By: Sahal Shoukathali, Anusree M., Muhammed Vasil, Abhishek Ashok, and Fousiya K.
1-4-Student, Department of Electrical and Electronics
Engineering, College of Engineering Trikaripur, Kasaragod,
Kerala, India
5-Assistant Professor, Department of Electrical and Electronics
Engineering, College of Engineering Trikaripur, Kasaragod,
Kerala, India
Electric hazards associated to transmission lines are a big worry when negotiating India’s complex
electrical distribution network. According to estimates from the National Crime Records Bureau, about
one lakh individuals have perished from electrocution in only the last ten years. The average yearly
death toll increased from approximately 11,000 to 12,500 between 2021 and 2025. According to CEI Electrical. Accident Statistics, it has reached 13,855 by 2023. Transmission line mishaps, especially in
the LT Line, are a significant contributing element to these disasters. The conventional safety system
does not provide sufficient safety and cannot keep up with new technology developments. Our
innovative method seeks to enhance power distribution and avoid accidents by quickly identifying issues
on the transmission lines. The dual-post system is made up of Node-MCU controllers and Raspberry Pi
(RPI) boards. RPI coordinates data processing, street light regulation and central control. The wireless
communication, line break detection and street light activation are all controlled by the Node-MCU.
Relay-controlled street lights are efficient in adjusting both human inputs and external circumstances.
The Node-MCU’s potentiometer-based circuit quickly identifies and logs line breaks. Enhancing theft
detection, a current sensor tracks the load on a light that is actuated by a push button. For prompt
action, RPI receives real-time data on theft attempts and line breaks. Users are empowered with remote
control of street lights and theft notifications; thanks to seamless Android app integration. We can save
important human lives and avoid accidents brought on by electrical hazards by putting this technology
into practice.
Keywords: IoT, line breakage detection, accident prevention, fault location detection, remote street
light control
Citation:
Refrences:
1. Jianxiong Wu, Wei Du, Jiaying Wang, Guozhu Yang and Yajie Zhao. Application of Power
Internet of Things in Online Monitoring of Transmission Lines. IEEE SCOUT. 2023; 19-5p.
2. Hengyu Yang. Transmission Line Fault Detection Based on Multi-layer Perceptron. IEEE
BDICN. 2022; 5p.
3. Jennica Astronomo, Mariel Dane Dayrit, Cristopher Edjic Jr, Engr. Richard T. Regidor.
Development of Electricity Theft Detector with GSM Module and Alarm System.IEEE
HNICEM. 2020; 5p.
4. Fatih Ertam, Ilhan Firat Kilincer, Orhan Yaman, Abdulkadir Sengur. A New IoT Application
for Dynamic WiFi based Wireless Sensor Network. IEEE ICEE. 2020; 4p.
5. Vineeth N and P Sreejaya. High Impedance Fault detection in Low Voltage Distribution
Systems Using Wavelet and Harmonic Fault Indices. IEEE PESGRE2020. 2020; 6p.
6. Ehnaish Aburaghiega, Mohamed Emad Farrag, Mohamed Mahmuod Gouda. On-line
Condition Monitoring of Power Transformer Health Status Enforced by Temperature and
Electrical Signatures. IEEE MEPCON. 2019; 521-6p.
7. Subash Chandar Athikessavan, Elango Jeyasankar, Sai Srinivas Manohar, Sanjib Kumar
Panda. Inter-Turn Fault Detection of Dry-Type Transformers Using Core-Leakage Fluxes.
IEEE TRANSACTIONS ON POWER DELIVERY. 2019; 34(4). 1230-11p.
8. HUA Guanghui, CHEN Mingjia, LIU Haixuan, YE Rongbo. Research and Application of
Monitoring Method of Small Current Grounding Fault in Distribution Line Based on Cloud
Computing. IEEE CICED. 2018; 7p.
9. Abdul Qayyum Khan, Muhammad Sarwar, Qudrat Ullah, Sufi Tabassum, Gul Naeem Iqbal.
IFAC-PapersOnLine. 2018; 51(24), 1356-8p.
10. Rohit R Pawar and Dr. S B Deosarkar. Health Condition Monitoring System For Distribution
Transformer Using Internet of Things. IEEE ICCMC. 2017; 117-6p.
11. Andi Adriansyah, Akhmad Wahyu Dani, Gerri Irman Nugraha. Automation Control and
Monitoring of Public Street Lighting System based on Internet of Things. IEEE ICECOS.
2017; 231-6p.
12. Velhal Geeta Vilas, Dr. V Muralidhara, Avani Pujara, S.M. Bakre. A Diagnosis of Fault
Location System for Electrical Transmission and Distribution Network. IEEE ICESA. 2015;
163-4p.
