Industrial IoT: Where Two Worlds Collide
Russell Fowler, a long-standing associate with a background in traditional IT roles and a passionate advocate of sustainable IT, shares insights into the challenges and opportunities of integrating IT with the historically distinct realm of OT. “Industrial IoT: Where Two Worlds Collide” delves into the convergence of Operational Technology (OT) and Information Technology (IT) within engineering and asset-focused organisations.
I’m not an engineer, I’ve spent most of my career in traditional IT roles, but I’ve done a lot of work in engineering & asset-focused organisations which represents a fascinating collision of two quite different worlds. Projects that bridge these realms of Operational Technology (OT) and Information Technology (IT) can be greatly affected by how we approach them, and these projects are more and more common as there is a gradual technology convergence and a drive to ‘digitise’ industrial processes. This journey through the convergence of OT and IT has been an eye-opener, revealing not just the technical intricacies but the human elements—how we communicate, how we perceive technology, and how we work together. It's a constant learning experience, one that underscores the need for a shared language and understanding as we navigate the future of industrial innovation.
As an example of the type of challenge that language and jargon can throw up, I was working on a project that was trying to get some sensor data out of an RTU connected to a SCADA system. The guy I was working with kept talking about a 'data diode.' Now, I've been around the block a few times, but this term had me scratching my head. After dancing around the subject for a bit, too embarrassed to show my ignorance, I finally bit the bullet and asked. It turns out, that a 'data diode' is just an engineering term that had been adopted to describe a firewall designed to only let data through in one direction. Who knew? Well, apparently, everyone but me! It was a clear example of how the jargon we get so comfortable within our own worlds can sound like a foreign language to someone else.
The historical technological variations between OT and IT are not just about the hardware and software; they're about how each field views and uses technology. On the OT side, you've got systems designed for longevity and reliability. We're talking about heavy-duty equipment that's expected to run 24/7, often for decades, under harsh conditions. The communication protocols here, like Modbus, are tried and tested, built for specific, unchanging tasks. It's a world where "if it ain't broke, don't fix it" isn't just a saying—it's a way of life.
Switching over to the realm of IT, and it's like stepping into a different universe. In comparison, innovation races forward at breakneck speed. We're all about the latest and greatest—faster processors, cloud computing, and comms protocols that make data sharing as easy as sending a tweet. In IT, change isn't just expected; it's celebrated. But this fast-paced evolution can be a double-edged sword, especially when you're trying to integrate with OT systems that view the "latest update" with a healthy dose of scepticism.
In navigating between these worlds, I've learned that it's not just about making two systems talk to each other. It's about establishing a dialogue between two very different cultures, each with its own language, priorities, and ways of working. If done successfully, the potential upsides can be enormous. Not only for operational efficiency but for sparking innovation and ideas we haven't even dreamed of yet.
As some of you know, IoT has become an area of focus for me in the last few years and it is a technology area that embodies the collision of IT and OT worlds. On one hand, you have IT pushing for cloud-based analytics and machine learning, eager to mine the vast data lakes generated by OT equipment for insights that can drive efficiency and innovation. On the other, OT is cautiously opening up to these possibilities, while fiercely guarding the reliability and security of their systems. It's a dance of give-and-take, where both sides are still figuring out the steps. The issue of ownership and responsibility for these integrated systems is a hot topic. IT has decades of experience managing data and networks, but bringing OT's critical infrastructure into this fold is a new frontier for many.
Cyber security is a field where both OT and IT have much to learn from each other. OT's approach to security has traditionally been about securing the perimeter, keeping threats at arm's length, air gapping systems from threats. IT, meanwhile, is moving towards a "zero trust" model, where security is not about the perimeter but ensuring the safety of every interaction within and between networks and systems disparately hosted across on-premise and multiple clouds. Operational networks, especially those adhering to the Purdue model, are structured to maintain a clear hierarchy between different layers of control and operation. This structure is crucial for maintaining integrity and security in OT environments. However, the push towards IIoT (Industrial IoT) blurs these lines, as we try to connect these well-defined, isolated layers directly to the vast, unpredictable world of the internet and the cloud, lured by real-time data analytics, and the promise of operational efficiency. It's a delicate balancing act, navigating between the agility IT promises and the rock-solid reliability OT demands.
Industrial technology assets can have very long lifecycles, where some pieces of equipment are expected to keep chugging along for 40 years or more, designed in an era when the cutting edge of technology was a fax machine. Now, we're trying to retrofit these ageing titans with smart sensors and connect them to sleek, cloud-based analytics platforms. Newer industrial assets are being rolled out into this landscape that have fully integrated sensors with their own ecosystem of control and analytics software. So designing new IIoT solutions can quickly become a complex and fractured affair. There's also a whole marketplace of vendors out there, each with their own idea of what IIoT should look like. Some are old-school OT giants who've been in the game since before the internet was a thing, boasting about the ruggedness and reliability of their hardware and the engineering expertise to build sophisticated, highly precise, and innovative sensors. Others are IT upstarts, fluent in the language of the cloud, big data, and machine learning, promising to turn your data into gold. The trick? Finding the sweet spot where these worlds meet, where the robustness and engineering expertise of OT meets the innovation of IT. In my experience, it's rare to find a single vendor who speaks both languages fluently. Many vendors are also interested in selling end-to-end solutions that are great for individual use cases but with so many use cases you can end up with dozens of siloed systems. Getting tied into proprietary systems or offerings is an easy trap to fall into.
Delving deeper into the IIoT domain, we encounter the pivotal role of data utilisation which is a bit like opening Pandora's box—once you start collecting data, there's no going back. But here's the kicker: data, in its raw form, is just numbers and stats. The real magic happens when you start to analyse this data, turning it into actionable insights, the interpretation of this data requires deep expertise on the assets that you’re measuring. This is where the worlds of IT and OT blend further, bringing about a transformation that can redefine business processes. For instance, predictive maintenance, a concept that was once more theoretical than practical for many, becomes a tangible outcome with the right data analytics. Suddenly, you're not just fixing machines when they break down; you're preventing the breakdowns before they happen, based on data trends and predictive modelling. It's a game-changer, but it requires a shift not just in technology, but in business processes and working practices.
The skill sets required for deep data analytics and the organisational changes and expertise needed to act on these insights often don't reside within the same team—or even the same department. Bridging this gap is essential, requiring a concerted effort to bring engineers, operational managers, and data scientists into a cohesive collaborative group. It's a bit like trying to conduct an orchestra where the musicians have never seen the score before. Everyone needs to learn not just their own part, but also how it fits into the larger symphony of the organisation's goals.
When it comes to the nuts and bolts of IIoT deployment, the technological considerations are as diverse as they are complex. Edge processing, for example, has emerged as a critical capability, allowing for data to be processed closer to where it's generated, thereby reducing latency and bandwidth use. This is especially crucial in industrial settings, where decisions often need to be made in real-time. Then there's the challenge of connectivity in environments that are, to put it mildly, not Wi-Fi friendly. The solution? A toolbox filled with every connectivity option imaginable, from traditional wired connections to LPWAN and even private 5G networks. Each technology brings its own set of advantages and constraints, and choosing the right mix is more art than science and there are always trade-offs. It's about finding a balance between technological capabilities and the harsh realities of industrial environments.
Navigating these technological and organisational choppy waters is no small feat. It requires a willingness to experiment, to fail fast, and to learn faster. Integrating IIoT into traditional industrial settings is fraught with challenges, but it's also filled with opportunities for those willing to embrace the change. As I reflect on my experiences, I'm reminded that at the heart of this transformation is not just technology, but people—those willing to bridge gaps, translate between languages, and to forge a new path forward. A key lesson emerges: the importance of respecting both worlds equally. It's been a narrative not just about the technology itself but about the people and processes that drive it.
In closing, as we forge ahead in this age of digital transformation, let's remember that the integration of IIoT into our industrial landscapes is not just a technical challenge but a human one. The technology will continue to evolve, offering new opportunities and solutions. However, the enduring success of these initiatives will depend on our ability to navigate the complexities of human collaboration and process adaptation. Embracing this holistic approach—valuing people and process as much as technology—is the key to unlocking the full potential of IIoT and driving meaningful, lasting change in the industrial sector.
RUSSELL FOWLER
Platform Smart Associate
Founder of GreenFuture Technology Consulting
LinkedIn
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