Processing sensor
data at the edge:
Advantages for
the energy sector

Author: Rose de Fremery

Energy and utility companies are increasingly using sensors to track energy usage, demand, outages and other crucial business metrics. In doing so, they're in line with a larger overall business trend. According to HPE analysts, 75% of enterprise-generated data will be created and processed outside a traditional data center or cloud by 2025.

Curious about processing sensor data at the edge advantages and why so many organizations are turning to this method of data collection? Here's how processing sensor data at the edge can help energy and utility businesses quickly make autonomous decisions, improve worksite safety, reduce energy consumption and improve network performance.

Network performance improvements

Energy businesses can gain powerful insights by collecting a large volume of sensor data, but then they're faced with a challenge: how to best process it. If they choose to process the data in a data center or in the cloud, they may run into latency issues that slow down the rate of processing, which throws a wrench into a timely decision-making process and can limit the autonomy of a local facility. Processing data off-site may also use up more bandwidth while constantly transmitting the sensor data, which increases costs and can affect overall network performance.

By processing sensor data at the edge, however, energy and utility companies can significantly reduce the latency involved in data transmission. Since all processing happens locally, there's no need to transmit the data from so many sensors back to the data center or up to the cloud before performing the necessary analysis.

This enhanced network performance can lower the company's bandwidth usage, which often improves its overall network performance and increases the capacity that can be allocated to other network services. It can also reduce the costs associated with bandwidth consumption, resulting in leaner and more efficient operations. The most compelling advantages of processing sensor data at the edge, however, have to do with timely and autonomous decision-making.

Quick, autonomous decision-making

When an accident or an anomaly happens, an energy facility or utility company may need to quickly make a decision about how to respond. This isn't always easy, however, when sensors are located in far-flung and inhospitable locations with reduced internet connectivity.

Processing sensor data locally at the edge makes timely and autonomous decision-making easier, furnishing leaders with the information they need to act. That way, they don't have to aggregate large quantities of data, send them to the cloud and wait for word to come back.

Local and autonomous decision-making can improve worksite safety by giving managers the insight they need to respond to an emerging safety incident. For example, water companies can monitor Internet of Things (IoT) sensor data to keep tabs on work sites, such as mines and oil rigs, responding right away if their workers' safety is threatened—for example, by automatically shutting down a section of pipe upon detection of a failure.

That same kind of sensor data can be used to proactively notify customers if water contamination has occurred, so they can secure their businesses and homes. With the agility to act in near real time, the business can mitigate the impact of an unexpected event and protect its business reputation.

Enhanced equipment monitoring

Energy and utility companies are also processing sensor data at the edge to improve equipment condition monitoring. For example, they can place wireless, internet-enabled sensors throughout the grid to monitor power quality. If a failure occurs, the system can send an alert right away, so local managers can take the appropriate action.

These alerts can be triggered in the case of an outage, a fault or a restoration in service. With real-time equipment condition monitoring, managers can quickly dispatch crews to fix the affected equipment and minimize the resulting downtime.

This capability can also be used for predictive monitoring, empowering the energy company to proactively address equipment issues before they affect customers. In this way, they can improve the customer experience while also reducing the operational costs and revenue impact associated with downtime.

Reduced energy consumption

Smart meters can monitor energy consumption data in near-real time, allowing energy and utility companies to better understand how their services are being consumed and use that information to optimize their operations. With 5G and Edge computing more smart meters can be deployed in mass to monitor, maintain & manage energy consumption in near real time. This could enable energy and utility companies to better understand energy usage and optimize their operations.

This way, customers can become partners with energy and utility companies in helping prevent service issues and can enjoy a better customer experience in the process. Customers who place a high priority on sustainability may appreciate being able to take control of their energy usage. In addition, since edge computing may consume less energy overall than cloud computing at scale, this practice may help energy and utility companies do their part to ensure a sustainable future.

Edge computing is modernizing the energy sector

Energy and utility customers are becoming more sophisticated, demanding a higher standard of service from the companies with which they do business. IoT sensor data makes it possible for these companies to optimize their operations and meet customer demand for a high-quality experience. To access the full spectrum of features that IoT can enable, however, they may want to consider a hybrid architecture with edge computing versus just a traditional cloud.

Processing sensor data at the edge advantages include not only enhanced network performance but also rapid local decision-making, improved equipment monitoring and reduced energy consumption. By modernizing their businesses in this way, energy and utility companies can build a solid foundation for long-term business growth.

Learn how an oil company was able to improve safety and productivity with M2M.

The author of this content is a paid contributor for Verizon.