The Research of Navigation Safety based on Deep Learning

• Main Authors: YANG, SHIH-TING, 楊仕廷
• Other Authors: WEI, HUNG-CHE
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/yqwwvr

碩士 === 國立高雄科技大學 === 電訊工程系 === 107 === Taiwan is surrounded by the sea, the abundant fishery resources and diverse marine resources in the surrounding waters and the unique geographical location make the maritime transport vessels very frequent here. When the ship is sailing, it often affected by different factors such as restricted waters, sea conditions, weather conditions, helmsman's experience and the ship's own operating conditions. Furthermore, ships sailing on the sea often have external incident such as wind, waves, currents and tides, which cause the ship to be easily disturbed and deviate from the scheduled course. Therefore, it is necessary to have the ability of correcting the ship's route to ensure that the ship can avoid disasters with better navigation direction and speed immediately. There are many irresistible dangers in maritime navigation. If the duty officer is negligent or not action properly, it will lead to accidents such as collision, cuase the loss of life and property. In view of this, how to avoid the accidental collision of the ship has its urgency, and in order to reduce the mistake caused by the human operation factors, this paper applies the Automatic Identification System (AIS) data returned from the ship to research the safety of navigation. The main content of the research is to learn the characteristics of the existing AIS data through Big Data analysis technology and Deep Learning (DL) technology, by this way to learn the sailing characteristics of ships around Taiwan, then, designed a ship navigation safety prediction system based on the sailing characteristics of these ships. This system can effectively predict and analyze the navigation behavior and collision warning of sea vessels, and promote the safety and efficiency of navigation in Taiwan.