Water losses in water distribution systems (WDSs) significantly contribute to economic costs and additional energy consumption. If leaks in the WDSs are not repaired in time, they may develop into breaks, which can lead to traffic interruptions, property damage and negative publicity for water utilities. In recent years, Internet of Things (IoT) technologies with distributed wireless acoustic sensors (e.g., accelerometers) have been increasingly adopted in water utilities to build smart water networks (SWNs) for detecting leaks. However, the potential of such SWNs is significantly untapped due to limited study in this area. This project will develop advanced signal processing techniques, statistics-based and machine learning techniques using the IoT data to unlock the potential of SWNs and enable effective water asset maintenance by detecting developing cracks in water networks.
- Student type: International, Domestic
- Research degree type: PhD
- Signature research theme: Sustainable Green Transition
- Supervisor: Dr Wei Zeng
