“Smart Street Light Fault Identification And Using Notification App”

M.M.Kharade ¹, Aditi Aghav², Roshni Dahibhate ³, Dattatray Sankpal ⁴, Mohammad Farhan ⁵

Nagesh Katmore, Sufiyan Aslam Siddiqui

^1,2,3,4,5Electrical Engineering Department Trinity College of Engineering and Research, Pune, Maharashtra

Abstract - Street lighting plays a vital role in ensuring public safety and efficient transportation during night hours. However, conventional street light monitoring systems often fail to detect faults such as lamp failures, power fluctuations, or wiring issues in real-time, leading to energy wastage and inconvenience to the public. This project proposes smart fault identification and alerting system for street lights

using IoT technology. In the proposed system, sensors and microcontrollers are integrated with each street light unit to continuously monitor its operating status, including parameters such as current flow, voltage level, and light intensity. When an abnormal condition or fault is detected—such as bulb failure, power

outage, or abnormal power consumption—the system automatically identifies the faulty light and transmits the data to a central server through wireless communication (e.g., Wi-Fi/GSM). An application installed on the concerned authority’s smartphone receives instant fault notifications, including the

location and type of issue. This system enables timely maintenance, reduces manual inspection efforts, and improves energy efficiency and reliability of street lighting infrastructure. Additionally, the use of app-based alerts ensures rapid response and enhanced operational management. The proposed solution contributes toward building smarter, safer, and more sustainable cities. In contemporary urban landscapes, the efficiency and reliability of street lighting systems are crucial for public safety and sustainable city management. This paper introduces an advanced street light control system designed to significantly enhance the management and functionality of urban lighting infrastructures. The proposed system

integrates Light Dependent Resistors (LDRs) to perform continuous monitoring of ambient light levels, enabling automatic adjustment of lighting to ensure energy conservation while maintaining optimal illumination. These sensors are pivotal not only for maintaining energy efficiency but also for identifying any deviations from standard light outputs, thereby facilitating immediate fault detection.

 Key Words: BT136-600E, MOC-3021, ACS712, HC-SR 501 PIR, LM393 LDR, ESP 32s.