Optimizing Ship Safety Using SAR Images, Iot-Driven Weight Management, Obstacle Detection And Border Alert System

Abstract: This project focuses on developing a comprehensive system for ship detection, passenger monitoring, and maritime safety using Synthetic Aperture Radar (SAR) imagery and IoT-based automation. Initially the system  detects the ships using SAR images and employs an infrared (IR) sensor, connected to an ESP32 microcontroller, to count passengers boarding the ship. Once the passenger count exceeds a preset threshold, the system activates DC motors to automatically close doors.  underwater UV sensor detects obstacles, and a crack sensor monitors the ships structural integrity. To improve maritime security, the system incorporates RF modules to monitor border crossings and GPS tracking to trace the ship's location, even when network coverage is lost. Additionally, a sink detection mechanism is integrated to send alerts via Telegram if abnormal tilting or potential sinking is detected.​

Keywords: SAR images, RF Modules, ESP32 module, GPS, UV Sensors, IR Sensors, ADXL Sensors.