Trends in intelligent sensor-based customized management technologies for sewer infrastructures

Abstract

Sewer infrastructure management is essential for public health, environmental protection, and urban stability. Aging networks and the impacts of climate change emphasize the need for advanced management solutions. Traditional methods, such as periodic inspections and reactive maintenance, are insufficient to address the complexities of modern sewer systems. This study surveys intelligent-sensor-based management technologies aimed at improving sewer infrastructure. Key technologies include Internet-of-Things-driven data collection, machine learning and deep learning analytics, cloud and edge computing, and autonomous robotics. Based on case studies from South Korea, Germany, Japan, and the United States, the practical benefits of these technologies were explored, including real-time monitoring and predictive maintenance, as well as challenges such as sensor durability, robotic mobility, and data analysis limitations. Rather than proposing solutions, this study evaluates the current state of these technologies and identifies gaps that require further research and innovation. It provides a comprehensive overview that serves as a valuable resource for researchers and practitioners and contributes to the advancement of sustainable and efficient sewer management systems.