Smart IoT-Based Water Tank Monitoring using ESP2 and Mobile Application

Abstract

In rural, institutional or residential areas, water shortage and ineffective water tank monitoring continue to be major problems leading to unplanned water outages and ineffective water resource management. Conventional monitoring techniques involve manual inspections which are time-consuming, prone to human error and cannot offer real-time information. Therefore, the aim of this research is to create a Smart IoT-Based Water Tank Monitoring System that enables real-time monitoring of water level and TDS-based purity indicators via a mobile application. An ESP32 microcontroller, a waterproof ultrasonic sensor (JSN-SR04T) to measure water level, a Total Dissolved Solids (TDS) sensor to monitor water quality and a DHT11 sensor to measure ambient temperature and humidity are all integrated into the proposed system. Users can remotely access real-time information and receive low water level alarms by using Firebase Real-Time Database as a cloud platform to synchronize sensor data with a mobile application created with Android Studio. A prototype model is used to create a system that facilitates design, implementation, testing and iterative improvements throughout the development process. Meanwhile, functional and real-world tests were conducted to evaluate the sensor accuracy, data transmission reliability, application responsiveness, and system stability under various operating situations. According to the experimental findings, the proposed system effectively tracks water levels and TDS-purity parameters in real time, ensures reliable communication between the hardware and the cloud database, and promptly notifies users when water levels exceed pre-defined criteria. In addition to improving monitoring effectiveness and reducing manual intervention, the created system provides a feasible and affordable alternative for smart water resource management. To accommodate more smart water management applications, further research can improve the system by adding predictive analytics, historical data visualization, and other water quality criteria.