MUMBAI, India, Feb. 6 -- Intellectual Property India has published a patent application (202541123552 A) filed by Rajalakshmi Engineering College, Chennai, Tamil Nadu, on Dec. 8, 2025, for 'autonomous surface vehicle system for intelligent aquatic debris detection and collection.'
Inventor(s) include Dr. P. Kumar; and Raghavan.
The application for the patent was published on Feb. 6, under issue no. 06/2026.
According to the abstract released by the Intellectual Property India: "The Autonomous Surface Vehicle System for Intelligent Aquatic Debris Detection and Collection is an innovative robotic solution designed to address the global challenge of water pollution through the integration of Artificial Intelligence (AI), Machine Learning (ML), I ntcrnet of Things (loT), and renewable energy technologies. The system functions as a selfnavigating, solar-powered surface vehicle capable of detecting, classifying, collecting, and monitoring floating debris in real time without human intervention. It employs an Al-based 'ision detection unit using Convolutional Neural Networks (CNNs) to analyze continuous image streams of water surfaces, accurately identifying debris types such as plastics, bottles, leaves. and waste materials while distinguishing them from natural entities like fish and n:getation. Once debris is detected, an onboard autonomous navigation system, driven by Ci PS. ultrasonic sensors, and Inertial Measurement Units (IMU), calculates an optimized path using advanced path-planning algorithms for efficient and collision-free movement. The mechanical debris collection mechanism, consisting of a conveyor or scoop assembly, retrieves and deposits the debris into a storage compartment monitored by load sensors. The system operates primarily on solar energy, with a smart power management unit distributing energy across all subsystems to ensure sustainability and long-term operation. Data from all modules, including operational status, debris volume, GPS coordinates, and battery performance, are transmitted via the loT communication interface to a cloud-based dashboaid, allowing for real-time monitoring, performance analytics, and mission scheduling. This continuous feedback loop also enables the AI algorithms to undergo self-learning and performance optimization over time. The invention offers a fully autonomous, eco-friendly, and intelligent alternative to manual water cleaning methods, significantly reducing human L'i"I(Jrt and environmental impact. By combining AI perception, loT connectivity, renewable energy utilization, and autonomous control, the system represents a major advancement in smart environmental robotics, providing a scalable and sustainable solution for global aquatic waste management and ecological conservation."
Disclaimer: Curated by HT Syndication.
