Automated Fault Detection and Location Monitoring of Street Lights in Smart Cities

Abstract

This work will implement an automated fault detection and monitoring system for streetlights in smart cities. The system will use smart streetlights with sensors, communication modules, and intelligent controllers to create a sensor network across the city. These sensors, like light intensity, motion, and temperature sensors, will collect real-time data on the status of street lights and the environment. The data will be analyzed by a centralized monitoring system that will use algorithms to detect abnormalities in the sensor data that may indicate faults or malfunctions in the street lighting infrastructure. GPS tracking technology will be used to pinpoint the location of each street light. An automated alert system will notify maintenance teams and city officials through a webpage if a fault is detected. The system will also use historical data to anticipate potential issues before they arise.The benefits of this system include improved energy efficiency, cost savings through timely maintenance, quick response times for fault resolution, and data-driven decisionmaking for urban planning. It will provide real-time information on the status of street lights and their environment, which can be used to optimize energy consumption and reduce costs. The system will also enable city officials to make data-driven decisions for urban planning. Ultimately, this system will help to create smarter and more sustainable cities by enhancing public safety, optimizing energy consumption, and ensuring the reliability of street lighting infrastructure. The system will provide a more efficient and costeffective approach to street lighting maintenance, leading to better services for citizens.