The Key to Situational Awareness for Pipeline Networks 

The pipeline sector has adopted IoT technology at pace and for good reason.

Leveraging networks of deeply integrated sensors, an IoT application allows operators unparalleled insight into their assets’ performance and health. Systems designed to analyse and humanise the data from sensors are also in high demand as operators seek to gain greater situational awareness. Over the past few years, there has been significant investment in these areas across the energy and water sectors, however, many operators have struggled to make the most of IoT technology. A solution lies in edge computing. 

Edge Computing 

Applications based solely on sensors have limits. They typically require connection to the cloud which is not guaranteed. In fact, 75% of decision makers in the water industry report that connectivity issues have impacted their IoT projects. In many cases, where data isn’t transferred directly to the cloud, it is lost. 

One solution to this problem is to twin sensors with edge computing. An edge computer is capable of storing data locally at times when connection is unavailable. This means that critical data is not lost, and the threat of poor connectivity is lessened. 

However, edge computing is more than just a solution to poor connectivity, it represents an opportunity to streamline data processes. Klarian’s edge analysis uses many of the same methods and algorithms that are performed by Juno Perform, our software to transform data into intelligence to improve pipeline performance. Bringing a model from the cloud into the edge means that the results are specifically targeted to a location and reduces the time from event to detection. These benefitsbecome part of a robust, flexible analysis programme. 

This makes it possible to use the collected data to make decisions about processing and transmission. For example, Klarian’s edge analysis software can choose to send higher resolution data while a detected event is taking place. 

Edge computing can also have a positive impact on cyber-security. As cyber-attacks become more common, cloud and server-based technology represent a single point of failure. Conversely, edge computing de-emphasises reliance on the cloud, and allows the use of secure networking protocols, and for the software to be upgraded in response to an evolving threat landscape. It also allows for local storage of data, making operations more resilient to the threat of cyber-attacks.

Conclusion 

For water and energy companies in the UK, managing processes with an IoT led approach is becoming the norm. Operators can’t manage what they can’t measure and IoT technology enables more complete oversight of their systems. Edge computing makes these technologies more effective and more resilient and should be part of any operator's analysis program. If comprehensive situational awareness is the goal, edge computing is a critical, if underutilised, piece of the puzzle. 

Authored by Greg Bodnar, Head of Embedded Devices.