Bio-Inspired Marine Waste Collection System with Adaptive Suction Mechanism: Energy Optimization through Intelligent Waste Dimension Recognition

Marine pollution from synthetic and organic waste poses critical threats to aquatic ecosystems and human health. This research presents an innovative autonomous marine waste collection robot inspired by fish feeding biomechanics, integrating artificial intelligence, renewable energy systems, and adaptive mechanical design. The system employs a dual-chamber diaphragm-based vacuum mechanism capable of generating controlled negative pressure for targeted waste suction across multiple water layers including surface, suspended, and benthic zones. A computer vision system utilizing enhanced convolutional neural networks with spatial-spectral attention mechanisms achieves 94.2% accuracy in waste classification and detection under variable lighting conditions. The intelligent suction inlet, constructed from shape-memory alloy segments, dynamically adjusts its diameter from 2 to 25 centimeters based on waste dimensions, resulting in 42% energy reduction compared to fixed-aperture systems. Energy autonomy is achieved through hybrid renewable sources including 23% efficiency solar cells and ocean current converters, enabling carbon-neutral operation. Laboratory testing demonstrated waste collection rates of 2 kilograms per hour with energy consumption of 0.5 kilowatt-hours per kilogram, while open-water trials in the Persian Gulf confirmed 85% detection rates for micro plastics larger than 0.1 millimeters. This technology represents a paradigm shift in autonomous aquatic waste management, offering scalable solutions for oceanic, riverine, and lacustrine environments.