Pairing IoT and AI to Reduce Network Maintenance Costs (2023)

By Goutam Agarwal, Rogers Communications; J. Clarke Stevens, Independent Consultant

The most fundamental component of a cable service provider’s products is the network. The networks we provide are ubiquitous in the lives of our customers. Any network disruption causes inconvenience, but as more people work from home, run businesses over the network, or manage critical services online, an outage can increasingly have a serious financial effect or even put people’s lives at risk. It is imperative that our networks provide the features, quality, and reliability our customers have come to expect. There are many obstacles to maintaining quality and reliability: Data is frequently erroneous or arrives too late to be of significant value; finding qualified employees for a more complex portfolio of products and getting those people to the right place at the right time to fix problems is increasingly difficult and expensive; diagnosing problems is often a matter of experience that is isolated to a few experts. It is expensive to send people to fix plant problems, and the prescribed fix may not always be effective. One possible solution is to provide the necessary technical capability to the technicians to cut through complexity and reduce cost, while allowing the network to self-diagnose and in many cases repair problems without the need to roll a truck. Such tools are built on the concept of the Internet of Things (IoT). This includes sensors and actuators in the network and Artificial Intelligence (AI) algorithms to interpret and correctly diagnose or even automatically repair network problems. While instrumenting the network is an up-front capital cost, it can pay for itself by providing an accurate real-time view of the status of the network. AI can interpret the collected data and use that data to provide an accurate diagnosis of the problem, isolate a precise location for the fix, then potentially reroute traffic while a repair is made and even automatically make the repair. This results in a more reliable network that can be maintained at a lower cost. In this paper, we will explore existing and potential IoT solutions that can be installed in the network, and how IoT and AI can be combined to build network infrastructure that is simpler and less expensive to maintain. We will frame this as a progressively improving solution from a reactive response, to planned upgrades, then moving to proactive prevention and finally to a predictive solution that anticipates and resolves problems before they happen. This approach migrates the network from a resource that exhibits frequent downtime into a resource that is rarely down while being less expensive to maintain.

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