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IIoT – Industrial Internet of Things: Be prepared to fail

IIoT – Industrial Internet of Things: Be prepared to fail

IIoT – or the industrial internet of things – is one of the biggest shifts in the way humans conduct busines. Connected devices have become ubiquitous – outnumbering the number of people on the planet and growing – offering unprecedented levels of data, which is fueling the Fourth Industrial Revolution.

This ability to store, analyse and implement learnings from big data is how IIoT will change the world. And it is set to completely change the way businesses operate.

With simple, affordable sensors and actuators, the most important aspects of any business can now record all the most important data. However, the real magic occurs at the processing end, as the data from various points are compared and contrasted to offer previously unimaginable levels of insight.

This will offer huge opportunities to streamline processes, vastly improving efficiency.

Perhaps the real reason why IIoT is needed is the changes that will be experienced by the consumer, with the possibility for what was once considered a one-off purchase to instead become an ongoing service.

Either way, changes are already afoot and businesses need to be ready for the impending digital shake-up.

What is IIoT?

The Industrial Internet of Things (IIoT) offers the ability to clearly see the various aspects of a manufacturing operation – from micro through to macro – as part of a whole.

By incorporating a broad suite of internet-enabled technology that is available today – from sensor-embedded devices, cloud computing, mobile technology, artificial intelligence and even robotics – IIoT is recreating manufacturing business model by streamlining efficiency across the entire business.

Take, for example, the production side of things. With sensor-embedded devices, software is able to predict far more accurately at what point a machines is set to experience a mechanical fault or failure. An alert can be sent to an engineer to service the machine before this problem arises, thus minimising downtime.

Part of the appeal, however, is that IIoT platform is not reliant on your workforce being IT wizards who can dissect reams of data or understand complex code. The reason IIoT is making such a big splash is because its insights are accessible to someone who may only have a cursory understanding of computers.

Thanks to advances in cloud computing, the big data collected by IIoT devices can be displayed on easy-to-understand interfaces, offering insights that are simple to comprehend and action.

The result is that the efficiencies that have created so many billion-dollar companies in Silicon Valley are now simple and affordable for the manufacturing industry to take advantage of.

And that means it’s an offering that’s seriously on the rise, with research by MarketsandMarkets indicating IIoT market size is set to grow from $US 64 billion in 2018 to $US 91.40 billion by 2023.

Industrial Internet of Things definition

The Industrial Internet of Things is the broad range of devices that connect to and offer insights into equipment and hardware, as well as the software and other analytics platforms used to glean and display insights into the data collected.

Not to be considered simply for ‘industrial’ use, IIoT offers advances in virtually all industries, and promises to improve efficiencies in supply chains, production and management.

The difference between IoT vs IIoT vs Industry 4.0

The Internet of Things is the broad umbrella term for connected devices – it includes devices that are specifically IIoT, but would includes consumer-focused aspects, such as smartcars, smartspeakers and fitness trackers.

IIoT is the interconnected machines, devices, software and platforms that are created and used specifically by businesses – of all descriptions – to improve their efficiency and thus profitability.

Industry 4.0 is the description of the current, global shift in manufacturing, also referred to as ‘the fourth industrial revolution’ (the first three being: mechanisation via water and steam power, mass production thanks to electricity and the assembly line, and automation as a result of computers).

While IIoT is part of Industry 4.0, it also includes implementing such principles as information transparency and decentralising decision-making.

In this regard, you might say that Industry 4.0 is the philosophy that will drive future manufacturing, whereas IIoT is the means by which it will be implemented.

Industrial IoT market size and economic impact

As stated above, there is expected to be massive growth in the IIoT sector in the coming years, with value approaching the $US 100 billion mark in the coming years.

Part of the market size will be informed by IIoT platforms – the ways the insights offered are recorded, stored and analysed – although Market Research Futures estimates this amount will make up a relatively small $US 650 million by the end of 2022.

Arguably the largest economic impact will be felt instead by the vast improvements in efficiency on offer.

As more and more businesses adopt IIoT models and practices, downtime created by malfunctioning equipment will be reduced, production lines will be more efficient as a result of hardware being able to self-report the need for an increase in stock availability, both of which will ultimately lead to lower costs and thus increased consumer demand.

IIoT Architecture: the pieces of the puzzle

While there are a number of ways that IIoT architecture can be set out, perhaps the most common and easily understood is a five-layer system.

1. Perception layer

The perception layer is where the action happens in the real world. It’s where, for example, a thermometer measures the temperature of a refrigeration unit to ensure it’s cold enough, an accelerometer measures the pace of a turbine, or a camera records footage.

This layer also involves actuators, which don’t just record data, they influence it – think a switch that can be flicked to turn a machine on or off, or a valve releasing more fuel into a system.

In essence, it’s where data is collected and influenced – and as batteries and computing power grow cheaper and smaller, it’s a layer that is expanding by the day.

2. Transport layer

The transport layer is all about transmitting data.

Using technology such as Bluetooth, 4G, NFC and the various other networks available, data is taken from the point at which it is collected and taken to the processing layer, where deeper insights can be taken from it.

The transport layer also allows for data to be communicated to the perception layer from the processing layer – thus allowing for actuators to influence their environment in real time.

3. Processing layer

iiot layers

The processing layer is where the huge levels of data are stored, analysed and go from being a series of ones and zeroes into actionable insights.

While an amount of processing can be done at the perception layer, to really make the most of the vast amounts of data from the multitude of points possible, cloud computing and processing power is required – for both storage and to provide depth of analysis from the data collected.

4. Application layer

This is the layer at which the aforementioned ones and zeroes that have become actionable insights are communicated to the user.

Three layers of data collection, transport and processing are basically useless unless said data can then be presented in a manner that is easily understood.

The application layer is where and how the data is communicated in a manner that takes into account the user – both by giving them information that they will find useful and doing so in a manner that they can follow.

5. Business layer

The business layer is the top of the system and while it is informed by the data that is fed through up the other layers, it overseas the other four, ensuring they are performing.

This is the layer at which, ultimately, the success or failure of a business will be determined, as all the data in the world is of no use unless it’s analysed and implemented successfully.

Privacy and security are also increasing concerns within IIoT and it’s at this layer such considerations are overseen.

IIoT applications – the reason for bothering

Credit to DZone

Arguably the most exciting aspet of IIoT is that it has virtually limitless potential, and the more integrated it becomes in your operation, the more benefits you will see.

Operational efficiency

Operational efficiency is one of the oldest functions of the IIoT, dating back to 1982, when students at Carnegie Mellon University installed software into a Coke vending machine that told them whether or not the machine was stocked with cold drinks.

Extrapolating this idea out, sensors can now take the guesswork out of restocking any good – as stock approaches zero, a digital notification can be sent to inform the supplier – in what is an entirely scalable concept.

It’s hardly confined to re-stocking either, with an company’s entire inventory able to be overseen and communicated using something as simple and transportable as a mobile dashboard.

Cost optimisation

When dealing with large-scale operations, overheads such as maintaining temperature and humidity, or simply keeping the lights on, can add up to huge expense.

But with IIoT devices, day-to-day costs can be minimised in real time.

Air conditioning and lighting can be rigged to run only when people are in the building – and confined to the areas they are actually required, based on sensors determining when and where human employees are. Meanwhile, a room full of servers, which needs to maintain certain atmospheric levels regardless of people present, can adjust its levels based on actual requirements – reducing costs based on seasonal and even daily weather elements. 

IIoT and M2M also offers huge potential, as machines downstream can communicate to those further up the production line their exact needs. As a result, orders can be filled in a far more individualised fashion, minimising wasted product and reducing the need for storage space.


While automation is hardly a new concept, thanks to IIoT and artificial intelligence, it’s being taken to the next level.

Rather than simply pre-programming a device – say, a robot arm – to perform a single, simple task over and over again, IIoT and machine learning are combining to improve performance and therefore capability over time.

With censors, cameras and the myriad other ways an automated device can measure its surrounds, it can learn in real time how to fix a mistake – say, for example, how to pick up a component that may have fallen over.

Where previously a simple, common error such as this could destroy hours of work, IIoT automation will correct the issue as it happens and continue as if nothing happened in the first place.

Predictive maintenance

While those who forget history are doomed to repeat it, IIoT’s applications in predictive maintenance can all but spell the end of unexpected and unnecessary downtime.

By installing sensors on the major components of vital machinery, it is easy to see when something is going awry and attend to it before it becomes a larger issue.

Even better is the ability to build your hardware a digital twin. Using the data your machines create as they go about their daily work, a digital replica can be built and run through the number of cycles required to find out at what point the physical machine will break down or cease to be efficient.

Using this digital ‘run to fail’ method of maintenance, you will still get the maximum use out of your hardware, but without suffering the issues associated with it actually failing on you.

Wearable integration

After failing to achieve cut-through with consumers, Google pivoted Glass – their augmented reality eyewear – to industry, where it has become one of the best IIoT devices.

Replacing standard eye-protection goggles, AR glasses provide opportunities for on-the-job training that recognises and interacts with its environment in real time, and can alert the wearer to potential hazards in the vicinity.

Heartrate and air-quality monitors can ensure someone is aware of what affect their immediate surrounds are having on their health and safety.

And with many wearables now able to recognise their user based on physical traits – such as height, heartbeat, ocular recognition – wearables are also the future of maintaining security and privacy.

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