The Promise and Perils of AI Sensor Calibration and Smart Ventilation

Exploring the promise and risks of AI-driven calibration for indoor air quality sensors, from data accuracy to trust and regulation. AI and machine learning are increasingly used to calibrate low-cost indoor air quality sensors, promising more accurate and data-driven building management. But how reliable are these approaches in real-world indoor environments, and what risks do they introduce?

In this EDIAQI Webinar, EDIAQI and NextAire explore the promises, limits, and trust challenges of AI-driven sensor calibration, including uncertainty, transparency, ethics, and regulation. The session also featured a lively Q&A with the experts, engaging directly with audience questions and real-world concerns.

▶️ Watch the recording Funded by the European Union’s Horizon Europe Programme (Grant Agreement No. 101057497).