This is like a smart thermostat for a mobile network: when there’s no one in a room, it turns the lights and heating off automatically. Here, AI detects when parts of the cellular network aren’t carrying traffic and safely powers them down, then wakes them up when needed.
Mobile operators waste significant energy keeping radio and network resources active even when there is no or very low traffic. This AI solution minimizes energy use during low-traffic periods without harming service quality, cutting OPEX and supporting sustainability/Net Zero commitments.
Deep integration with telecom network equipment and telemetry plus Nokia’s domain-specific network data and models, which are hard for generic AI vendors to replicate.
Hybrid
Time-Series DB
High (Custom Models/Infra)
Real-time inference latency and reliability at network scale (millions of cells/parameters), plus safe failover to avoid service degradation when powering elements down or up.
Early Majority
Framed specifically around ‘zero energy at zero traffic’ as a design principle, tightly coupled with Nokia’s RAN and network management stack, using AI to automate cell and resource shutdown/activation decisions based on fine-grained traffic behavior and service constraints.