• Title/Summary/Keyword: Maritime ICT

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Energy Efficient Route Search Using Marine Data (해양 데이터를 활용한 에너지 효율적인 최적 항로 탐색)

  • Kim, Seong-Ho;Jin, Kyo-Hong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.1
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    • pp.44-49
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    • 2020
  • Recently, one of the major issues of shipbuilding and marine is the reduction of air and marine pollution emission to ships. In response, the International Maritime Organization (IMO) has concluded an international convention (MARPOL) to prevent pollution from ships. A Annex Six of The Convention restricts and regulates air and marine pollution of ship from exhausting gases. To this end, it is required to apply EEDI (Energy Efficiency Design Indicators) to the construction of new ships, and to minimize the emission of environmental pollutants by recommending the application of EEOI (Energy Efficiency Operation Indicators) to operational ships. Therefore, in this study, we propose to calculate the grade of operating efficiency (EG) of ships based on actual operational data for transport ships and to provide energy-efficient optimal path search information through analysis of marine environment data.

Measurement and Analysis of 433 MHz Radio Wave for Drone Operation (드론 운용을 위한 433 MHz 전파 측정 및 분석)

  • Seong-Real Lee
    • Journal of Advanced Navigation Technology
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    • v.27 no.2
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    • pp.209-213
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    • 2023
  • Currently, 2.4 GHz and 5 GHz bands are used as frequencies for drone operation. In December 2019, the Ministry of Science and ICT newly allocated the 433 MHz band for the invisible long-distance operation of drones. However, since the 433 MHz band is the same as the previously allocated frequency band for amateur radio communication, interference cannot be avoided. Therefore, as a prerequisite for the development of a drone operation system based on the 433 MHz band, interference avoidance technology for this frequency band must be developed and applied. In this paper, we report the results of measurement and analysis of 433 MHz band signals necessary for the development of interference avoidance and reduction technologies for 433 MHz signals. The measurement and analysis of the 433 MHz band signal are performed through the spectrum measured at 5-minute intervals at three locations. Since the measurements and analyzes performed in this study considered spatial characteristics, temporal characteristics, and traffic characteristics, it is considered to be the basic data necessary for the development of interference avoidance technology in the 433 MHz band.

Construction of real-time remote ship monitoring system using Ka-band payload of COMS (천리안 위성통신을 이용한 실시간 원격 선박 모니터링 체계 구축)

  • Jeong, Jaehoon;Kim, Tae-Ho;Yang, Chan-Su
    • Korean Journal of Remote Sensing
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    • v.32 no.3
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    • pp.323-330
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    • 2016
  • Communication, Ocean and Meteorological Satellite (COMS) was launched in 2010 with three payloads that include Ka-band communication payload developed by Ministry of Science, ICT and Future Planning (MSIP) and Electronics and Telecommunications Research Institute (ETRI). This study introduces a real-time remote vessel monitoring system built in the Socheongcho Ocean Research Station using the Ka-band communication satellite. The system is composed of three steps; real-time data collection, transmission, and processing/visualization. We describe hardware (H/W) and software systems (S/W) installed to perform each step and the whole procedure that made the raw data become vessel information for a real-time ocean surveillance. In addition, we address functional requirements of H/W and S/W and the important considerations for successful operation of the system. The system is now successfully providing, in near real-time, ship information over a VHF range using AIS data collected in the station. The system is expected to support a rapid and effective surveillance over a huge oceanic area. We hope that the concept of the system can be fully used for real-time maritime surveillance using communication satellite in future.

Deep Learning Based Floating Macroalgae Classification Using Gaofen-1 WFV Images (Gaofen-1 WFV 영상을 이용한 딥러닝 기반 대형 부유조류 분류)

  • Kim, Euihyun;Kim, Keunyong;Kim, Soo Mee;Cui, Tingwei;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.293-307
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    • 2020
  • Every year, the floating macroalgae, green and golden tide, are massively detected at the Yellow Sea and East China Sea. After influx of them to the aquaculture facility or beach, it occurs enormous economic losses to remove them. Currently, remote sensing is used effectively to detect the floating macroalgae flowed into the coast. But it has difficulties to detect the floating macroalgae exactly because of the wavelength overlapped with other targets in the ocean. Also, it is difficult to distinguish between green and golden tide because they have similar spectral characteristics. Therefore, we tried to distinguish between green and golden tide applying the Deep learning method to the satellite images. To determine the network, the optimal training conditions were searched to train the AlexNet. Also, Gaofen-1 WFV images were used as a dataset to train and validate the network. Under these conditions, the network was determined after training, and used to confirm the test data. As a result, the accuracy of test data is 88.89%, and it can be possible to distinguish between green and golden tide with precision of 66.67% and 100%, respectively. It is interpreted that the AlexNet can be pick up on the subtle differences between green and golden tide. Through this study, it is expected that the green and golden tide can be effectively classified from various objects in the ocean and distinguished each other.

Analysis of Reliability of Weather Fields for Typhoon Maemi (0314) (태풍 기상장의 신뢰도 분석: 태풍 매미(0314))

  • Yoon, Sung Bum;Jeong, Weon Mu;Jho, Myeong Hwan;Ryu, Kyong Ho
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.5
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    • pp.351-362
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    • 2020
  • Numerical simulations of the storm surge and waves induced by the Typhoon Maemi incident on the south sea of Korea in 2003 are performed using the JMA-MSM forecast weather field, NCEP-CFSR reanalysis weather field, ECMWF-ERA5 reanalysis weather field, and the pressure and wind fields obtained using the best track information provided by JTWC. The calculated surge heights are compared with the time history observed at harbours along the coasts of Korea. For the waves occurring coincidentally with the storm surges the calculated significant wave heights are compared with the measured data. Based on the comparison of surge and wave heights the assessment of the reliability of various weather fields is performed. As a result the JMA-MSM weather fields gives the highest reliability, and the weather field obtained using JTWC best track information gives also relatively good agreement. The ECMWF-ERA5 gives in general surge and wave heights weaker than the measured. The reliability of NCEP-CFSR turns out to be the worst for this special case of Typhoon Maemi. Based on the results of this study it is found that the reliable weather fields are essential for the accurate simulation of storm surges and waves.

Estimation of Significant Wave Heights from X-Band Radar Using Artificial Neural Network (인공신경망을 이용한 X-Band 레이다 유의파고 추정)

  • Park, Jaeseong;Ahn, Kyungmo;Oh, Chanyeong;Chang, Yeon S.
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.6
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    • pp.561-568
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    • 2020
  • Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.

Correlation Analysis of Cause factor through Ship Collision Accident, and Cause factor Analysis through Collision Time (선박 충돌사고의 원인요소 간 상관관계 및 충돌시간에 따른 원인요소 분석)

  • Youn, Donghyup;Shin, Ilsik
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.1
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    • pp.26-32
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    • 2017
  • Enlargement and speed-up of a ship and diversification of ship's type have served to greatly increase the importance of marine transport means. It's reported that accident occurrence frequency of collision is high next to engine damage among the ship accident types, and that the accident ratio according to human factors is also high. In addition, ship accidents come to occur caused by complex cause factors rather than a sole cause factor, it is necessary to investigate the cause factors through the written verdict. This study proposed the cause factors of collision ship accident on the basis of human factors in collision ship accident among the written verdicts provided by the Korean Maritime Safety Tribunal, and inquired into the cause factor and effect through the correlation analysis of accident occurrence factors. Also, this study predicted the collision accident through analyzed the major cause factor of the occurrence at the zero minute when collision on the basis of the time taken from the time point of detecting collision of ships to the time point of collision occurrence. This study used commercial software-Statistical Package for Social Sciences (SPSS Ver21.0) to do correlation analysis. For time analysis, this study analyzed the cause factor and time by analyzing the time taken from the time point of detected ships to the time point of collision occurrence on the basis of the written verdicts. The study analysis showed that there were many cases of collision ship accidents occurrence caused by more than two sorts of cause factors, and that the case (zero minute) where there is no time to spare for collision avoidance accounted for 36.1 %, and negligence in guard or surveillance of the other ship, and sailing while drowsy, or drinking was a contributor to an accident. Poor watch keeping is very strong relationship with pool ready for sail.

The Innovation Ecosystem and Implications of the Netherlands. (네덜란드의 혁신클러스터정책과 시사점)

  • Kim, Young-woo
    • Journal of Venture Innovation
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    • v.5 no.1
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    • pp.107-127
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    • 2022
  • Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.