• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.255-261
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• 2020

As the accidents of cargo and passenger carrying ships occur, the stress faced by the vessel users is increasing. The risk factors for accident deterioration in remote marine area are stronger than those in road accidents, and therefore the need for safety control is greatly emphasized. To overcome such issue, a lot of effort has been made in terms of conducting research and development of the passengers and freights location tracking system. However, the inner bulkhead structures are made of aluminum/steel which is a difficult material to transfer location information through. This study aims to measure the receiving rate of LoRaWAN signal inside the aluminum/steel bulkhead structures with variation in reception strength and distance. The test was taken place at platforms with 6T and 8T enclosures to reflect the same conditions found in fishery patrol boats. The receiving rate of through-the-wall communication at 10M distance turned out to be 86% in case of using two 6T enclosures, and 73% in case of using one 8T enclosure. The result showed that the receiving rate was more affected by the thickness rather than the number of enclosures.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.1-7
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• 2020

The demand on the underwater communications is extremely increasing in searching for underwater resources, marine expedition, or environmental researches, yet there are many problems with the wireless communications because of the characteristics of the underwater environments. Especially, with the underwater wireless networks, there happen inevitable delay time and spacial inequality due to the distances between the nodes. To solve these problems, this paper suggests a new solution based on ALOHA-Q. The suggested method use random NAV value. and Environments take reward through communications success or fail. After then, The environments setting NAV value from reward. This model minimizes usage of energy and computing resources under the underwater wireless networks, and learns and setting NAV values through intense learning. The results of the simulations show that NAV values can be environmentally adopted and select best value to the circumstances, so the problems which are unnecessary delay times and spacial inequality can be solved. Result of simulations, NAV time decreasing 17.5% compared with original NAV.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.280-283
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• 2019

통신기술이 1 세에서 5 세대로 발전하는 동안 해상물류의 핵심인 컨테이너는 기능상의 큰 발전없이 과거에 머물러 있다. 이에 본 논문에서는 컨테이너의 위치 및 상태 정보를 수기로 관리하던 기존의 방식에서 벗어나 IoT 장비를 활용해 실시간 위치 파악, 상태 모니터링 및 자동화 등을 통해 물류의 가시성을 확보하고 컨테이너를 효율적으로 재배치함으로써 비용 절감 및 새로운 서비스 창출하기 위한 스마트 컨테이너를 제안한다. 부가적으로, 태양열판을 이용한 전원공급, 펠티어 소자를 이용한 냉방기능을 제공함으로써 신선 식품 배송의 핵심인 풀 코드 체인(Full Cold Chain) 플랫폼으로 활용범위를 넓히고자 한다.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.867-874
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• 2021

The IoT (Internet of Things) technology is rapidly becoming an important consideration in many engineering fields in the current 4th industrial era. In recent years, the concepts of digital shipbuilding and smart factories have been adopted as trends in shipyards. However, there is active interest in research on implementing autonomous driving in autonomous vehicles and airplanes, which is currently available in commercial form in a limited capacity. The present study is regarding the path-tracking performance of a boat to accomplish an autonomous driving mission using a flight controller (FC) and real-time kinematic (RTK) global positioning system (GPS) based on an open-source Ardupilot; an actual sea test is also performed using this system on a calm lake. The boat's mission is to evaluate the maneuverability of the self-driving process to a specific point and returning to the home position. For a given speed, the difference between the preset mission trajectory and actual operational trajectory was analyzed, and a series of studies were conducted on the applicability of the system to ships. In addition, the movements and maneuverability of the OmniX-type hull with four propellers were investigated, and the driving path-tracking performance was observed to increase by a maximum of 48%.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.125-138
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• 2016

Currently, there is increasing demand for weather information, however, providing meteorology and climate information is limited. In order to improve them, supporting the meteorology and climate big data platform use and training the meteorology and climate big data specialist who meet the needs of government, public agencies and corporate, are required. Meteorology and climate big data requires high-value usable service in variety fields, and it should be provided personalized service of industry-specific type for the service extension and new content development. To provide personalized service, it is essential to build the collaboration ecosystem at the national level. Building the collaboration ecosystem environment, convergence of marine policy and climate policy, convergence of oceanography and meteorology and convergence of R&D basic research and applied research are required. Since then, demand analysis, production sharing information, unification are able to build the collaboration ecosystem.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1349-1354
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• 2021

An All-in-one LED lantern is a light device to determine the fairway of ships in operation. The current all-in-one LED lantern powered by solar energy is challenged by insufficient power capacity due to limited sun hours. This article presents an all-in-one 9-Nautical mile LED lantern driven by solar and wind power that is abundant maritime renewable energy. Furthermore, the remote smart monitoring system is developed. A smart control system capable of remote control of the lantern was implemented by using the LED lantern device and monitoring system as IoT. This technology that realtime condition monitoring and remote control are developed for safe ship navigation. We expect that maintaining the accuracy and consistency of LED lanterns prevents marine accidents and reduces social costs.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.314-322
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• 2022

During the shipbuilding process, many blocks are moved between shipyard workshops by block carrying vehicles called a transporter. Because block logistics management is one of the essential factors in enhancing productivity, it is necessary to manage block information with the transporter that moves it. Currently, because a large amount of data per day are collected from sensors attached to blocks and transporters via IoT infrastructure installed in shipyards, automated methods are needed to analyze them. Therefore, in this study, we developed an algorithm that can automatically match the transporter and the working block based on the GPS sensor data. By comparing the distance between the transporter and the blocks calculated from the Haversine formula, the block is found which is moved by the transporter. In this process, since the time of the measured data of moving objects is different, the time standard for calculating the distance must be determined. The developed algorithm was verified using actual data provided by the shipyard, and the correct result was confirmed with the distance based on the moving time of the transporter.

• Journal of IKEEE
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• v.25 no.1
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• pp.193-200
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• 2021

In order to prevent illegal fishing and reduce lost fishing gear, it is necessary to develop a constant and continuous fishing gear monitoring system in the marine environment. In this paper, we design a long-term operational, reliable system model with communication coverage of more than 25Km considering the reality of gradually expanding fishing activity due to the depletion of fishery resources and marine environments. The design results are implemented to verify the operability of the system by separating the communication success rate of SKT and private LoRa networks and verifying the control function of each control system through the collected location information, respectively.

• Journal of IKEEE
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• v.27 no.3
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• pp.225-233
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• 2023

This paper implements a system that monitors human body lifting information in the event of a marine accident. The monitoring system performs ultrasonic communication through a lifting device controller that transmits underwater environment information, and LoRa communication is performed on the water to provide GPS information within 10 km to the control center or mother ship. The underwater lifting controller transmits pneumatic sensor, gyro sensor, and temperature sensor information. In an environment where the underwater conditions increase by one atmosphere of water pressure every 10m in depth, and the amount of air in the instrument decreases by half compared to land, a model of a 60kg underwater mannequin is used. Using one 38g CO2 cartridge in the lifting appliance SMB(Surface Maker Buoy), carry out a lifting appliance discharge test based on the water level rise conditions within 10 sec. Underwater communication constitutes a data transmission environment using a 2,400-bps ultrasonic sensor from a depth of 40m to 100m. The monitoring signal aims to ensure the safety and safe human structure of the salvage worker by providing water depth, water temperature, and directional angle to rescue workers on the surface of the water.