Open AccessSafe distance reminder system on ship against port for the standing process using image processing
Author(s) -
Ari Wibawa Budi Santosa,
Ayu Hardianti,
Sereati Hasugian,
Imam Sutrisno,
Agus Khumaidi
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1175/1/012010
Subject(s) - dock , process (computing) , port (circuit theory) , computer science , convolutional neural network , real time computing , artificial intelligence , object (grammar) , signal (programming language) , computer vision , simulation , marine engineering , engineering , electrical engineering , programming language , operating system
Since ancient times, Indonesia has been known as a country that conducts trading activities. However, the number of accidents when the ship is about to dock is an indication of the need to improve the marine transportation system. The factors that cause accidents include human, technical and weather errors. Seeing these conditions and also related to the increasingly rapid development of technology, modern solutions for detecting objects using cameras can be developed. By using a PC as a video processor from a camera that works in real time and can classify several ship objects using the Convolutional Neural Network (CNN) method. As well as being able to estimate the distance of the object where the ship must turn off the engine before docked with the camera using Stereo Vision. and the results of the algorithm processing can be translated into a signal that will be sent to the harbormaster and also the ship that will dock as an output. Then the ship that will dock can find out the distance where the ship has to turn off the engine through the signal sent or siren. The average total accuracy of the system which is able to detect ships is 97.15%.