AI-Assisted Smart Water Pump Management System Using ESP32-CAM and Edge Vision Analytics

The AI-Assisted Smart Water Pump Management System Using ESP32-CAM and Edge Vision Analytics is an intelligent water management solution designed to automate water pumping operations through real-time visual monitoring and edge-based decision-making. The system utilizes an ESP32-CAM module to continuously observe water storage tanks, reservoirs, irrigation channels, or water distribution systems and analyze visual data locally using embedded image-processing techniques.

Unlike conventional water level controllers that rely solely on contact-based sensors, the proposed system employs Edge Vision Analytics to assess water conditions, monitor tank levels, detect overflow situations, identify dry-run conditions, and evaluate pump operational status. Based on the analyzed information, the ESP32-CAM autonomously controls a relay-driven water pump, ensuring efficient water utilization and preventing resource wastage.

The system incorporates a battery-backed power architecture consisting of rechargeable 3.7V lithium batteries, a Battery Management System (BMS), and a buck converter, enabling reliable operation even during power interruptions. The integrated monitoring framework can also detect abnormal operating conditions such as prolonged pump operation, insufficient water availability, or potential pump failure and generate alerts for preventive maintenance.

Through IoT connectivity, users can remotely monitor water levels, pump status, battery condition, and system performance using a smartphone or web dashboard. The proposed solution supports smart agriculture, domestic water management, industrial water distribution, and sustainable water conservation initiatives.