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Rakuten Mobile, Inc. Head of Network Intelligence Rishi Davda joined us on Zero-Touch Telecom Live to share his experience building and operating an AI model to quickly and accurately diagnose sleeping cells. The replay is available below.
Sleeping cells are a problem begging to be solved by AI given how much analysis and data is required to find them. At any given time, there may be dozens of sleeping cells hiding in plain sight amongst hundreds of thousands of normally functioning cells. These sleeping cells appear to be operating as expected but are actually delivering poor customer experiences, sometimes for days on end.
Symptoms like latency and low traffic flow aren’t enough to pinpoint a sleeping cell. Huge amounts of data related to region, weather patterns and events must also be considered and analyzed with historical context.
Watch now to hear Rishi explain how the Rakuten Mobile sleeping cell AI model was built, his experience running it and how it has been tuned over time to improve results.
And if you haven’t already, be sure to read Rishi’s article from our last Zero-Touch Telecom newsletter, where he explains the data that informs AI models, the analysis conducted, goals and challenges that arose along the way.
