Data Management for Linear Assets: Case for Edge Processing
Collecting and processing data efficiently is central to good linear asset management. In general, the more data we collect on linear assets, the more accurate analytics we can run and the better picture we get for the real-time state of linear assets. This brings us to the question of how best to manage the deluge of data and make the most out of it. Organizations that have enough bandwidth have an advantage that they can bring in huge amounts of data to get better insights into their assets. On the other hand, companies that have limited bandwidth to transfer, process, and report data are in a bind: how much data to collect and how to process the data without overflowing the available bandwidth? In this post we discuss the option of edge processing of data for companies strapped for bandwidth.
Edge Processing is best summed by The IEEE Standards Association as: “Placing data and data-intensive applications at the edge reduces the volume and distance that data must be moved.”
In addition to making the data processing possible within relatively limited bandwidth, following are some additional benefits of edge computing.
Local control over data
In some situations, where the centralized control or decision making is not essential, edge computing is the best way to capture and use data at the location. This adds to the accessibility and efficiency of the data processing by eliminating the unnecessary steps and latency.
Smart use of bandwidth
Edge processing could also help make the most out of the available bandwidth. The ability to process data close to the field helps companies make critical decision of whether to keep, use, or discard the data at the spot. In this way, it is easier to send only the relevant data to the centralized location for further processing, reducing the need of huge data transfer. So, the overall effect is that companies end up having more bandwidth free for necessary operations.
Another benefit of edge processing is the decreased latency in decision making due to less time required to transfer data to the cloud. In situations where time is critical, edge computing gives the decision makers an edge. To reduce latency to the minimum, edge processing can make local decisions on the collected data and directly communicate alarms to appropriate maintenance personnel.
Edge computing makes data management for linear assets possible within limited bandwidth and brings some unique advantages as well. If you have any questions about the applicability of this approach for your linear assets, let us know. We’ll be happy to help.
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