Climate change is intensifying extreme weather events, putting growing pressure on urban infrastructure such as sewer systems. To address these challenges, researchers at The Hong Kong Polytechnic University (PolyU) have developed an innovative smart sewage management model to enhance the resilience, efficiency and sustainability of underground sewerage networks.
Led by Prof. Tarek ZAYED, a member of RICRI and Professor of the Department of Building and Real Estate, the research team developed a model that uses deep learning algorithms to analyse sewer pipeline conditions with high accuracy. The system helps infrastructure operators detect deterioration, defects and potential blockages at an early stage, enabling more timely and effective maintenance.
The study responds to the urgent need for smarter infrastructure management in dense urban environments, where ageing sewer systems are increasingly vulnerable to extreme rainfall and other climate-related pressures. By integrating intelligent assessment, real-time monitoring and predictive analysis, the model supports a proactive approach to sewer inspection and maintenance.
This data-driven solution can help reduce service disruptions, lower operational risks and improve resource allocation. It also highlights the transformative potential of digital technologies in infrastructure management by supporting preventive maintenance and evidence-based decision-making. As cities face the combined pressures of climate change, urbanisation and ageing infrastructure, such innovations will be vital in strengthening urban resilience.