• Title/Summary/Keyword: Marine IoT

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Implementation of Human Positioning Monitoring Device for Underwater Safety (수중안전을 위한 인체 위치추적 모니터링 장치 구현)

  • Jong-Hwa Yoon;Dal-Hwan Yoon
    • 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.

Development of Deep Learning Model for Detecting Road Cracks Based on Drone Image Data (드론 촬영 이미지 데이터를 기반으로 한 도로 균열 탐지 딥러닝 모델 개발)

  • Young-Ju Kwon;Sung-ho Mun
    • Land and Housing Review
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    • v.14 no.2
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    • pp.125-135
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    • 2023
  • Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

A Study on Capacity of Electric Propulsion System by Load Analysis of 6,800TEU Container Ship (6,800TEU 컨테이너선의 부하분석을 통한 전기추진시스템 용량 연구)

  • Jang, Jae-Hee;Son, Na-Young;Oh, Jin-Seok
    • Journal of Navigation and Port Research
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    • v.42 no.6
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    • pp.437-445
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    • 2018
  • IMO (International Maritime Organization) has been strengthening the regulations of ship emission gas such as sulfur oxides (SOX), nitrogen oxides (NOX) and carbon dioxides (CO2) to protect the marine environment. Especially, ECA (Emission Control Area) has been set and operated in the USA and US. As a countermeasure against these environmental regulations, the demand for environmentally, friendly and highly efficient vessels has led to a growing interest in technology related research with respect to electric propulsion systems capable of reducing exhaust gas. Container ships were excluded from the application coverage of the electric propulsion systems for reasons of operation at economical speed. However, in the future, the need for electric propulsion system is expected to rise, because it is easy to monitor and control so that it can be an applicate to smart ship which are represented by fourth industrial revolution technology. In this study, research was carried out to design a generator and battery capacity through the load analysis of the 6,800TEU container ship to apply the electric propulsion system of the container ship. A capacity design based on the load analysis has an advantage that the generator can be operated in a high efficiency section through the load distribution control using the battery.

Service Platform Design for Smart Environment Disaster Management (스마트 환경재해 관리를 위한 서비스 플랫폼 설계)

  • Weon, Dalsoo
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.3
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    • pp.247-252
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    • 2018
  • The problem of the environment is urgently coming to the world as a problem that humanity must solve. In particular, Korea is directly affected by air pollution and marine pollution due to its geopolitical position with China, and is also exposed to a great deal of pollution due to air, water, soil, and weather. In this situation, due to the disconnection between the management domain / service (system) related to the environment, the ability to quickly identify causes and cope with situations in the event of environmental pollution or disasters is weak, and duplication and investment are being faced. The development of a service platform for smart environment disaster management is designed to detect environmental disasters in an early stage through the management of smart environment disaster management at the national level, It will be a way to predict complex environmental disasters.

Development of Reefer Container Real-time Management System (실시간 냉동컨테이너 관리 시스템 개발)

  • Choi, Sung-Pill;Jung, Jun-Woo;Moon, Young-Sik;Kim, Tae-Hoon;Lee, Byung-Ha;Kim, Jae-Joong;Choi, Hyung-Lim;Lee, Eun-Kyu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.12
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    • pp.2917-2923
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    • 2015
  • In spite of a recent trend of container ships becoming larger in size, the current circumstance is that managing reefer containers marine transportation is being mostly dependent upon manpower. Particularly, in the case of bad weather or nighttime, reefer containers are not being monitored due to lack of safety device. For the purpose of reducing such risk, IMO is recommending a system using PLC but the system is not being used. In addition, they are still relying on manpower for control and reliability of freight in transit is decreasing due to lack of information during marine transportation for every subject related to freight as well as shipper. Accordingly, the purpose of this paper is to propose a real-time reefer container management system to effectively control all reefer containers widely being used across the world.