PI-AI Fault Detector aims to provide next-generation artificial intelligence solutions for monitoring the condition of sensors in centralised heating, ventilation and air conditioning (HVAC) systems. Configurations and sensors in modern HVAC systems are highly complex and diversified. Detecting faulty sensors in these systems is a challenging task, and this is currently done with labour-intensive manual checks. Our solution features a generalised and reliable physics-informed deep-learning platform, providing high-dimensional sensor fault detection for complex and diverse HVAC systems. It automatically builds up a workflow based on sensor measurement data extracted from building automation systems. Our goal is to provide lifetime HVAC sensor health service and accelerate the transformation of building automation to an AI-driven paradigm.
Dr Ren Haoshan* (Postdoc, Department of Architecture and Civil Engineering, City University of Hong Kong)
Dr Xu Chengliang (Huazhong University of Science and Technology)
Dr Zhang Yelin (Res Asst, Alumna, Department of Architecture and Civil Engineering, City University of Hong Kong)
* Person-in-charge
(Info based on the team's application form)
- CityU HK Tech 300 Seed Fund (2023)