Real Time Predictive Diesel Level Monitoring in a Base Transceiver Station to Mitigate Operational Downtime

Real-time Diesel Level Monitoring System presents a solution to observe diesel levels at off grid remote base transceiver stations (BTS). Leveraging Internet of Things (IoT) technology, the system employs an Arduino Uno, sensor for data collection, interfaced with a capacitance sensor to measure fuel levels accurately. Additionally, an ESP8266 Wi-Fi module is used to facilitate remote connections, enabling seamless communication between the sensor and a central server. The operational flow is triggered by initializing the hardware, and then collection of data from the relevant sensors. The ESP8266 Wi-Fi module establishes a remote connection, transmitting the collected data to the server. At the server end, the data is received, processed and the information is stored in MySQL database, facilitating efficient retrieval and analysis. The frontend visualization provides a user-friendly interface, displaying real-time diesel level data on a dashboard. Users can interact with the system by predicting fuel levels through the "Predict" feature. This prediction was actualized using the linear regression algorithm to estimate the time left to exhaust the diesel at the BTS site. The system's architecture harmonizes hardware components, server-side processing, and frontend visualization to create an integrated and efficient fuel monitoring solution. The essence of this work can be traced to its ability to reduce down time that may arise due to fuel shortage, improve energy management and enhance operational efficiency at remote BTS sites providing valuable insights for monitoring and managing diesel resources.