• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.307-316
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• 2011

The majority of maritime accidents happened by human factor. For that reason, navigation experts want to an intelligent support system for navigation safety, without officer involvement. The expert system which is one of artificial intelligence skills for navigation support is an important tool that a machine can substitute for an expert through the design of a knowledge base and inference engine using the experience or knowledge of an expert. Further, in the real world, a complex situation requires synthetic estimation with the input of experts in various fields for the correct estimation of the situation, not any one expert. In particular, synthetic estimation is more important for navigation situations than in other cases, because of diverse potential threats. This paper presents the method of knowledge fusion pertaining to navigation safety knowledge from various expert systems, using a blackboard system. Then we will show the validity of the method via a design and implementation of test system effort.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.310-315
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• 2014

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.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.635-642
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• 2023

With the development of artificial intelligence technology, drones are evolving beyond simple remote control tools into intelligent drones that perform missions autonomously. The importance of drones is gradually gaining attention due to the use of drones in overseas military conflicts and the analysis of the future operational environment in Korea. AMAD is proposed for the rapid development of intelligent drones. In order to develop intelligent software based on AMAD, an integrated development environment (IDE) that supports users with functions such as debugging, performance evaluation, and monitoring is essential. In this paper, we define the concepts of the development environment required for intelligent software development and describe the results of reflecting them in the design of the IDE and AMAD's agents, SVI and MPD, which are interfaced with the IDE.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.674-679
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• 2017

As the importance of the 4th industrial revolution and ICT technology increased, it became a software centered society. Existing software training was limited to the composition of the learning environment, and a lot of costs were incurred early. In order to solve these problems, a learning method using a web compiler was developed. The web compiler supports various software languages and shows compilation results to the user via the web. However, Web compilers that support artificial intelligence technology are missing. In this paper, we designed and implemented a tensor flow based web compiler, Google's artificial intelligence library. We implemented a system for learning artificial intelligence by building a meteorJS based web server, implementing tensor flow and tensor flow serving, Python Jupyter on a nodeJS based server. It is expected that it can be utilized as a tool for learning artificial intelligence in software centered society.

• Journal of Advanced Navigation Technology
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• v.18 no.1
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• pp.22-28
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• 2014

This paper presents the design and development of ECU simulator in order to verify automatic firmware update system of ECU SW on the vehicle. We designed and developed general-proposed ECU simulator as devide into HW and SW parts. HWadopt 32bit MPU, CAN, LIN, LCD, and touch-pad button to satisfy general-proposed ECU level. And SW constructed as finite-state-machine structure in order to support HW spec. We developed ECU manager which deliveries update data to verify validity of operation. And we tested ECU simulator with ECU manager. For test of validity of ECU simulator, we set 4 scenarios between ECU simulator and manager. As the result, we confirmed validity of operation in ECU simulator for automatic SW update system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1140-1147
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• 2022

With the development of digital technology, the marine environment is expected to change rapidly. In the case of autonomous vessels, technology is being developed in many countries, and the international community has begun to discuss ways to operate it. Changes in ships cause changes in the marine traffic environment and urge changes to aids to navigation. This study aims to analyze the cyber security management awareness of VTS personnel to improve the cyber security system for aids to navigation. To this end, the current status of cyber security management was reviewed with a focus on VTS, and a survey was conducted on VTS personnel. The survey analysis used the IPA methodology, and as a result of the analysis, a clear difference was observed in the perception of cybersecurity between those with experience in security and those without experience. In addition, technical measures related to cyber-attack detection and blocking should be implemented with the highest priority. The results of this study can be used as basic data for improving the cyber security management system for aids to navigation.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.296-301
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• 2019

Artificial intelligence is closely linked to our real lives, leading innovation in various fields. Especially, as a means of transportation possessing artificial intelligence, autonomous unmanned vehicles are actively researched and are expected to be put into practical use soon. Autonomous cars and autonomous unmanned aerial vehicles are required to equip accurate navigation system so that they can find out their present position and move to their destination. At present, the navigation of transportation that we operate is mostly dependent on GPS. However, GPS is vulnerable to external intereference. In fact, since 2010, North Korea has jammed GPS several times, causing serious disruptions to mobile communications and aircraft operations. Therefore, in order to ensure safety in the operation of the autonomous unmanned vehicles and to prevent serious accidents caused by the intereference, rapid situation judgment and countermeasure are required. In this paper, based on big data and machine learning technology, we propose a countermeasure system for GPS interference that supports decision making by applying John Boyd's OODA loop cycle (detection - direction setting - determination - action).

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.566-573
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• 2024

Applying autonomous driving technology to construction sites is very difficult due to safety issues. However, the application of various positioning and sensing devices, such as cameras and radars, to construction equipment is very active. Based on these technological trends, the government is making various efforts, including the Serious Accident Punishment Act and support for industrial safety management expenses, to reduce the incidence of accidents caused by construction equipment and industrial vehicles. And, related industries have been developing various safety equipment over the past few years and applying them to the field. In this paper, we investigate the current status of safety equipment-related technologies currently applied to construction equipment and industrial vehicles, and propose a direction for the development of safety technology in construction equipment based on artificial intelligence. Improving the safety and work efficiency of construction equipment based on the technology proposed in this paper should be reviewed through simulation in the future.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.16-21
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• 2014

In recent, the maritime traffic has increased with an increase in international trading volumes and the growing popularity of marine leisure activities. As increasing of maritime traffic, marine accidents happened continually and there are possibilities of accidents at sea. According to the analysis of marine accidents, most accidents occurred by human error of seafarers. To reduce the accidents by human error, the various assistance system for assist seafarers have been proposed. It is required to real-time data management method for applying to real-time system, but most proposed assistance system used off-line data for analysis. In this paper, we aim to build a navigation supporting system for providing safety information to deck officer with data of AIS(Automatic Identification System) and ARPA Radar(Automatic Radar Plotting Aids Radar), and proposed a management algorithm for real-time ship information with blackboard system and verified the validity.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.298-303
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• 2014

In this paper, we proposed a robust object extraction and tracking algorithm in the IR image sequence acquired in the sea environment. In order to extract size-invariant object, we detect horizontal and vertical edges by using DWT and combine it to generate saliency map. To extract object region, binarization technique is applied to saliency map. The correspondences between objects in consecutive frames are defined by the calculating minimum weighted Euclidean distance as a matching measure. Finally, object trajectories are determined by considering false correspondences such as entering object, vanishing objects and false object and so on. The proposed algorithm can find trajectories robustly, which has shown by experimental results.