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What Opportunities Does the Industrial IoT Present for Field Service?

The increased number of connected devices in the field comes with a surge of data, and the question of what to do with all this information.
By Nic Grange
Nov 24, 2017

The Internet of Things (IoT) has already made a significant impact on the industrial and utility sectors, from smart meters to oil and gas monitors, and there is no arguing that it is changing the industry. With smarter technology, field-service managers are able to gain deeper insights that were not available in the past.

But the increased number of connected devices in the field also comes with a surge of data and an even bigger question: what do we do with all this data? As enterprises gather more data, they need to decide what type of information will be valuable for analysis and lead to decision-making impact—a key driving force for the next phase of growth for the Industrial Internet of Things (IIoT).

The first set of challenges organizations face involves where to store the data, whether to store all or just part of it, and how long to keep it for. Some people will say that cloud storage is cheap and, as a result, you should keep everything indefinitely, but overtime those costs will grow and eventually become significant enough to be questioned.

Techniques like downsampling can help reduce the amount of data while still allowing analysis. A sensor might capture a temperature reading every 10 seconds, but you might only want to keep it to a granularity of one reading per minute or even per hour. Those readings can be aggregated into one value, representing the average or middle value.

The next set of challenges are where and when to process the data. This is commonly done on a centralized system, but this approach usually has timeliness implications. Certain organizations have to turn to edge processing to avoid the delay it takes for data to flow back to a centralized system. Usually, the type of edge processing is kept quite simple, like raising alerts that need immediate action.

Manual data collection was typically carried out infrequently, such as every three months on a preventative maintenance schedule. This made it very difficult to see trends, but when data starts to be collected on a frequent interval every minute or few seconds, it opens up the opportunities to analyze trends and develop intelligence into analysis, real-time monitoring and alerting.

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