IoT Based Intelligent Low-Cost Anti-Collision Cum Monitoring System for Fishing Vessel

Abstract

The collision of fishing vessels is the problem many fishermen face. Due to the lack of a proper system, this problem persists and inevitable danger needs to be solved. Even after detecting the objects that may collide with the ship, the captain may not be able to manoeuvre it to safety. The system proposed here would be able to overtake the control of the motor and the propeller, to slow down the ship. In this paper, an ultrasonic sensor is used to detect objects; and the system alerts the crew of the danger ahead. A DC motor is also used to replicate the operation of the propeller of the ship and emergency braking system. For control and sensing parameters, Arduino Uno is used as the microcontroller. To display the Real-time data on the web, ESP-S01 (8266) module is used. The relative distance of the object is logged on thingspeak through the ESP module. A machine learning model is implemented using Support Vector Machine (SVM) to predict the appropriate direction to avoid collisions, The testing accuracy of the model is 98%. Similarly, the logs and live updates help the port rescue team to help the crew under distress.