels and to bring order and sophistication to data and understanding that security is an art that involves cryptography. Most companies don’t have the talent they need to develop secure products.

 

 

References:

http://www.dbta.com/BigDataQuarterly/Articles/10-Predictions-for-the-Future-of-IoT-109996.aspx

https://campustechnology.com/articles/2016/02/25/security-tops-list-of-trends-that-will-impact-the-internet-of-things.aspx

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”

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

• What is next for IoT?
• Internet of Things (IoT): Security, Privacy and Safety
• Internet of Things (IoT) : Myths and Facts
• Internet of Things (IoT): The Third Wave?
• Fog Computing is Vital for a Successful Internet of Things (IoT)
• The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits
• The Internet of Everything (IoE)

 

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

• What is next for IoT?
• Internet of Things (IoT): Security, Privacy and Safety
• Internet of Things (IoT) : Myths and Facts
• Internet of Things (IoT): More than Smart “Things”
• Internet of Things (IoT): The Third Wave?
• Fog Computing is Vital for a Successful Internet of Things (IoT)
• The Internet of Everything (IoE)

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?
• Internet of Things (IoT): Security, Privacy and Safety
• Internet of Things (IoT): More than Smart “Things”
• Internet of Things (IoT): The Third Wave?
• Fog Computing is Vital for a Successful Internet of Things (IoT)
• The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits
• The Internet of Everything (IoE)

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

• Internet of Things (IoT): Security, Privacy and Safety
• Internet of Things (IoT) : Myths and Facts
• Internet of Things (IoT): More than Smart “Things”
• Internet of Things (IoT): The Third Wave?
• Fog Computing is Vital for a Successful Internet of Things (IoT)
• The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits
• The Internet of Everything (IoE)

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

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.

Securing the Internet of Things (IoT)

The Internet of Things (IoT) as a concept is fascinating and exciting, but the key to gaining real business value from it, is effective communication between all elements of the architecture so you can deploy applications faster, process and analyze data at lightning speeds, and make decisions as soon as you can.

IoT architecture can be represented by four systems:

1. Things: These are defined as uniquely identifiable nodes, primarily sensors that communicate without human interaction using IP connectivity.
2. Gateways: These act as intermediaries between things and the cloud to provide the needed Internet connectivity, security and manageability.
3. Network infrastructure: This is comprised of routers, aggregators, gateways, repeaters and other devices that control data flow.
4. Cloud infrastructure: Cloud infrastructure contains large pools of virtualized servers and storage that are networked together.

Next-generation trends namely, Social Networks, Big Data, Cloud Computing, and Mobility, have made many things possible that weren’t just a few years ago. Add to that, the convergence of global trends and events that are fueling today’s technological advances and enabling innovation including:

• Efficiencies and cost-reduction initiatives in key vertical market
• Government incentives encouraging investment in these new technology
• Lower manufacturing costs for smart devices
• Reduced connectivity costs
• More-efficient wired and wireless communications
• Expanded and affordable mobile networks

Internet of Things (IoT) is one big winner in this entire ecosystem. IoT is creating new opportunities and providing a competitive advantage for businesses in current and new markets. It touches everything—not just the data, but how, when, where and why you collect it. The technologies that have created the Internet of Things aren’t changing the internet only, but rather change the things connected to the internet—the devices and gateways on the edge of the network that are now able to request a service or start an action without human intervention at many levels.

Because the generation and analysis of data is so essential to the IoT, consideration must be given to protecting data throughout its life cycle. Managing information at this level is complex because data will flow across many administrative boundaries with different policies and intents. Generally, data is processed or stored on edge devices that have highly limited capabilities and are vulnerable to sophisticated attacks.

Given the various technological and physical components that truly make up an IoT ecosystem, it is good to consider the IoT as a system-of-systems. The architecting of these systems that provide business value to organizations will often be a complex undertaking, as enterprise architects work to design integrated solutions that include edge devices, applications, transports, protocols, and analytics capabilities that make up a fully functioning IoT system. This complexity introduces challenges to keeping the IoT secure, and ensuring that a particular instance of the IoT cannot be used as a jumping off point to attack other enterprise information technology (IT) systems.

International Data Corporation (IDC) estimates that 90% of organizations that implement the IoT will suffer an IoT-based breach of backend IT systems by the year 2017.

 Challenges to Secure IoT Deployments

Regardless of the role your business has within the Internet of Things ecosystem— device manufacturer, solution provider, cloud provider, systems integrator, or service provider—you need to know how to get the greatest benefit from this new technology that offers such highly diverse and rapidly changing opportunities.

Handling the enormous volume of existing and projected data is daunting. Managing the inevitable complexities of connecting to a seemingly unlimited list of devices is complicated. And the goal of turning the deluge of data into valuable actions seems impossible because of the many challenges. The existing security technologies will play a role in mitigating IoT risks but they are not enough. The goal is to get data securely to the right place, at the right time, in the right format, it’s easier said than done for many reasons, Cloud Security Alliance (CSA) in a recent report listed some of the challenges:

• Many IoT Systems are poorly designed and implemented, using diverse protocols and technologies that create complex configurations.
• Lack of mature IoT technologies and business processes
• Limited guidance for lifecycle maintenance and management of IoT devices
• The IoT introduces unique physical security concerns
• IoT privacy concerns are complex and not always readily evident.
• Limited best practices available for IoT developers
• There is a lack of standards for authentication and authorization of IoT edge devices
• There are no best practices for IoT-based incident response activities.
• Audit and Logging standards are not defined for IoT components
• Restricted interfaces available IoT devices to interact with security devices and applications.
• No focus yet on identifying methods for achieving situational awareness of the security posture of an organization’s IoT assets.
• Security standards, for platform configurations, involving virtualized IoT platforms supporting multi-tenancy is immature.
• Customer demands and requirements change constantly.
• New uses for devices—as well as new devices—sprout and grow at breakneck speeds.
• Inventing and reintegrating must-have features and capabilities are expensive and take time and resources.
• The uses for Internet of Things technology are expanding and changing—often in uncharted waters.
• Developing the embedded software that provides Internet of Things value can be difficult and expensive.

Some real examples of threats and attack vectors that malicious actors could take advantage of are:

• Control systems, vehicles, and even the human body can be accessed and manipulated causing injury or worse.
• Health care providers can improperly diagnose and treat patients.
• Intruders can gain physical access to homes or commercial businesses
• Loss of vehicle control.
• Safety-critical information such as warnings of a broken gas line can go unnoticed
• Critical infrastructure damage.
• Malicious parties can steal identities and money.
• Unanticipated leakage of personal or sensitive information.
• Unauthorized tracking of people’s locations, behaviors and activities..
• Manipulation of financial transactions.
• Vandalism, theft or destruction of IoT assets.
• Ability to gain unauthorized access to IoT devices.
• Ability to impersonate IoT devices.

Dealing with the challenges and threats

Gartner predicted at its security and risk management summit in Mumbai, India this year, that more than 20% of businesses will have deployed security solutions for protecting their IoT devices and services by 2017, IoT devices and services will expand the surface area for cyber-attacks on businesses, by turning physical objects that used to be offline into online assets communicating with enterprise networks. Businesses will have to respond by broadening the scope of their security strategy to include these new online devices.

Businesses will have to tailor security to each IoT deployment according to the unique capabilities of the devices involved and the risks associated with the networks connected to those devices. BI Intelligence expects spending on solutions to secure IoT devices and systems to increase five fold over the next four years.

The Optimum Platform

 

Developing solutions for the Internet of Things requires unprecedented collaboration, coordination, and connectivity for each piece in the system, and throughout the system as a whole. All devices must work together and be integrated with all other devices, and all devices must communicate and interact seamlessly with connected systems and infrastructures. It’s possible, but it can be expensive, time consuming, and difficult.

The optimum platform for IoT can:

• Acquire and manage data to create a standards-based, scalable, and secure platform.
• Integrate and secure data to reduce cost and complexity while protecting your investment.
• Analyze data and act by extracting business value from data, and then acting on it.

Last word…

Security needs to be built in as the foundation of IoT systems, with rigorous validity checks, authentication, data verification, and all the data needs to be encrypted. At the application level, software development organizations need to be better at writing code that is stable, resilient and trustworthy, with better code development standards, training, threat analysis and testing. As systems interact with each other, it’s essential to have an agreed interoperability standard, which safe and valid. Without a solid bottom-top structure we will create more threats with every device added to the IoT. What we need is a secure and safe IoT with privacy protected, tough trade off but not impossible.