DESIGNING AN INTELLIGENT IOT-DRIVEN EMBEDDED SYSTEM FOR FAULT DETECTION AND DIAGNOSTICS IN UNDERGROUND CABLE NETWORKS

Abstract

Underground cable networks are critical components of modern infrastructure, providing essential services such as electricity and telecommunications. However, detecting faults in these networks is a challenging task due to their inaccessibility and the complexity of their fault mechanisms. Traditional fault detection methods often suffer from delays, high maintenance costs, and inefficiency. This paper presents the design and implementation of an intelligent IoT-driven embedded system aimed at enhancing fault detection and diagnostics in underground cable networks. The proposed system integrates sensors, microcontroller-based embedded systems, and IoT communication protocols to enable real-time monitoring and fault detection. A robust fault detection algorithm is employed to analyze sensor data, identify potential faults, and trigger notifications for timely intervention. The system’s IoT capabilities enable remote monitoring, data logging, and diagnostics, significantly improving the operational efficiency and reducing downtime. Experimental results demonstrate the system's accuracy and responsiveness in identifying faults, making it a promising solution for modernizing cable fault management. This paper also discusses the challenges, limitations, and potential for future developments in integrating advanced technologies for the optimization of underground cable network management.