IoT-Based Autonomous Aquatic Surface Vehicle for Real-Time Water Quality Monitoring and Automated Fish Breeding Management

Abstract

Global aquaculture is transitioning from traditional, labor-heavy practices to technology-driven "Smart Farming" to meet the rising global demand for protein. This study addresses the critical challenges of mass fish mortality and operational inefficiency caused by inconsistent monitoring of parameters such as pH, dissolved oxygen (DO), and temperature. Here, this work proposes a Wi-Fi-controlled robotic platform centered on the ESP32 microcontroller, designed to operate as an Autonomous Surface Vehicle (ASV) within pond environments. The robot integrates a multi-sensor array for real-time environmental data acquisition and an onboard IP-camera module for live visual surveillance. Utilizing a dualpropulsion system for navigation and a specialized mechanical dispenser for automated feeding, the system allows farmers to manage pond conditions remotely via a mobile application. Data logging and automated alerts ensure early detection of water contamination, significantly reducing the risks associated with manual errors. Experimental results demonstrate that this IoT-based solution optimizes resource allocation, reduces operational costs, and maintains ideal growth conditions. This research provides a scalable, cost-effective framework for transforming traditional aquaculture into a technologically advanced, sustainable food production sector.