American
International
University-
Bangladesh

Students & Supervisors

Abstract

INTRODUCTION The world’s oceans are essential to the planet’s ecological balance, climate regulation, and human prosperity. The health of the world's seas is increasingly under risk due to plastic pollution, as over 11 million metric tons of plastic enter marine environments annually [1]. This predicament has major implications for public health, the economy, and the environment. Traditional cleaning methods are often costly, time-consuming, and inefficient when applied widely. Modern robotics and artificial intelligence (AI) technologies provide innovative solutions to this global problem by using automation to detect, collect, and process marine debris [2]. This abstract examines the growing contribution of trash-collecting robots, drones, and skimmers to improving marine sustainability. It evaluates their technology, operational procedures, and efficacy in real-world scenarios, emphasizing how these technologies have the potential to completely transform ocean cleanup efforts. KEYWORDS: Ocean Cleanup, Artificial Intelligence, Sustainability, Marine Pollution, Drones, Robots. METHODOLOGY This evaluation integrates a multidisciplinary approach, combining literature review, case studies, and system performance analysis. Key technologies were analyzed across three categories. Here we are: AERIAL DRONES: The use of unmanned aerial vehicles, or UAVs, to map the distribution of garbage in the ocean is growing. Researchers examined studies on rotary and fixed-wing drones used by groups such as The Plastic Tide and The Ocean Conservancy. Image resolution, flight time, and the accuracy of AI-based garbage classification were among the parameters evaluated.[3] SELF-SUFFICIENT SURFACE SKIMMERS: We looked at devices like Clear Bot and The Ocean Cleanup's ""Interceptor"" to learn about AI integration [4]. In rivers and coastal areas, skimmers autonomously detect and gather floating debris using solar-powered propulsion and onboard sensors. TRASH-COLLECTING ROBOTS: The capacity of semi-autonomous and underwater robot technologies, such WasteShark and Sea Clear’s underwater drone system, to navigate and collect submerged garbage was investigated [5]. Key performance metrics were depth tolerance, collection efficiency, trash sorting systems, and sensor fusion techniques. The capacity of technologies like WasteShark's underwater and semi-autonomous robots and SeaClear's underwater drone system to navigate and collect submerged trash was assessed [6]. TECHNOLOGICAL LIMITATIONS: • High cost of development and maintenance. • Limited energy storage in solar or battery-powered systems. • Navigational challenges in rough sea conditions. • AI systems still need more training data for better obstacle avoidance. RESULTS In case of Aerial Drones when mapping hotspots for marine trash and tracking cleaning activities, aerial drones proved to be quite useful. In good weather, machine vision algorithms trained on neural networks such as YOLO were able to discriminate plastics from natural detritus with up to 92% accuracy [7]. Unfortunately, drones are better applicable for surveillance than active gathering because of their limited payload, wind interference and battery life. For Self-sufficient Skimmers illustrate great promise for self-sufficient trash removal in regulated settings including ports, rivers, and coastal waterways. For instance, the Ocean Cleanup's Interceptor gathered more over 100,000 kg of plastic in the Cengkareng Drain in Indonesia in just six months [8]. The best paths for collecting rubbish and avoiding obstacles were made possible by AI-assisted navigation. Solar-powered operation enhanced sustainability, while onboard sorting helped reduce the need for human intervention. Nevertheless, these skimmers faced challenges in high-wave conditions. Lastly, underwater & trash-collecting robots are similar to an aquatic Roomba, the WasteShark successfully gathered floating waste and microplastics from limited water bodies.

Keywords

Publication Details

• Type of Publication:
• Conference Name: LURS 2nd Student Research Conference 2025
• Date of Conference: 09/08/2025 - 09/08/2025
• Venue: Leading University, Sylhet
• Organizer: Leading University Research Society (LURS)