The Hong Kong Polytechnic University (PolyU) is dedicated to pioneering innovative transportation technologies that enable sustainable and efficient mobility. A novel research project of PolyU, aimed at developing a universal vehicle self-diagnosis system driven by automotive component data and real-time predictive analytics, has received support from the Smart Traffic Fund. This support strengthens the capabilities in intelligent vehicle management and maintenance.
Led by Prof. Li-Ta HSU, Associate Professor and Limin Young Scholar in Aerospace Navigation in the Department of Aeronautical and Aviation Engineering, the project titled “Automotive Component Data-Driven and Real-Time Predictive Universal Vehicle Self-Diagnosis System” has been awarded approximately HK$6.19 million in funding over a 24-month period.
The project aims to develop a universal vehicle self-diagnosis system capable of analysing automotive component data and providing real-time predictive functions. The system integrates multimodal sensing technology, aggregating sensor data from vehicle OBD-II parameters, GNSS, high-resolution cameras, acoustic sensors, and inertial measurement units.
Through deep fusion and synchronized processing of these multi-source datasets, the system accurately extracts vehicle fault features and abnormal behaviour patterns. The collected multimodal data will be transmitted to a cloud analytics platform, which employs deep learning and time-series analysis models to deliver fault classification for accurate detection and lifespan prediction.
The system also develops GNSS reasoning algorithms to enable location-aware analytics, including indoor and outdoor environment inference. It connects with fleet management platforms to support daily operations and maintenance decisions.
PolyU has long been committed to the research and application of vehicle-related innovation and technology, with 28 projects supported by the Smart Traffic Fund to date.
The Smart Traffic Fund provides funding support to local organisations and enterprises for conducting research and applying innovation and technology, with the objectives of enhancing commuting convenience, improving efficiency of the road network or road space, and strengthening driving safety.
