Five years after the Industrial Internet of Things (IIoT) burst to corporate consciousness, much has been discussed and written about this powerful new era of linked, intelligent machines and apparatus.
The world wide web has transformed how folks communicate, what they do and how they operate together. Now, attention has shifted to doing the same for machines. For the past few years, systems programmers have focused on interconnecting sensors, edge nodes and analytics to construct smart systems, transforming operations into significant productivity environments. These associated systems make up what is called the Industrial IoT (IIoT).
This fourth industrial revolution is the most disruptive in industrial automation history, affecting businesses from healthcare to energy, transportation into manufacturing.
Not only is the pace of change accelerating, but so too are the technological leaps. Within the upcoming few years, engineers in each industry will find a way to leverage the new capabilities generated by linking machines and procedures with more powerful compute and analytics capabilities.
What is the Industrial Internet of Things (IIoT)?
Let’s start with a common definition. IIoT refers to the interrelated, automated use of machines, devices and sensors that run industrial applications.
With a strong focus on large data and machine learning, the IIoT enables businesses and enterprises to increase efficiency and reliability within their operations, together with reduced reliance on human-to-machine interactions. It also enables new business models or sales sources from useful data that is gathered and shared.
The influential Industrial Internet Consortium defines IIoT systems as: The internet of things, machines, computers and individuals, enabling smart industrial operations employing advanced data analytics for transformational business outcomes.
IoT and IIoT: What’s the Difference?
The term “Internet of Things” first surfaced in a presentation by Kevin Ashton, co-founder of MIT’s Auto-ID Lab, to Proctor & Gamble in 1999. Initial work in IoT was focused on home-based consumer applications. Keep in mind the hype generated by the earliest connected refrigerator, letting you know that it was out of eggs?
IoT is a superset of all connected applications (consumer and industrial). It is typically utilized to describe connected applications in consumer markets such as wearables, temperature control, home security systems, purchasing, travel planning applications and more. IoT has disrupted industries from entertainment to travel, shopping to personal healthcare, and has an estimated market size in the hundreds of billions of dollars, according to various market analysts.
The rapid expansion is a result of the push-pull of market forces, as the consumer demand for the convenience and services of smart, related applications is matched with corporate interest in amassing and leveraging that same data into new growth opportunities.
IIoT – industrial IoT – is a subset of IoT and focuses specifically on industrial applications such as transportation, manufacturing, energy and agriculture. Notably, IIoT has different technical requirements given its increased level of sophistication, interoperability and security requirements.
The same technology that monitors your personal fitness apparatus is entirely different from the systems needed to run advanced industrial applications such as autonomous air taxis or remote robotic surgery. The two IoT and IIoT have technical challenges, but the risks and complexities for autonomous industrial applications are inherently higher.
IIoT enablement has made great strides from cross-industry, public-private collaboration. Within the past few years, thousands of universities, companies, consortia and standards organizations have come together to work on the technical innovation necessary to make IIoT operate in a safe, scalable and reliable way.
Industrie 4.0 and IIoT
Industrie 4.0 (also referred to as Industry 4.0) was initiated by the German authorities as part of its “High-Tech Strategy 2020” in 2010. Industrie 4.0 is all about linked value chains: Industrial industries can connect and automatically integrate things and processes to form cyber physical systems. The ultimate goal of Industrie 4.0 is to increase the value in manufacturing environments and reduce waste through the use of new technologies.
From the early days of IIoT, there was a fair amount of effort made by both Industrie 4.0 and IIoT proponents to differentiate the two initiatives. After a rather exhaustive analysis, this has now given way to the consensus that there are more similarities than differences in their approaches. Today, Industrie 4.0 is often used interchangeably with the Industrial Internet of Things (IIoT). Both terms refer to linking machines along with other machines/devices and analytics so as to improve productivity and outcomes.
The Way IIoT Works?
Typical IIoT techniques need data to be shared between multiple devices and across multiple networks, from the border (sensors, remote devices and computers) into the cloud (centralized computer programs ).
This is challenging because the sheer volume of data — and of course the strict safety and security requirements — can easily overwhelm a community, particularly one that spans across remote operations. These interconnected systems need new ways to manage increased data volume, performance demands, safety risk and safety certifications.
Managing IIoT data-flow is critical to ensuring IIoT applications function as designed. A proven architecture put forward by the Industrial Internet Consortium is the databus. In contrast with a database, which manages historical data at rest, the “databus” manages data in motion.
A “databus” is a data-centric software framework that distributes and manages real-time data from the IIoT, enabling applications and devices to work together as one integrated platform. The “databus” simplifies application and integration logic. Instead of exchanging messages, software components communicate via shared and filtered data objects. Applications directly read and write the value of these data items, which are cached locally.
As previously explained, IIoT applications are data dense and require high reliability. The connectivity layer, or framework, is critical to accommodate the rapid exchange of high volume data. The Industrial Internet Consortium published the Industrial Internet Connectivity Framework (IICF) to map and clarify the confusing landscape of connectivity solutions.
It provides recommendations to help unlock data in isolated systems, enable data sharing and interoperability between previously closed elements and subsystems (brownfield) and also to accelerate the growth of new applications (greenfield) within and across industries.
The IICF defines a reference architecture for opening up data otherwise locked in a lot of domain-specific connectivity technologies utilised in IIoT systems. It utilizes gateways to a few core connectivity standards that can offer syntactic interoperability without compromising the fidelity of the functional and non-functional aspects of the domain-specific technology.
This framework recommends the databus architecture, as described above, for the peer-to-peer communication necessary for agility and volume of IIoT applications.
IIoT for Engineers, Developers and Architects
In addition to streamlining operations, IIoT will rewrite vendor relationships, redefine profitability, and re-invent shipping from surroundings to price to product. Therefore, IIoT systems cannot be created in isolation. Given the investment, they need to be designed to operate for several years, even decades.
For IIoT system engineers, architects and developers working to create these next generation systems, they need to start with the fundamental truth that their system needs to work flawlessly with the unknown. If you are a designer, your challenge is to look beyond today’s experience into a future that will be dominated by smart computing. Above all, you have to think about a system that can scale and integrate with the unidentified systems of the future.
New systems have to be based on proven IIoT standards so as to be “future proofed” and also to ensure they have the necessary interoperability, scalability and security necessary for data-driven systems.
The Industrial Internet Reference Architecture provides a standards-based architectural template and methodology for system architects to design their methods based on a Frequent framework and concepts.