Sensor Enabled Centralised Monitoring System for Streetlight Fault Detection Using IoT

This paper presents a novel, sensor-enabled centralised monitoring system for fault detection in streetlights. Unlike traditional methods that depend on citizen reports or manual inspections, this system utilizes Internet of Things (IoT) technology to identify faults automatically and efficiently. The system comprises monitoring devices equipped with sensors and transceivers attached directly to streetlights. These devices collect data on light source functionality and potential wiring faults. This data is then wirelessly transmitted to a central transmitter, which relays it to a cloud platform. A machine learning model, trained with an accuracy of 98.8%, analyzes the data and predicts the streetlight’s operational status. The predicted status and detailed fault information are displayed on a dedicated webpage, allowing stakeholders to monitor remotely. This eliminates manual searches, expedites repairs due to precise fault knowledge, and empowers linemen for faster resolution. Overall, this cost-effective system significantly improves streetlight maintenance efficiency, enhancing public safety and contributing to a well-lit urban environment.