IoT Based Real Time Electric Line Fault Detection with Automated Cut Off System

Abstract

Electric line faults such as wire breakage or fallen conductors pose a serious threat to public safety, especially when the affected line continues to carry live current until manual intervention is performed. In conventional power distribution systems, fault identification and power isolation are often delayed due to dependence on human reporting and inspection, which increases the risk of accidents and fatalities. To overcome this limitation, this paper presents an IoT?based real?time electric line fault detection system with an automated cut?off mechanism.The proposed system continuously monitors the continuity of the electric line using a sensing mechanism interfaced with a microcontroller. When a line discontinuity occurs due to wire fall or breakage, the system immediately detects the fault and triggers an automated cut?off response to isolate the affected line, thereby enhancing public safety. Simultaneously, the fault status is transmitted to a web?based monitoring dashboard, which can be accessed through a laptop or control room system by Electricity Board (EB) officials.The system is designed to operate in real time, providing fast fault detection, reliable alert visualization, and automatic restoration once the line continuity is re?established. Experimental validation using a prototype demonstrates the effectiveness of the proposed approach in reducing response time and improving operational safety. The proposed system is simple, cost?effective, and suitable for smart power distribution and safety?critical applications.

Introduction

The text discusses the importance of electric power distribution systems and the safety risks that occur when faults such as broken or fallen power lines happen. Overhead electric lines are commonly used because they are inexpensive and easy to install, but they are exposed to weather conditions, lightning, storms, falling trees, vehicle accidents, construction activities, and aging infrastructure, which often cause damage. When a live wire falls on the ground, it poses a serious danger to people, animals, and vehicles because electricity may still be flowing through the damaged line.

Traditional fault detection methods mainly rely on manual inspection, public complaints, and protection devices such as relays, circuit breakers, and fuses. While these systems protect electrical equipment, they are not designed to ensure public safety, especially when faults occur in distribution lines. Existing systems often have delayed response times, lack real-time monitoring, and depend heavily on human intervention, which increases the risk of accidents.

To address these problems, the study proposes an IoT-based electric line fault detection system with an automated cut-off mechanism. The system uses sensors connected to a microcontroller to continuously monitor the condition of electric distribution lines. When a fault such as a wire break or disconnection is detected, the system automatically isolates the affected line and cuts off the power, preventing electricity from flowing through the damaged wire. At the same time, the system sends real-time alerts to a web-based dashboard, allowing Electricity Board officials to quickly identify the fault and take appropriate action.

The system architecture includes sensors, a microcontroller, an automated cut-off unit, and an IoT communication interface that transmits fault information to a monitoring platform. The algorithm continuously checks sensor readings, detects abnormal conditions, activates the safety cut-off, sends alerts, and restores the system to normal once the fault is fixed.

Experimental testing showed that the proposed system can detect faults quickly, automatically disconnect damaged lines, and provide real-time alerts, significantly reducing response time and reliance on manual inspection. Compared to traditional systems, it improves public safety, reliability, and efficiency in power distribution networks.

The system has several advantages, including real-time fault detection, automatic power isolation, remote monitoring, faster response, and cost-effective implementation. It can be applied in overhead power distribution lines, urban and rural electricity networks, smart grids, industrial power systems, and safety monitoring systems.

However, the prototype has limitations, such as dependence on sensor accuracy, network connectivity, and environmental conditions. Future improvements may include GPS-based fault location, mobile alert applications, cloud data storage, multi-line monitoring, and integration with advanced smart grid technologies.

Conclusion

This paper is about a system that uses the Internet of Things to detect faults on lines in real time. The system is designed to make people safer and to reduce the time it takes to respond to problems with power distribution. The system constantly checks if the electric lines are working properly it finds faults away and it automatically cuts off power to the line that has a problem. This helps to isolate the line that is affected. It prevents more damage. The Internet of Things system is really good, at detecting faults on lines and it helps to keep people safe.The integration of IoT technology enables real?time alert visualization through a web?based dashboard, allowing Electricity Board officials to monitor and respond to faults efficiently. Experimental results obtained from the prototype implementation demonstrate that the system is reliable, fast, and effective in handling fallen wire conditions.

References

[1] G. Andersson, “Power System Protection and Control,” IEEE Power Engineering Society, vol. 15, no. 4, pp. 45–52, 2019. [2] M. Kezunovic, “Smart Fault Location for Smart Grids,” IEEE Transactions on Smart Grid, vol. 2, no. 1, pp. 11–22, Mar. 2018. [3] A. Kumar and R. Singh, “Microcontroller?Based Power Line Fault Detection System,” International Journal of Electrical Engineering, vol. 7, no. 3, pp. 120–126, 2017. [4] S. Li, L. Da Xu, and S. Zhao, “The Internet of Things: A Survey,” Information Systems Frontiers, vol. 17, no. 2, pp. 243–259, 2015. [5] P. Siano, “Demand Response and Smart Grids—A Survey,” Renewable and Sustainable Energy Reviews, vol. 30, pp. 461–478, 2014. [6] R. Bayindir, I. Colak, and G. Fulli, “Smart Grid Technologies and Applications,” IEEE Transactions on Industrial Informatics, vol. 12, no. 6, pp. 235–244, 2016. [7] J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions,” Future Generation Computer Systems, vol. 29, no. 7, pp. 1645–1660, 2013. [8] H. G. Rodriguez et al., “Real?Time Monitoring of Power Distribution Systems Using IoT,” IEEE Access, vol. 6, pp. 32710–32720, 2018. [9] N. Mohan, T. M. Undeland, and W. P. Robbins, Power Electronics: Converters, Applications, and Design, 3rd ed., New York, NY, USA: Wiley, 2012. [10] ESP32 Technical Reference Manual, Expressif Systems, 2023.

Copyright

Copyright © 2026 M. Pradeep Kumar, I. Gowshik Raj, J. Sathya Priya. 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.