IoT-Based Smart Transformer Monitoring and Protection System with Theft Detection and Cloud Analytics
Rachabathuni Mohan Rushi*1, Badakala Sai Kumar2, Beig Mehaboob Subhani3, Kukatlapalli Sandhya4 , Challgolla Sridhar5
1Student, Department of EEE,Bapatla Engineering College, Bapatla 522101,AP, India
2Student, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
3Student, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
4Student, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
5Associate Professor, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
Abstract — The power distribution transformers are one of the most crucial pieces of equipment used in electricity grids across the world. Failure of such devices due to any reasons ranging from electrical issues to thermal problems or even to theft may cause outages for many consumers, and result in losses. Transformer theft is still rampant in India and other developing countries, thus highlighting the need for remote monitoring systems.
This paper describes the development of a robust and cost-effective IoT-based solution for the purpose of real-time monitoring and protection of power distribution transformers. The proposed system employs an Arduino Uno as the controlling device, along with various types of sensors, including ACS712 Current Sensor, Voltage Divider, DS18B20 Temperature sensor, HC-SR04 Ultrasonic Sensor for estimation of oil level, and ADXL345 Accelerometer for detecting physical tampering of the transformer. A SIM800A module is used to send SMSs to maintenance personnel about potential threats to the transformer's operation, whereas the NodeMCU (ESP8266) module sends sensor readings online to the ThingSpeak IoT cloud platform.
Six parameters are continuously monitored by the system, namely: supply voltage, load current, transformer oil temperature, oil level, vibration/acceleration, and thermal status. In case of occurrence of any of these faults, threshold-based fault detection enables the system to automatically shut off the transformer via relay switching along with an alarm signal through the buzzer. The experimental findings revealed that the system was able to detect the occurrence of all faults including high voltage, low voltage, overload, high temperature, low oil level, and theft. Visualization of data was done on ThingSpeak dashboard throughout the experimentation period (March 25-April 04, 2026).
Key Words— Transformer monitoring, IoT, Arduino, NodeMCU, ThingSpeak, ADXL345, ACS712, DS18B20, GSM, Theft detection, Condition monitoring
