Performance Analysis of Single Phase Induction Motor and Data Management Using IoT

This research presents an innovative approach for real-time monitoring and analysis of induction motors by integrating NodeMCU and Arduino microcontrollers. The system employs a NodeMCU board for sensor data acquisition, while an Arduino board handles control and data processing tasks. Sensors attached to the induction motor collect crucial performance metrics, including temperature, vibration, and current consumption. The collected data is formatted into a Comma-Separated Values (CSV) file by the Arduino microcontroller. A Spring backend system parses the CSV data and stores it in a MongoDB database, enabling efficient management and storage of the acquired sensor data. The system incorporates an analytics service built on the Spring framework, enabling users to perform basic statistical methods and generate insightful visualizations. This functionality enhances the system’s capability to extract valuable insights from the collected data, aiding in predictive maintenance, fault detection, and performance optimization of induction motors. The proposed system offers a comprehensive solution for real-time monitoring, data management, and analysis of induction motors, utilizing the combined capabilities of NodeMCU, Arduino, Spring, and MongoDB.