What if LoRaWAN devices could make decisions—not just transmit data?

This keynote explores how edge AI brings intelligence directly to low-power nodes, enabling faster responses, lower bandwidth, improved privacy and longer battery life. Through real-world examples spanning predictive maintenance, smart agriculture, embedded vision and industrial monitoring, discover how devices can detect anomalies, identify events and send only actionable insights over LoRaWAN.

The session also addresses the critical path from prototype to production, including data quality, model optimization, power consumption, security, validation and lifecycle management. See how compact models can deliver millisecond-level anomaly detection in just a few kilobytes of memory—and learn what it takes to deploy edge AI at scale.