The idea of a connected world helping users to make more informed decisions is gaining ground. A smarter world where systems with sensors and local processing are connected to share information is taking hold in every single industry. This is a mix of a num-ber of concepts, smart machines, machine to machine communications, big data. Many labels have been given to this overarching idea, but the most ubiquitous is the Internet of Things (IoT) as the physical world is embedded with intelligence and humans can now collect data sets about virtually any environment around them. 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 IIoT can be characterised 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 Analog Data solutions to gain deeper insight through data and analyt-ics.

Imagine industrial systems that can adjust to their own environments or even their own health. Instead of running to failure, ma-chines 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.

THE IIOT CHALLENGE

This challenge becomes even more daunting and complex when comparing the requirements of the industrial internet to those of the consumer internet. Both involve connecting devices and systems all across the globe, but the IIoT adds stricter requirements to its local networks for latency, determinism, and bandwidth. When dealing with precision machines that can fail if timing is off by mil-lisecond, adhering to strict requirements becomes pivotal to the health and safety of the machine operators, the machines, and the business.

ADAPTABILITY, SCALABILITY

Platform-based design/open architecture/real-time ethernet

As the IIoT comes to fruition, it will be a big change for historical industrial systems. The traditional design and augmentation of industrial systems are characterised by either (1) designing a proprietary or custom end-to-end solution or (2) adding functionality by repeatedly tacking on vendor-defined black boxes. The tack-on solution can be quick to implement, but at what cost? One of the biggest advantages of the IIoT is that data is easily shared and analysed for better decision making. For example, in a vendor-defined condition monitoring solution, the data being acquired and analysed is not easily available; the system is limited to sending simple alarms to prevent catastrophic failure. Data may be available after an event to analyse and determine what went wrong, but by then, time, money, and more may have been lost. If the condition monitoring data is not continuously analysed and made available through an open, standardised interface, there is no possibility of adjusting control algorithms based on data collected or correlating the collected data to control events to improve efficiency or prevent system downtime.

The opposite is true for the end-to-end solutions. All the components and end-to-end solution can work in harmony, but the under-lying issue still remains. When an end-to-end solution is built, the communication protocols are uniform and data can be shared eas-ily. But at that point, the solution itself essentially becomes the black box due to proprietary communication protocols. As soon as an update is required, the engineer faces the dilemma of taking on a solution that may not communicate well with the whole system or of starting the process over and creating a new end-to-end solution. IIoT systems need to be adaptive and scalable through software or added functionality that easily integrates into the overall solution. When the entire system is a black box, this cannot occur. There has to be a better way to integrate disparate systems and reduce system complexity without sacrificing innovation.

Engineers and scientists still face many challenges and unknowns when implementing a comprehensive strategy using IIoT. However, there is no doubt that the ongoing design of the IIoT represents a massive business and technology opportunity for all of us. It will generate new revenue streams, improve productivity, reduce operational costs, boost competitiveness, as well as many other benefits.