by Lynne Canavan, Director of Ecosystems, Real-Time Innovations (RTI)
Five-plus years after the Industrial Internet of Things (IIoT) burst into corporate consciousness – and the Industrial Internet Consortium (IIC) was launched – much has been discussed and written about this powerful new era of connected, intelligent machines and devices. Thanks to the collaborative efforts of IIC members, solid groundwork has been made on recommendations on the IIoT reference architecture, IIoT security, IIoT connectivity framework and more. Still, much of the information on IIoT is scattered across the digital landscape. This blog takes a consolidated look the ‘what,’ ‘why,’ ‘how,’ and ‘where’ of the IIoT.
Introduction to the Industrial Internet of Things (IIoT)
The Internet has transformed how people communicate, what they do and how they work together. Now, the same transformation is underway for industries. For the past few years, systems developers have focused on interconnecting sensors, edge nodes and analytics to build smart systems, transforming operations into significant productivity environments. These connected systems make up what is called the Industrial Internet of Things (IIoT).
IIoT is disruptive, affecting industries from manufacturing to healthcare, energy to transportation. Not only is the pace of change accelerating, but so too are the technological leaps. In the next few years, engineers in every industry will find a way to leverage the new capabilities generated by connecting machines and processes with more powerful compute and analytics capabilities.
What is IIoT?
The Industrial Internet Consortium defines IIoT systems as: The internet of things, machines, computers and people, enabling intelligent industrial operations using advanced data analytics for transformational business outcomes.
In more common terms, IIoT refers to the interrelated, automated use of machines, devices and sensors that run industrial applications. With a strong focus on big data and machine learning, the IIoT enables industries and enterprises to increase efficiency and reliability in their operations, with reduced reliance on human-to-machine interactions. It also enables new business models or revenue sources from useful data that is collected and shared.
For a more in-depth introduction to IIoT, please access the white papers and technical papers located in the IIC Resource hub. Another good introduction is the Rise of the Robot Overloads e-book.
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. Remember 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 used to describe connected applications in consumer markets such as wearables, temperature control, home security systems, shopping, travel planning applications and more. IoT has disrupted industries from entertainment to travel, shopping to personal healthcare, and has an estimated market size is in the hundreds of billions of dollars, according to various market analysts. The rapid growth is a result of the push-pull of market forces, as the consumer demand for the convenience and services of smart, connected applications is matched by corporate interest in collecting 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, healthcare, energy and agriculture. Notably, IIoT has different technical requirements given its increased level of complexity, interoperability and security needs. The same technology that monitors your personal fitness device is entirely different – and must be entirely different – from the systems needed to run advanced industrial applications such as autonomous air taxis or remote robotic surgery. Both 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. Over the past few years, a vast ecosystem of universities, companies, consortia and standards organizations have come together to work on the technical innovation necessary to make IIoT work in a secure, scalable and reliable way. The IIC is the largest of such consortia.
Industrie 4.0 and IIoT
Industrie 4.0 was initiated by the German government as part of its “High-Tech Strategy 2020” in 2010. Industrie 4.0 is all about connected 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.
In the early days of IIoT, there was a fair amount of discussion to differentiate the two initiatives. After a rather exhaustive analysis of Industrie 4.0 vs. IIoT, this has now given way to the consensus that there are more similarities than differences in the two approaches. Today, Industrie 4.0 is often used interchangeably with Industrial Internet of Things (IIoT). Both terms refer to connecting machines with other machines/devices and analytics in order to improve productivity and results.
Top IIoT Industries and Applications
IIoT applications are found in nearly every industry including:
- Aerospace (airports, airplanes, drones and other unmanned air vehicles)
- Agriculture (connected farms)
- Automotive (connected, semi-autonomous and autonomous vehicles)
- Energy Systems (smart grid, distributed energy resources (DERs) and renewable energy)
- Healthcare (connected healthcare, robotic surgery and medical imaging)
- Manufacturing (connected factories)
- Military (military vehicles, simulations, training and operations)
- Oil & Gas (exploration and refining)
- Smart Cities (citizen and municipal services, parking and infrastructure, etc.)
- Transportation (buses, subways, trains and Hyperloop)
IIoT also runs cross industry applications including:
- Autonomous systems
- Communications systems
- Robotics, Drones and Haptic systems
How IIoT Works?
Typical IIoT systems require data to be shared between multiple devices and across multiple networks, from the edge (sensors, remote devices and computers) to the cloud (centralized computer systems). This is challenging because the sheer volume of data – not to mention the stringent safety and security requirements – can easily overwhelm a network, particularly one that spans across remote operations. These interconnected systems require new ways to manage increased data volume, performance requirements, security risk and safety certifications.
The definitive IIoT technical resource for IIoT is the IIC’s Industrial Internet Reference Architecture. This standards-based architectural template and methodology enables IIoT system architects to design their own systems based on a common framework and concepts.
IIoT Connectivity
As previously described, 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) in 2017 to map and clarify the confusing landscape of connectivity solutions.
The IICF defines a reference architecture for opening up data that is otherwise locked in a number of domain-specific connectivity technologies used in IIoT systems. It uses gateways to one (of a handful) recommended core connectivity standards that can provide syntactic interoperability with performance.
One recommended approach is via the DDS databus, which provides a peer-to-peer communication that distributes and manages real-time data in the IIoT, enabling applications and devices to work together as one integrated system. 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 objects, which are cached locally.
IIoT for Engineers, Developers and Architects
In addition to streamlining operations, IIoT has begun to rewrite vendor relationships, redefine profitability and re-invent delivery from environment to cost to product. IIoT systems cannot be created in isolation. Given the investment, they must be designed to run for several years, even decades. From the outset, the system engineers, architects and developers working to develop these next generation systems must face the fundamental truth that their system must work flawlessly with the unknown. Their challenge is to look beyond the technology of today into a future that will be dominated by intelligent computing. Today’s IIoT systems must be flexible, scalable and must be able to integrate with the unknown systems of the future.
New systems must be based on proven IIoT standards in order 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, as mentioned above, provides a standards-based architectural template and methodology for system architects to design their systems based on a common framework and concepts.
The ROI of IIoT
IIoT streamlines and automates, leading to productivity gains, more efficient operations, cost savings and revenue-generation opportunities. Higher levels of automation and improved product quality, combined with more efficient operations through predictive maintenance, are just some of the ways that IIoT can streamline operations. From a management perspective, this will free up staff to work on higher-value tasks.
IIoT also generates new revenue streams through the data generated. The big data coming off smart machines and devices can be analyzed to add insights, advanced trouble shooting or analysis of opportunities, resulting in cost savings and profits from more efficiently run operations. Data from performance or usage can be used to form new products or services, new business models and additional revenue streams.
For example, manufacturers can create new asset-sharing models with other manufacturers, to share resources at times of under-utilization or unforeseen demand. The data can yield insights into patterns that reveal opportunities for cost savings or growth.
In a smart building where IIoT devices monitor energy consumption, the building owner can use the data to optimize efficiencies. Ensuring the windows aren’t open while the air conditioning is running or that the lights are turned off when no one is in the meeting room are now routine practices, yielding energy and cost savings. With IIoT data, the building owner can generate even more revenue by selling its data to a utility provider. That utility in turn, will aggregate this data with that from thousands of buildings to help predict and regulate energy consumption.
In short, IIoT can improve productivity and quality, while freeing up resources to help businesses to expand in new directions.
Barriers to IIoT
While the benefits of IIoT are numerous, barriers to adoption remain. Two of the biggest hurdles are security and interoperability. To understand what’s on the minds of industry executives, listen in on conversations in this short video.
When physical systems go online, there are substantial benefits, but there are also increased risks from external and even internal threats. Cyberattacks can inflict damage to the systems causing huge financial losses at best and serious injuries or even death at worst. IIoT security is something that must be designed into the IIoT system from the ground up, not as an additional protective layer after the system has been built. There are several excellent resources on security, including several published by the IIC, yet it still remains the top concern of IIoT systems.
Interoperability is another challenge. Connected IIoT systems rely on rapid, immediate and 100% accurate data exchange, across systems and across geographic areas. From the sensor to the machine to the enterprise system, data needs to be collected, analyzed, stored, retrieved and acted upon, seamlessly. Lack of interoperability and lack of standards between IIoT sensors, devices, and applications hinder the communications of IIoT systems. Progress has been made through collaborative efforts in the previously-described Industrial Internet Connectivity Framework, as well as through standards such as DDS among others. Industries can leverage these standards to mitigate risk in developing and deploying IIoT systems.
For more information including in-depth how-to’s and recommendations, please visit the IIC’s Resource Hub.
Additional Resources:
- “How to Lead in IIoT” – IIC
- IIC Accelerator Program
- IIC Industry Leadership Councils
- IIC Journal of Innovation