Water scarcity is a growing global challenge, and leaks in distribution networks continue to contribute significantly to this problem. This paper presents an intelligent leak detection system for desalination networks. This system relies on integrating Internet of Things (IoT) sensors with automatic shut-off valves and ESP32 microcontrollers to accurately locate leaks and send notifications directly to the operator via the Blynk app. The Critical Path Method (CPM) was used to improve project scheduling and resource management while ensuring efficient execution. Simulation tools such as SolidWorks and Proteus were used to verify the electronic control logic and the correctness of the system design. The project management analysis determined the total project duration to be 15 weeks. The system demonstrated high feasibility with an initial cost of 916 Saudi Riyals and a payback period of approximately 1.22 years, which proves the system’s cost-effectiveness in reducing water and operational losses. The results clearly demonstrate the potential for development and expansion to include several regions in the Kingdom, which will enhance sustainability and efficiency in water resource management in Saudi Arabia. 

Keywords

Detecting Leaks, Critical Path Method (CPM), Risk Management, Water distribution networks, Economic study.