IoT-Driven AI Roboat System for Advancing Water Pollution Control Through Intelligent Water State Monitoring and Debris Removal

Water pollution poses a significant threat to ecosystems and human health, especially in countries like Bangladesh where water bodies are heavily contaminated with plastic and industrial waste. This paper presents the design and implementation of a floating waste collection boat with water quality monitoring system. The system integrates temperature, turbidity, and Total Dissolved Solids (TDS) sensors to provide real-time water quality data visualization using Blynk web console. The boat utilizes a catamaran hull and is controlled via Radio Frequency (RF) through a mobile phone, with an efficient conveyor belt for waste collection. A waste detection model using YOLOv11 is trained to detect floating wastes for an effective waste management and environment monitoring, achieving mean average precision (mAP) of 77.6 %, precision of 75.9 %, and 75.8 % of recall. This system proves to be scalable, low-cost, and supports sustainable waste management.