Cerberus: Privacy-Preserving Crowd Counting and Localisation using Face Detection in Edge Devices

Cerberus uses face detection in edge devices to perform privacy-preserving crowd counting and localisation. We describe its deployment in a university setting where ceiling-mounted cameras perform real-time face detection to report occupied seats without storing or transmitting images. Cerberus' aim is ultimately to integrate with digital twins over a LoRa network enabling data visualisation and support applications in building informatics, while balancing data accuracy and individual privacy. The paper describes the system's design, deployment, and potential for broader urban informatics applications, highlighting its effectiveness in privacy-preserving crowd monitoring.