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More killer apps for industrial IoT

The killer app is a powerful concept. It is the vehicle for driving adoption of any new technology — and IoT, especially industrial IoT, needs that catalyst. In many ways, it shines a light on the differences between consumer and business-oriented IoT.

Consumer vs. industrial IoT

On the consumer side, the device is typically the star of the show. That is why CES is filled with endless ideas of how to add sensors and connectivity to everything in our lives. Consumers are more easily lured into purchasing the latest and greatest gadget — even if it has no inherent value other than the coolness factor. Businesses think differently.

Businesses need to justify any technology purchase by tying it back to a tangible benefit. This almost always takes the form of an ROI calculation. If a positive return cannot be established, no right-minded company will allocate budget for it.

That is why the killer app is so important. It represents a solution to a real business problem. One that is obvious and immediate. One that is easy to understand and does not require an extensive deployment effort.

Building on other examples of killer apps for industrial IoT, here are three more:

IoT device management
It may seem obvious, but as more equipment across an organization becomes data-enabled, a mechanism is needed to manage it all. This is even more critical for assets in the field, which may be scattered across a large geographic area.

The problem is that most enterprise device management solutions are not designed to handle the resource-constrained nature of IoT devices, which in many cases have limited processing power, memory or bandwidth. While solutions have started to support mobile devices running embedded versions of Windows and variants of Android or Linux, there is an entire class of equipment out of their reach.

Asset optimization
An amazing benefit of IoT is visibility into real-time operational data. This can be used to understand how the population of connected equipment is performing. By establishing a data model baseline of operating behavior, it is possible to identify any underperformers. To take this a step further, these models can also uncover the contributing factors to the problem and generate a prescriptive remediation plan.

This same methodology can also assist in simulations. It is incredibly useful to be able to understand how a change in the equipment design or configuration will affect overall performance.

Asset utilization
This exists today in a rudimentary form: the visualization of telemetry data in dashboards. But businesses need more than just current sensor data. They need a way to apply logic to that data to enforce a business policy, whether for its own corporate governance or to comply with a mandated regulation.

Product companies also have a desire to understand utilization data. This can be used to track what features are being used and whether they are working as intended, both of which can improve product design. It solves an issue these companies face today where they lack visibility until the point a customer encounters a problem and seeks support.

And, this is just the beginning…

By no means is this an exhaustive list of killer apps, but rather a start to what is possible. As the industry matures, expect to see an increased emphasis on an app-based approach to IoT. And for those in the midst of defining an IoT strategy, the key to success is identifying the tangible business use case first and then the technology required to achieve it — not the other way around.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

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