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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.
The final set of challenges to be discussed relate to real-time alerting based on readings collected. As we have seen in modern IT monitoring, IoT monitoring is likely to face the same problems around alert fatigue. This would be when a field technician receives too many false positive alerts and, as a result, begins ignoring them or becomes overworked.
Alert fatigue can happen when there is an over-reliance on raw readings being used in isolation. These raw metrics can be noisy and should not raise alerts unless correlating data matches certain conditions or unusual trends are identified. An alert will be raised if a machine's temperature remains above a certain threshold for a few seconds, even though it may not be a problem that requires immediate attention, if there is a trend of that machine becoming hotter at a similar time each day and then having its temperature go back to normal. Knowing that trend may allow better categorization of that alert to be one lower in priority.
Data analysis and visibility for managers will drive the future of the IIoT. Visualization and data analysis can be categorized as either real-time or historical. Real-time analysis can be accomplished at the edge, often to raise alerts but also to aggregate multiple metrics or downsample. The downside with aggregation or downsampling at the edge is that you lose the ability in the central system to drill down. Historical analysis is more about examining trends and inferring what is likely to happen in the future.
In order to provide visualization for management, the data collected often needs to aggregate several times so that it can fit onto a single screen. They should always have the ability to drill down on those top-level metrics. You really want to keep the headline metrics to a minimum and make them as simple to understand as possible; otherwise, people will become overloaded and miss key indicators or changes.
Properly analyzed data from connected devices will have a huge impact on preventative maintenance, especially for industries that need to avoid breakdowns due to costly repairs involving oil wells and elevators, for example. Preventing all failures is not feasible in most cases, but analysis can also help to reduce the time required to restore through better alerting and ensuring that technicians have the right tools and parts to resolve these issue as quickly as possible—hence, keeping downtime to a minimum.
The Internet of Things has created a new set of challenges for industrial organizations, but these organizations can use intelligent and effective data-analysis techniques to provide visibility for managers to drive the future of the IIoT going forward.
Nic Grange is the CTO of Retriever Communications. Nic has been with Retriever Communications since 2004 and currently serves as the company's chief technology officer. His primary responsibilities include evaluating new technologies, particularly in the areas of mobile, automation, integration, security and the cloud.
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