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Eco Rover: A Smart Vision Integrated Autonomous System for Sustainable Water Body Rehabilitation
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Plastic pollution in coastal waters isn't just an eyesore—it breaks down into microplastics that can enter the food chain and eventually end up on our plates. Researchers built "Eco-Rover," a solar-powered robotic boat that uses AI-powered cameras to spot floating plastic, scoop it up, compress it for storage, and even sprinkle eco-friendly nutrients back into the water to help aquatic plants recover. This kind of automated cleanup could make it faster and cheaper to tackle plastic pollution at its source, before it breaks down into the tiny particles that threaten both marine life and human health
Floating plastic waste has become a serious environmental problem that harms marine ecosystems and affects human health, particularly in coastal regions of Tamil Nadu such as Palk Bay, Pulicat Lake, Muthupet Lagoon, Pichavaram Mangrove Forest, and Thoothukudi, where slow-moving currents cause the accumulation of floating debris on the water surface. Manual cleaning methods are often slow, labor-intensive, and inefficient for large water bodies, highlighting the need for automated and intelligent solutions. This paper presents Eco-Rover, an autonomous robotic system designed for efficient surface-level plastic waste detection and removal while also supporting aquatic ecosystem restoration. The robot employs a catamaran-style floating mechanism with two buoyant pontoons connected by a rectangular platform to ensure stability and balanced load distribution. Dual propeller motors provide propulsion and maneuverability across the water surface. A front-mounted scoop mechanism with serrated edges collects floating plastic debris, which is guided through a 35–40° slanted plate into a load carrier chamber equipped with drain holes for water removal. Inside the chamber, a screw compactor driven by a low-speed, high-torque motor compresses the collected plastic to increase storage efficiency. For intelligent operation, a camera module mounted on a vertical stand captures images for real-time analysis using a Raspberry Pi vision system with the YOLOv8 algorithm, enabling accurate plastic detection. Navigation and obstacle avoidance are managed through an Arduino-controlled propulsion system integrated with ultrasonic sensors. Additionally, a fertilizer storage tank with a mini pump and rear micro-sprinkler system dispenses Liquid Seaweed Extract, an eco-friendly bio-stimulant that helps restore nutrient balance and promote aquatic plant growth after waste removal. By integrating mechanical waste collection, compression mechanisms, AI-based detection, and ecological restoration, the proposed Eco-Rover offers a scalable and sustainable approach for smart water-surface cleaning and environmental management.
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Smart Ocean Cleanup: An AI-Integrated Autonomous System for Marine Waste Management
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This paper presents an AI-powered autonomous boat system designed to detect and collect marine pollution — including plastics, oil spills, and microplastics — using deep learning image classification, IoT sensors, and robotic collection mechanisms. The system demonstrated over 94% accuracy for pollutant detection and classification across several AI models. While focused more broadly on ocean cleanup technology than on microplastic science specifically, it demonstrates how AI-integrated robotics could help address the practical challenge of removing plastic waste from ocean surfaces before it breaks down further.
Smart Water Boat Garbage Collector
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Researchers designed an automated boat system using ultrasonic sensors, a conveyor mechanism, and microcontroller-based navigation to collect floating plastic waste from rivers and lakes with minimal human intervention, demonstrating a low-cost automation approach to surface water cleanup.
Ocean and River Plastic Waste Detection Using Computer Vision
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Millions of tons of plastic pour into our oceans every year, much of it carried by rivers—but tracking where it comes from has always relied on slow, manual surveys. This study built an AI camera system that automatically spots and counts floating plastic waste from drone and shoreline footage with over 91% accuracy, offering a faster way to find pollution hotspots. Better tracking matters because plastic waste that lingers in waterways breaks down into microplastics, which end up in the fish and water we consume, making tools like this useful for guiding cleanup efforts before pollution reaches our food and water supply.
Smart Floating Waste Collector
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Researchers built a solar-powered floating robot that uses YOLO-based deep learning to detect plastic bottles, polythene bags, and aluminum cans on water surfaces in real time and automatically collects them via a motorized conveyor, demonstrating feasibility as a low-maintenance aquatic waste management prototype.
“WAVECLEAN” – An Innovation in Autonomous Vessel Driving Using Object Tracking and Collection of Floating Debris
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Researchers designed an autonomous vessel called WAVECLEAN that uses object-tracking technology to identify and collect floating marine debris, including plastics. The system combines camera-based detection with machine learning to navigate waterways and gather waste without human operation. The study demonstrates a technology-driven approach to addressing plastic pollution in harbors, rivers, and coastal areas.
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