AI for IIoT: How Artificial Intelligence Will Take Industrial Internet of Things to New Heights

Before we delve deep into this subject, let us hear what expert-level research has to say about both technologies:


  • Artificial Intelligence sector will become a $190 billion industry by the year 2025. (Source: Market & Market)
  • 40% of the digital transformation initiatives in 2019 are powered by AI. (Source: IDC)
  • There will be more than 64 billion IoT devices by 2025, up from about 10 billion in 2018. (Source: Business Insider)
  • Business investment will account for more than 50% of the overall IoT spending in 2020. (Source: PwC)
  • IoT has the potential to generate $4T to $11T in economic value by 2025. (Source: McKinsey Global Institute)


And we can keep on going with the many more remarkable statistics about AI and IoT, but these ones should be enough for now. The re-emergence of the decades-old technological ideas like Artificial Intelligence and the Internet of Things, at the right time and right place, has suddenly disrupted the traditional industrial norms – for the better this time. It has kickstarted a digital revolution that was only possible way back in the science fiction writings of H.G. Wells, Jules Verne, Arthur Conan Doyle, or other masterminds of Sci-Fis. It has ushered the classical Industrial Revolution of the 18th century into the Industry 4.0 of the 21st.

The early proponents and experts of both technologies were simply ecstatic about the outstanding transformational possibilities a union between AI and IoT will produce. And fast forward a couple of years into the future; here we are today witnessing the ever-increasing adoption of both AI and IoT in the industrial sphere, appropriately and shortly known as IIoT (Industrial Internet of Things). So, how IIoT differs from traditional industrial format? How AI will help to aggravate its performance more? Let us try to find out!


Industrial Evolution: The Age of IIoT & Previous Industrial Ages

We all know that the industrial revolution began back in the late 18th century in England. This age was known as Industry 1.0 when the man saw mechanical manufacturing for the very first time in history. Those primitive manufacturing machines were mostly powered by steam and water, a revered technology at that time. In that early period of the industrialization of business, Textiles were the leading most industrial sector. 1721 was the year when it all started with the world’s first water-powered silk factory at Derby, England.

Well, fast forward to two centuries ahead and we entered an age where industrial machines go electrical – welcome to the age of Industry 2.0.  While this industrial age started in the late 19th century – around 1870 – it was not so impactful in the late 19th century until the electrification of industrial machinery in the early years of 20th century powered the ideology out of England, USA, and Western Europe to other parts of the world.

The introduction of electricity in the industrial sector was really the main catalyst of Industry 2.0 which has directly led to the foundation of modern industries and operations. The remarkable efficiency and automation factor which electricity has brought into this arena dramatically enhanced the speed and demand of innovation, and within 70 years of its inception, the world was ushered into yet another industrial age which was known as Industry 3.0.

Industry 3.0 was the age when electrical power was enhanced and augmented by the coming of Information Technology (IT). Industrial efficiency boomed in this era with micro-chips such as integrated circuits and transistors making industrial machinery smarter, reliable, more efficient, and less-dependent (automated). One big innovation because of which Industry 3.0 thrived, and made possible the transformation to 4.0, is the creation of Programmable Logic Controller (PLC) in 1968. It is now that the industrial processes – manufacturing and production – can be controlled fully remotely with a programmed logical controller.

And now, the arrival of Industry 4.0, which was initially started back in the 1990s with the coming of the telecommunication and the “World Wide Web,” an age in which we are currently experiencing the remarkable revolutionary breakthroughs in the industrial sector. One of the major highlights of Industry 4.0 has been the Internet due to which we have seen great breakthroughs, such as the IIoT itself. And so, with the merging of real-world operations with the virtual ones, man and his industries are no longer restricted within physical or geographical boundaries anymore. But what role does IIoT specifically play in the age of Industry 4.0? Let us take a brief look into that before we explore the remarkable relationship between IIoT and AI.


How IIoT Makes a Difference in the Industrial Sector?

IIoT, or the Industrial Internet of Things, is the sub-branch of the Internet of Things (IoT). The term IoT was first coined by Kevin Ashton in an official presentation given at Proctor & Gambles, UK, 1999. Although the idea of adding smart sensors to physical objects initially surfaced during the 1980s, a decade before Kevin Ashton era.

The ideology is simple in the industrial sector as well: making industrial machines smarter than humans at analyzing data in real-time and forming the basis of faster and better logical decisions. A smart connected machinery system of this capability ensures the management to pick errors or inefficiencies in the system, formulate better solutions and implement them faster to save critical time, money, and business prospectuses.

Making industrial processes smarter with IIoT also brings great environmental benefits to the table: better quality control, eco-friendliness, sustainability, and better industrial waste management. IIoT also helps in supply chain management, the entire process of raw material conversion into a product and it’s upkeeping from the point of origin to the point of consumption.

In the Industrial sector, predictive maintenance and analytics are not possible without proper IIoT infrastructure, as well as enhanced asset tracking and energy management for better power utilization. IIoT manages and controls all these processes with an integrated system of smart and intelligent devices ensuring perfect maintenance and management with less dependence on active human action.

That is why no industry can survive this massive digital transformation brought on by the advent of Industry 4.0 without using the crucial help provided by the Industrial Internet of Things. But how AI and IIoT combined makes the whole technology more worthy and noticeable for industrialists? Let us find out about this core aspect in the final chapter of our narrative on AI and IIoT. If you are interested to know more in-depth about what is Industrial Internet of Things, here’s a good read on this topic from TechTarget’s IoT Agenda.


AI & IIoT: How the Combination of These Two Technologies Takes Industrial Processes to The Next Level

Now, the focal point for which we all have been waiting for thus far: How AI dramatically enhances IIoT processes, and eventually takes your industrial processes to new heights of efficiency and sustainability? In the age of Industry 4.0, industries mostly rely on operational technology (OT) and their proficiency: manufacturing, supply chain, energy management, and human resource. These operational processes can now be enhanced and taken to a whole new level of precision by combining AI and IIoT forces. How it can be done? Let us find out!

In an industrial complex, what is the most massively generated thing? It is the data. Data is everywhere today and everything today also runs on data, be it industrial processes or a home that is managed by smart monitoring devices. While smart homes may not present many complexities with management, but the industry is a different ball game. To manage this massive amount of data generated in an industrial complex, and for better management of the entire IIoT ecosystem, industrialists currently lack the skillful human resource and reliable tools to make sense of, and utilize, the big industrial data productively. And that is where artificial intelligence will come to the rescue!

AI has the power to manage itself as well as its applications independently and intelligently. This means that the utilization and optimization potential, which can be missed by the lack of skillful human resources or tools, can be sufficiently overtaken by AI. This is exclusively beneficial for OT-based industries that are using tools or software to collect, process, and analyze data generated by the industrial machines that are managed and operated in an IIoT ecosystem. These types of industrial setups face critical issues of software-legacy, which in turn greatly hinders the interoperability factor.

By integrating AI algorithms in an IIoT infrastructure, the entire mechanical apparatus can be trained to, and automated, to manage and run itself smartly and intelligently. This touches base with the core element of data-based improvement and enhancement for industrial processes since AI is the king when it comes to data analytics, especially big data. The influx of data from an IIoT ecosystem of devices into AI-powered analytical models can significantly enhance the entire industrial procedure and not just the manufacturing department as is mostly spoken of.

Plus, combining AI with other enterprise sectors also has its own set of benefits. For example, if we look outside of the core industrial playground: Fundamental features of a city which deals with everyday life such as traffic management, smart homes, shopping complexes, parks & recreation, etc., are increasingly become mechanicalized, and artificial intelligence has a role to play here with Internet of Things (IoT) – power source of a smart city.


Final Words

So, in the age of Industry 4.0, the dependence and reliability in which the combination of AI and IIoT present is too good to ignore or overlooked. This is a transformational or evolutionary stage that is mandatory for the industrial sector to pass, and the survival is assured of only those who are the most befitting ones to adapt to this massive transformational change.

4 Common Areas for Supply Chain Improvement (News)

IoT-Busines-NewsIoT Business News is a 100% online media, focusing on the business side of the Internet of Things and Machine-to-Machine markets. This article below is originally published at IoT Business News, and its addresses crucial impact of data analytics on supply chain – in 4 major ways.

Supply chains are made up of so many interconnected moving parts that, even if the chain as a whole is functioning, there are always improvements available to make business outcomes a little better. Or a lot better. Here are four common areas for supply chain improvement organizations can achieve through data analytics.


  • Finding Better Ways to Manage Inventory
  • Identifying Recalls
  • Reducing Order-to-Cycle Delivery Times
  • Managing Risk


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Road Traffic Management via IoT Technology (Infographic)

“Nearly 1.35 million people die in road crashes each year, on average 3,287 deaths a day,” WHO.


But in this “digital” age, we have an exclusive set of some revolutionary technologies that we can implement in road traffic management and dramatically decrease the ratio of road-based accidents, such as the IoT technology.


Global Big Data (Power Sector) Market Report 2019

Global Big Data (Power Sector) Market Report 2019: Microsoft, IBM, Oracle & Others

This comprehensive research report will evaluate the current market size of Big Data in the Power Sector, including with major firms in this niche.

The cities of the future, often known as the “smart” cities, will be the places where not only road traffic management, but almost every function will be monitored, controlled, and often automated by an IoT framework.


How to Secure Your IoT Devices with IMEI Lock
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How to Secure Your IoT Devices with IMEI Lock

The rapidly growing infrastructure of IoT-powered devices – in numerous forms – needs serious protection. Learn how IMEI can be helpful in this.

So, learn in this brief infographic as to how IoT will revolutionize road traffic management, increase road safety, and dramatically reduce road-based fatalities.

road traffic management via IoT - infographic

AI for IIoT: How Artificial Intelligence Will Take Industrial Internet of Things to New Heights

So, how IIoT differs from traditional industrial format? & how AI will help to aggravate its performance more? Let us try to find out in this in-depth insight.

4 Common Areas for Supply Chain Improvement (News)

Supply chain management is one of those areas that are most impacted by data & IoT analytics. Read 4 major areas of the supply chain that are most impacted.

Global Big Data (Power Sector) Market Report 2019: Microsoft, IBM, Oracle & Others

This comprehensive research report will evaluate the current market size of Big Data in the Power Sector, including with major firms in this niche.

Road Traffic Management via IoT Technology (Infographic)

Nearly 1.35 million people die in road crashes each year, on average 3,287 deaths a day, says WHO. We can increase road safety by managing traffic with smart IoT solutions.

How IoT is Revolutionizing Agricultural Sector (Infographic)

Internet of Things (IoT) has solutions not only for the industrial sector, but it can deal effectively with many agricultural challenges as well.