The Industrial Internet of Things (IIoT)

Out of the hype cycle and moving steadily toward maturity, the industrial internet of things, also known as IIoT, represents a seismic shift in the industrial landscape, unlike anything we’ve seen since, well, the last industrial revolution.

Sure, the tech innovations of the past few decades have dramatically changed how we work. For instance, WiFi, laptops, smartphones, and cloud-based tools opened access to constant connectivity, more accurate data, and the ability to work from anywhere.

The industrial IoT stands to overhaul industrial operations completely. Organizations can now capture, process, and analyze data from previously untapped sources like production equipment, an entire fleet’s worth of tires, supply chain activity, even farm animals–then use those insights to make real-time decisions. Innovations in connectivity and artificial intelligence drive unprecedented efficiencies via faster processing and automated processes.

In this series, we’ll first introduce you to the concept of IIoT and highlight some everyday use cases, assess the current landscape, and look toward trends on the horizon. Here’s a closer look at what you can expect to learn in each installment.

What is Industrial IoT?

The industrial IoT is a term that refers to a subset within the broader Internet of Things (IoT) category. General IoT “things” span a wide range of computers, devices, and sensors that collect and transmit data, which can then be managed remotely through a cloud-based app. Where the term “IoT” is typically used in reference to consumer devices like fitness trackers, home security cams, or those home thermostats, “industrial IoT” applies the same principles as its consumer-grade counterpart to large-scale industrial processes.

This post is the first in our industrial IoT series. Here, we’ll provide a basic overview of the industrial IoT, highlighting specific use cases, emerging opportunities, and to balance things out, detailing some of the risks associated with adoption. Read more.

The Current State of Industrial IoT

In 2020, the IIoT has already come a long way, and as it stands, appears to be on the verge of widespread adoption.

Organizations are transforming legacy equipment with sensors and advanced analytics. Collaborative, AI-enabled robots (aka cobots) are fast becoming familiar faces on the factory floor. And then we have edge computing with its rapid, local processing, digital twins that model what might happen when an asset undergoes environmental changes, and unprecedented volumes of data.

In this installment, we examine where IIoT is right now, what’s keeping companies from embracing innovation, and why it may be time to start considering seriously how to bring intelligent systems into your business. Read more.

Benefits of IIoT

The industrial internet of things offers a diverse array of benefits to an equally diverse range of sectors, including healthcare, public utilities, retail, logistics, and countless others. That said, the manufacturing sector has led the charge when it comes to adoption, with many companies experiencing significant improvements in areas such as quality control, predictive maintenance, supply chain visibility, location-tracking, and more.

Here, we explore some of the many ways manufacturers are leveraging IIoT technologies to bring operations into the 21st century and the impact that transformation had on the industry–as well as the larger world around it. We’ll talk about benefits, risks, and the best practices that set the stage for sustainable success. Read more.

The Convergence of IT and OT

The idea of “tearing down silos” is familiar to those working in other sectors–development and operations coming together to deliver better applications, fast, or sales and marketing teams putting aside their differences to focus on delivering better customer experiences.

IT and operational technology (or OT), however, aren’t quite as friendly with one another.
In this article, we’ll discuss IT-OT convergence and the critical role it plays in ensuring organizations get the most out of their IIoT investments. Read more.

IIoT Challenges and Risks

In the past few installments, we briefly mentioned the challenges and risks associated with IIoT adoption. However, we mainly looked at the potential value provided by on-demand access to mass amounts of data–often from historically low-tech sources.

The industrial internet of things is the ultimate example of “high risk, high reward,” though it’s worth noting that many risks can be avoided by developing a strategy around solving a specific problem and developing a system for measuring results.

Here, we’ll dig a little deeper and offer a look at what can go wrong at the IIoT implementation stage, as you monitor and maintain operations, and later–when you attempt to scale. Read more.

Edge Computing and IIoT

Edge computing has emerged as a solution to some of the problems that arise while attempting to process vast volumes of data in the cloud. While the cloud offers sufficient processing power for most business operations–forecasting, communications, etc., it’s not the best choice for time-sensitive IIoT applications that demand access to real-time insights and require constant connectivity. Examples include autonomous vehicles, safety monitoring, condition-based monitoring, and security applications–all cases where minor interruptions caused by the cloud’s latency and connectivity issues could put sensitive data and human lives at risk.

Data processing is brought local with edge computing–and done right, offers a scalable, secure solution for capturing actionable insights in real-time. In this post, we’ll explain edge computing and its primary use cases in more detail. We provide a general breakdown of when to use cloud-computing vs. edge computing. Read more.

Cybersecurity for IIoT

Cybersecurity is one of the biggest challenges facing IIoT adopters. Systems are decentralized and can include thousands of connected devices, sometimes spanning multiple locations.
Compromised IIoT systems introduce threats that go way beyond the financial and reputational damage associated with a traditional cyberattack, by connecting physical equipment and infrastructure to the internet.

One unsecured endpoint–even something as small as a wireless printer–could put your entire system at risk, offering a gateway for attackers to hack smart factory equipment, connected robots, smart grids, autonomous vehicles, and so on. As such failing to embed cybersecurity best practices at every step of the implementation process can lead to real, physical harm.

The possibilities sound positively dystopian. Examples include acts of sabotage, a rogue machine that threatens human lives, or a freeze on all operations, costing hundreds of thousands, even millions, in lost revenue.

Unclear regulatory guidance, interoperability challenges, and finding a data management solution capable of efficiently processing and securing sensitive information further complicate the process. In this post, we’ll share some best practices for ensuring a safe IIoT transformation and maintaining protection as you scale, and as a result, increase your threat surface. Read more.

Implementing IoT at Your Organization

IIoT initiatives pose some unique challenges and potentially severe risks, which means, organizations must understand that strategic success relies heavily on developing a comprehensive IIoT strategy that accounts for every sensor, device, and endpoint.

The planning stage is an essential first step that lays the foundation for your connected system. As such, it’s important to stay laser-focused on the business cases that add the most value to your business. This might be as simple as increasing productivity and efficiency. Or, maybe it’s unifying data from heterogeneous sources like 30-year-old machinery, AI-powered bots, customer feedback, etc. and turning that information into actionable insights.

In any case, organizations need to audit their existing capabilities and equipment to identify technology and skills gaps, opportunities, and a sense of what they’ll need to put their transformation in motion. In this post, we outline a basic roadmap for kickstarting the IIoT implementation process and the key things to consider before making any commitments. Read more.

AI and IIoT

Like anything that falls under the “Industry 4.0” umbrella, it’s hard to separate the far-off promises of AI from the practical applications already in use today–and exponentially more so when you consider what happens when AI and IIoT join forces in one, connected system.

AI has long been embedded in the internet of things ecosystem. However, as organizations install more and more IoT devices, humans can no longer handle all of the data without some extra support, whether that’s analyzing disparate data sets, automating manual tasks, or responding to security threats without human intervention. Here, we’ll explore the symbiotic relationship between the two technologies–where AI is the brain to IIoT’s body. Read more.

IIoT Best Practices

While the industrial internet of things remains this sort of “wild west” as far as industry standards are concerned, we’re starting to see some best practices emerge, as more organizations complete pilot projects and move into real-deal applications.

In this post, we look at the Industrial Internet Consortium (IIC)’s report, A Compilation of Testbed Results: Toward Best Practices for Developing & Deploying IIoT Solutions. The paper revealed that while IIoT applications and the companies that use them are unique, several best practices apply across the board. Examples include identifying clear use cases, designing solutions with the end-user in mind, and eliminating the silos that block access to actionable insights. Read More.

Selecting the Right IIoT Platform

Here, we’ll look at an important piece of the IIoT puzzle we haven’t talked about much; IIoT platforms. Generally speaking, IIoT platforms work behind the scenes to ensure seamless communication across all connected components, and a centralized hub for monitoring and controlling IoT applications remotely.

The challenge is, not all IIoT platforms are created equal. A complete system includes hardware, software, a connectivity solution, and an interface that makes it easy to manage all of these moving pieces. Some platforms provide all-in-one solutions–essentially kits containing everything you need to get started. Many even include built-in tools, advanced analytics, and other capabilities that give organizations a head start as opposed to building each component internally.

Alternatively, some platforms only cover one part of the system like analytics or connectivity.
In this segment, we’ll offer a basic overview of what an IIoT platform is, explain the differences between five types of platforms, and provide a standard list of general capabilities that should be included in your solution. Read more.

What to Consider When Selecting an IIoT Partner

We’ve discussed promising IIoT business cases and the AI connection. We got realistic about risks and talked about planning, platforms, and legacy equipment. But, in this complex connected landscape, those examples are just the tip of the iceberg. Organizations need to execute every aspect of IIoT implementation flawlessly, or else, suffer significantly as a result. We mentioned what might happen if your IIoT system is hit with an attack, but there’s a lot more that could go wrong without the right expertise.

There’s also a whole host of challenges that come with establishing seamless interoperability across a decentralized system of heterogeneous “things.” Another common issue is achieving successful IT-OT convergence, as few people (on both IT and OT sides) have the expertise required for A: establishing a collaborative culture between these very separate groups, and B: applying IT security and data management best practices to systems that were never made to connect to WiFi.

This article discusses the benefits of working with an IIoT consultant who has seen it all before and can guide you through the process. Read more.

What’s Next for IIoT?

As it stands, IoT platforms, more affordable devices, and emerging standards and best practices are opening the industrial IoT to a broader range of businesses. While IoT-as-a-service platforms, low-cost sensors, and the need to keep pace with competitors and rising customer demands is moving IIoT into the mainstream, industry-wide transformation is still a ways off. Near term, we’ve got 5G on the horizon, ever-evolving AI capabilities, and increasingly user-friendly analytics tools that democratize business intelligence.

We’re also in the midst of a global pandemic, which may increase the use of automation and AI-based predictive analytics. Though the future of IIoT remains to be seen, this final installment considers what’s next for “Industry 4.0.” Read more.

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