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Practical AI – A Serious Issue for Industrial IoT

February 28, 2020 / MARTIN KEENAN

While the Industrial Internet of Things (IIoT) is maturing rapidly, there’s often a strong link to Artificial intelligence (AI) and Machine Learning (ML) tools to manage data flows. This raises a host of challenges including connectivity, security, storage and modeling requirements. Designers of IIoT devices and larger deployments must build in contingencies for shifts in these areas or risk falling short. While IIoT is gaining in maturity, the overall market still has many challenges to overcome. Some of these challenges are technical barriers to IoT device operation, such as connectivity standards and battery technology, but the picture is even wider than that. The world of IIoT not only requires IoT hardware to operate reliably and efficiently in all environments but also relies on supporting networks and services too. The result is that IIoT deployments cannot be viewed as isolated technology upgrades or productivity drives, but highly interconnected ecosystems sensitive to a wide range of variables – in particular the developing world of AI.