Taeho Hong

Development of a System for Transmitting a Navigator's Intention for Safe Navigation

For the past three decades, ship-to-ship collision accidents have steadily increased on the coast of South Korea by about 20% annually. Marine accidents have become more likely and more devastating in areas with increasing marine traffic and rising numbers of high-speed ships. Over 30% of the marine accidents in South Korea are concentrated in spring, since Korea’s coast is often covered in dense fog at this time of the year. Fog is generated when a large temperature range exists within a day, and this daily temperature range has increased due to abnormal weather conditions. This research proposed a system for transmitting a navigator’s intention utilizing electronic methods. A navigator’s intention was expressed on the electronic navigation chart for easier understanding of the surrounding situation, and the effectiveness of the system was verified through practical tests.

Development of an Embedded System for Ship선s Steering Gear using Voice Recognition Module

Recently, various studies had been made for automatic control system of small ships, in order to improve maneuvering and to reduce labor and working on board. To achieve efficient operation of small ships, it had been accomplished to rapid development of automatic technique, but the ship operation had been more complicated because of the need to handle various gauges and instruments. To solve these problems, there are examples to be applied to the speech information processing technologies which is one of the human interface methods in the system operation of ship, but the implementation of definite system is still incomplete. Therefore, the purpose of this paper is to implement the control system for ship steering using the voice recognition module.

Building a Fusion Information System for Safe Navigation

The International Maritime Organization has determined that more than 80% of maritime accidents are caused by human error. A variety of methods have been considered to reduce maritime accidents caused by such human error. Navigators operate by observing surrounding maritime situations and analyzing information using various navigational devices. This study proposes a system to ensure safe navigation by assisting navigators through the delivery of maritime safety information (MSI) between land and sea. In the future, supplementing the system through long-term on-the-ship tests is necessary by defining MSI in relation to maritime service portfolio regions.

Building an Algorithm for Compensating AIS Error Data

The domestic maritime environment shows higher frequency of maritime accidents amidst greater traffic volume arising from increasing international seaborne trade and maritime leisure activities. To reduce such maritime accidents, there exist various kinds of safety navigation devices in the ship bridge aimed to mitigate burdens of navigators and support their accurate decision making. Amongst is the AIS considered very important, which is an automatic tracking system to assist understanding of the circumstances in the vicinity by receiving information of other ships and also sending its own; where the information contains errors initially, however, such wrong information is periodically transmitted, accordingly giving rise to hindrance sometimes in decision making by shore operators or ship navigators at sea. This study is to propose the error data and field management algorithm using fuzzy theory toward improving reliability and accuracy in ship related information received from AIS.

Implementation of an Intelligent System for Identifying Vessels Exhibiting Abnormal Navigation Patterns

Vessels exhibiting abnormal navigation patterns (e.g., weaving in and out of courses or rotating in the same position) may have a serious impact on other vessels staying on normal courses. For this reason, ground VTS centers are keeping track of criminal vessels or damaged vessels in tandem with marine police. However, the number of available studies aimed at assisting the identification of seemingly apparent risk factors resulting from human errors has been next to nothing to date. In this respect, this study intends to implement an intelligent system that can identify vessels exhibiting abnormal navigation patterns based on fuzzy inference, in order to assist controllers and mates alike.

Implementation of an intelligent system for identifying vessels exhibiting abnormal navigation patterns

Vessels exhibiting abnormal navigation patterns (e.g., weaving in and out of courses or rotating in the same position) may have a serious impact on other vessels staying on normal courses. For this reason, ground VTS centers are keeping track of criminal vessels or damaged vessels in tandem with marine police. However, the number of available studies aimed at assisting the identification of seemingly apparent risk factors resulting from human errors has been next to nothing to date. In this respect, this study intends to implement an intelligent system that can identify vessels exhibiting abnormal navigation patterns based on fuzzy inference, in order to assist controllers and mates alike.