Smart RC Boat for Real Time Water Quality Monitoring

Abstract

This paper presents the design and implementation of a Smart RC Boat system for real-time water quality monitoring and pollution source prediction using machine learning. The system integrates multiple environmental sensors including pH, turbidity, temperature, conductivity, and total dissolved solids (TDS) with an ESP-32 microcontroller to collect and transmit data from aquatic environments. Wireless communication modules (HC-12 and Bluetooth), GPS, and a camera enable remote operation and geo tagged data acquisition. A web-based interface allows users to view sensor readings and input data into a machine learning model trained to classify pollution sources such as industrial discharge, sewage contamination, agricultural runoff, and algal blooms. The proposed system offers a low-cost, portable, and scalable solution for environmental monitoring, with potential applications in public health, aquaculture, and water resource management.