Optimization of Real Time Panel Trip Detection in Industrial Systems Using IoT and Mathematical Modeling

In modern setups, the detection and prompt acknowledgment of panel trips are crucial for ensuring the smooth operation and safety of critical systems. This presents a solution for implementing a Panel Trip Acknowledgment System using ESP32, WiFi client-server, and Telegram. The proposed system leverages the capabilities of ESP32, which provide built-in WiFi functionality, making them ideal for wireless communication that utilizes IOT. A client-server is established, where the ESP32 acts as a client, continuously monitoring the status of various panels within the industrial setup that incorporates power backup capabilities. Whenever a panel trip is detected, the ESP32 client sends a notification to a central server. To facilitate real-time notifications and easy accessibility, a Telegram bot is integrated into the system. The server, upon receiving a panel trip notification, triggers the Telegram bot to send an alert to authorized personnel or groups. This ensures that the relevant individuals are informed about the panel trip, enabling them to take appropriate action and minimize downtime. A mathematical model has been created to evaluate and improve the performance of the Panel Trip Acknowledgment System. Important components of the system are included in this model. The model determines the likelihood that a panel trip will occur during a monitoring interval and the likelihood that a panel trip will be detected during that time. It also calculates how long it takes to notice a panel trip and alert the appropriate people. The mathematical model offers important insights into the system's performance in various operational settings when combined with simulation data. The effectiveness of panel trip detection and warning can be increased by using this modeling approach to optimize crucial parameters like monitoring intervals and transmission periods. The research results enhance the Panel Trip Acknowledgment System's effectiveness in guaranteeing operational continuity and safety by assisting in its design and implementation in industrial settings. This study lays the groundwork for the implementation of cutting-edge IoT-based solutions for critical system monitoring and quick reaction in industrial settings.