• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.362-365
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• 2022

With the development of the 4th industrial revolution technology, smartization in various fields is accelerating. The shipping and logistics industry is also promoting smartization by combining advanced new technologies such as digital twin, Internet of Things, and artificial intelligence. In Korea, the Ministry of Maritime Affairs and Fisheries is promoting a strategy to spread the smart shipping logistics system in line with the changing global shipping logistics trend, and through this, it is creating a foundation for smart shipping logistics. This study aims to present the concept of a communication tool that recognizes the importance of communication between each logistics entity and exchanges opinions between logistics entities in a virtual digital twin environment to cope with the changing shipping logistics process. In addition, for the development of these communication tools, this study derive a software design model, including architecture.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.299-305
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• 2015

Modbus is a serial communications protocol, it has since become a practically standard communication protocol, and it is now a commonly available means of connecting industrial electronic devices. Therefore, it can be connected with all devices using Modbus protocol to the measurement and remote control on the ships, buildings, trains, airplanes and etc.. In this paper, we add the Modbus communication protocol to the existing lighting controller sensitivity to enable verification and remote control by external environmental factors, and also introduces a fuzzy inference system was configured by external environmental factors to control LED lighting. External environmental factors of temperature, humidity, illuminance value represented by the LED through a fuzzy control algorithm, the values accepted by the controller through the sensor. Modbus is using the RS485 Serial communication with other devices connected to the temperature, humidity, illumination and LED output status check is possible. In addition, the remote user is changed to enable it is possible to change the RGB values in the desired color change. Produced was confirmed that the LED controller output is based on the temperature, humidity and illumination.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.421-426
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• 2018

With regard to LED lighting devices which have currently been commercialized, LED operating sequences are being sold in a fixed state. In such a state, the external environmental factors are not taken into consideration as only the illumination environment application is considered. Currently, it is difficult to create an optimal lighting environment which can adapt to changes in external environmental factors in the ship. Therefore, it was concluded that there is a need to input the external environment value so that the optimal illumination value can be reflected in real time in order to adapt more organically and actively to the change of external environmental factors. In this paper, we used a microprocessor as an integrated management system for environmental data that changes in real time according to existing external environmental factors. In addition, a controller capable of lighting control of RGB LED module by combining fuzzy inference system. For this, a fuzzy control algorithm is designed and a fuzzy control system is constructed. The distance and the illuminance value from the external environment element are input to the sensor, and these values are converted to the optimum illumination value through the fuzzy control algorithm, and are expressed through the dimming control of the RGB LED module and the practical effectiveness of the fuzzy control system is confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.193-201
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• 2021

The welding has a high proportion of the production and drying of ships or offshore plants. Non-destructive testing is carried out to verify the quality of welds in Korea, radiography test (RT) is mainly used. Currently, most shipyards adopt analog-type techniques to print the films through the shoot of welding parts. Therefore, the time required from radiography test to pass or fail judgment is long and complex, and is being manually carried out by qualified inspectors. To improve this problem, this paper covers a platform for scanning and digitalizing RT films occurring in shipyards with high resolution, accumulating them in management servers, and applying artificial intelligence (AI) technology to detect welding defects. To do this, we describe the process of designing and developing RT film scanning equipment, welding inspection information integrated management platform, fault reading algorithms, visualization software, and testing and verification of each developed element in conjunction.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.606-614
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• 2020

In this paper, we analyze the influences of ship traffic and marine weather information on underwater ambient noise. Ambient noise is an important environmental factor that greatly affects the detection performance of underwater sonar systems. In order to implement an automated system such as prediction of detection performance using artificial intelligence technology, which has been recently studied, it is necessary to obtain and analyze major data related to these. The main sources of ambient noise have various causes. In the case of sonar systems operating in offshore seas, the detection performance is greatly affected by the noise caused by ship traffic and marine weather. Therefore, in this paper, the impact of each data was analyzed using the measurement results of ambient noise obtained in coastal area of the East Sea of Korea, and public data of nearby ship traffic and ocean weather information. As a result, it was observed that the underwater ambient noise was highly correlated with the change of the ship's traffic volume, and that marine environment factors such as wind speed, wave height, and rainfall had an effect on a specific frequency band.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Food Science and Industry
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• v.51 no.4
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• pp.278-301
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• 2018

Although more than 80% of living organisms are found in marine ecosystems, only less than 10% of marine resources have been utilized for human food consumptions and other usages. It is well known that marine resources (fish, shellfish and algae) have exceptional nutritional properties; however, their functional characteristic has not been completely discovered. It is believed that metabolites (organic compounds, proteins, peptides, lipids, minerals, etc.) play an important role to show its biological properties. Marine proteins and peptides are considered to be future drugs due to their excellent biological activities with a fewer adverse side effect. Marine peptides show several biological activities, including antimicrobial, antioxidant, anti-inflammatory, anti-cancer, anti-viral, anti-tumor, anti-diabetic, anti-hypertensive, anti-coagulant, immunomodulatory, appetite suppressing and neuroprotective effects. Therefore, the pharmaceutical, nutraceutical, and cosmeceutical companies have been paid attention to the marine peptides to commercialize into products. This current review mainly focused on the above mentioned biological activities of marine peptides and protein hydrolysates as a functional food and pharmaceutical applications. To commercialize these materials in industrial level required large quantity in high-purity level, and it is complicated to produce huge quantity from the marine resources due to insufficient raw materials, unavailability of raw materials through a year, hinder the growth with geographical variations, and availability of compounds in extreme small quantities. The best solution for these issues is to introduce new modern technologies such as artificial intelligence robots, drones, submersibles and automated raw material harvesting vessels in farming industries instead of man power, which will lead to 4th industrial revolution.