Development of an Integrated Water Body Surveillance System for Environmental Monitoring and Resource Management

A cost-effective solution is sought for the tracking and reporting of maritime vessels, including boats, barges, dinghies, etc., within a port's water limits, regardless of the specific port. The solution should also address the continuous monitoring of potential encroachments within the port limits and provide timely reporting. Additionally, a comprehensive Management Information System is required to manage and analyze data related to violators, encroachments, and other relevant activities—The project presents a cost-effective solution for maritime vessel tracking and reporting by introducing an autonomous boat equipped with LiDAR for obstacle detection. Integrating a YOLOv8-based machine learning model, the boat efficiently classifies diverse vessels within the port. Complementing this, an Optical Character Recognition (OCR) system identifies hull numbers, cross-verifying their presence in the port, and consolidates all pertinent data on a web server. This holistic approach addresses the challenges of monitoring vessel activities, detecting encroachments, and managing information pertaining to violators within port limits, offering a streamlined and technologically advanced solution for effective port management and security