When Sensors Fight Back: Why Production-Ready Edge AI Is Harder Than the Demo

Session details:

Edge AI systems often perform well in controlled demonstrations, but real-world deployment introduces sensor behaviors that quickly expose gaps between prototypes and production. Variability in sensor data, environmental conditions, and user interaction can drive repeated model updates, extended validation cycles, and unexpected system complexity.

This presentation shares real-world experiences across multiple sensor analytics domains, including acoustic, vision, and electrical sensing, where Edge AI models had to be iteratively adapted to handle noise, occlusions, and safety-critical edge cases. Rather than focusing on algorithms, the talk highlights how sensor data collection, retraining, and validation become ongoing system-level challenges. Attendees will leave with a practical understanding of why production-ready Edge AI depends on treating sensors, data workflows, and embedded constraints as first-class design considerations.