A Survey on Real-Time Water Surveillance Boat with Object Detection and Conveyor Belt Retrieval

Water pollution caused by floating waste such as plastics, bottles, and cans has become a growing environmental concern, posing serious threats to aquatic life and human health. Conventional cleaning methods are manual, labor-intensive, and inefficient for continuous or large-scale operations. To overcome these limitations, this paper presents a Real-Time Water Surveillance Boat with Object Detection and Conveyor Belt Retrieval, an autonomous system that integrates embedded control, computer vision, and mechanical automation for smart aquatic waste management. The system employs a Raspberry Pi as the central controller and a Pi Camera Module for real-time detection of floating debris using machine learning and computer vision algorithms. Upon detection, a motor-driven conveyor belt mechanism is activated to collect and store waste onboard, ensuring efficient and contactless retrieval. The system supports IoT-based monitoring for real-time data logging and remote supervision, enabling continuous tracking of debris detection events and system performance. Powered by rechargeable batteries with the provision for solar charging, the boat ensures energy- efficient operation suitable for lakes, rivers, and canals. This autonomous platform contributes to sustainable environmental management by reducing human effort, improving water quality, and promoting eco-friendly, intelligent waste retrieval.