An AI-powered platform for monitoring and detecting defects in sewer networks has been designed and implemented by a research team at the University of Birjand, led by Dr. Abolfazl Akbarpour, Professor in the Department of Civil Engineering. The platform aims to improve the accuracy and speed of sewer infrastructure monitoring and management, reduce inspection and maintenance costs, and minimize operational risks.
Explaining the system’s capabilities, Dr. Akbarpour stated: “The AI-powered sewer network monitoring platform can receive and process images and video footage from sewer inspections, identify defect types, and pinpoint the precise locations of damage within the network.”
He added: “One of the system’s key features is its use of an extensive database to train its artificial intelligence models. The platform’s development and machine learning processes have involved analyzing more than 1.3 million images of sewer networks. This volume of data has helped improve detection accuracy and accelerate network monitoring.”
The research project was implemented with support from the South Khorasan Province Water and Wastewater Company and in collaboration with Abniran Consulting Engineers.
By facilitating the identification and analysis of damage, this technology can improve sewer infrastructure management and maintenance while reducing the time and costs associated with inspections and the detection of underground hazards.
This achievement demonstrates the University of Birjand’s research capacity to develop practical technological solutions for the smart management of urban infrastructure.
