Real-Time Street Light Monitoring, Control and Fault Detecting System

Abstract

The Modern street lighting systems require intelligent automation to reduce energy consumption and improve maintenance efficiency. This paper presents a Real-Time Street Light Monitoring, Control, and Fault Detection System developed using an Arduino Uno microcontroller, an LDR sensor, a relay module, and a piezoelectric buzzer. The LDR sensor continuously measures ambient light intensity and automatically controls the operation of street lights according to surrounding environmental conditions. The proposed model also integrates a fault detection mechanism capable of identifying lamp failures and circuit interruptions in real time. Whenever an abnormal condition is detected, the system activates an audible buzzer alert to inform maintenance personnel immediately. This feature helps reduce repair delays and improves the safety and reliability of public lighting infrastructure. Experimental testing was carried out under multiple lighting conditions to evaluate system performance. The prototype achieved automatic switching response times between 1.5 and 2 seconds and detected faults within 500 milliseconds. The developed system also demonstrated approximately 58% reduction in energy consumption compared to traditional continuously operating street lighting systems. The proposed solution is economical, easy to implement, and suitable for smart cities, educational campuses, industrial areas, highways, and rural roads. Future enhancements may include loT-based remote monitoring, cloud integration, and GSM-based maintenance alert systems.

Introduction

The text describes a smart street lighting system designed to improve energy efficiency, automation, and maintenance in public lighting infrastructure. Traditional street lights often waste electricity because they operate on manual or timer-based control and require time-consuming manual fault detection. To address this, the proposed system uses an LDR sensor and an Arduino Uno microcontroller to automatically turn street lights ON at night and OFF during daylight conditions.

In addition to automatic control, the system includes a real-time fault detection mechanism that identifies issues like lamp failure or circuit breaks and immediately triggers a buzzer alert for maintenance teams. This helps reduce downtime and improves safety.

The project aims to create a low-cost, scalable, and energy-efficient solution suitable for smart cities, campuses, highways, industrial areas, and rural regions. The methodology includes sensor-based light detection, relay control, microcontroller programming, fault monitoring, and alert generation.

Testing results show that the system responds quickly (about 1.5–2 seconds for switching), detects faults in under 500 ms, and achieves around 58% energy savings compared to conventional systems, with no false

Conclusion

This paper presented a Real-Time Street Light Monitoring, Control, and Fault Detection System designed to improve energy efficiency and maintenance management in public lighting applications. The developed system successfully automated the operation of street lights using an LDR sensor and Arduino Uno microcontroller, thereby eliminating the need for manual control. The prototype effectively switched street lights according to surrounding light conditions and significantly reduced unnecessary power consumption. In addition, the integrated fault detection mechanism successfully identified lamp failures and circuit interruptions within a short response time and generated immediate buzzer alerts for maintenance personnel. Experimental results confirmed stable system operation under different environmental conditions. The developed model achieved automatic switching response times between 1.5 and 2 seconds and fault detection within 500 milliseconds while providing approximately 58% energy savings compared to conventional street lighting systems. The system is economical, reliable, and suitable for practical implementation in smart cities, industrial areas, campuses, highways, and rural regions. Future developments may include wireless communication, loT-based monitoring, solar energy integration, and cloud-based maintenance systems to further improve efficiency and automation.

References

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Copyright

Copyright © 2026 Yuvraj Rajput, Prof. P. D. Nimbalkar , Harshal Shelke , Atharv Sawant , Sanskruti Misal , Rohan Chincholkar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.