Optimal Rescue Ship Locations Using Image Processing and Clustering
Currently, globalization of the world economy has also resulted in a shipping volume increase. However, this growth in maritime traffic has led to increased risk of marine accidents. These accidents have a higher probability of occurring in regions where geographical features such as islands are pre...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-01-01
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| Series: | Symmetry |
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| Online Access: | http://www.mdpi.com/2073-8994/11/1/32 |
| _version_ | 1811306498785017856 |
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| author | Cho-Young Jung Sang-Lok Yoo |
| author_facet | Cho-Young Jung Sang-Lok Yoo |
| author_sort | Cho-Young Jung |
| collection | DOAJ |
| description | Currently, globalization of the world economy has also resulted in a shipping volume increase. However, this growth in maritime traffic has led to increased risk of marine accidents. These accidents have a higher probability of occurring in regions where geographical features such as islands are present. Further, the positioning of rescue ships in a particular ocean region with a high level of maritime activity is critical for rescue operations. This paper proposes a method for determining an optimal set of locations for stationing rescue ships in an ocean region with numerous accident sites, such as in the Wando islands of South Korea. The computational challenge in this problem is identified as the positioning of numerous islands of varying sizes located in the region. Thus, the proposed method combines a clustering-based optimization method and an image processing approach that incorporates flood filling to calculate the shortest pixel value between two points in the ocean that detours around the islands. Experimental results indicate that the proposed method reduces the distance between rescue ships and each accident site by 5.0 km compared to the original rescue ship locations. Thus, rescue time is reduced. |
| first_indexed | 2024-04-13T08:45:46Z |
| format | Article |
| id | doaj.art-8d2145c4392c4769a98ffe0bc47444f2 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-13T08:45:46Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-8d2145c4392c4769a98ffe0bc47444f22022-12-22T02:53:40ZengMDPI AGSymmetry2073-89942019-01-011113210.3390/sym11010032sym11010032Optimal Rescue Ship Locations Using Image Processing and ClusteringCho-Young Jung0Sang-Lok Yoo1Department of Marine Science and Production, Kunsan National University, Gunsan 54150, Jeonbuk, KoreaMokpo Maritime University, Mokpo 58628, Jeonnam, KoreaCurrently, globalization of the world economy has also resulted in a shipping volume increase. However, this growth in maritime traffic has led to increased risk of marine accidents. These accidents have a higher probability of occurring in regions where geographical features such as islands are present. Further, the positioning of rescue ships in a particular ocean region with a high level of maritime activity is critical for rescue operations. This paper proposes a method for determining an optimal set of locations for stationing rescue ships in an ocean region with numerous accident sites, such as in the Wando islands of South Korea. The computational challenge in this problem is identified as the positioning of numerous islands of varying sizes located in the region. Thus, the proposed method combines a clustering-based optimization method and an image processing approach that incorporates flood filling to calculate the shortest pixel value between two points in the ocean that detours around the islands. Experimental results indicate that the proposed method reduces the distance between rescue ships and each accident site by 5.0 km compared to the original rescue ship locations. Thus, rescue time is reduced.http://www.mdpi.com/2073-8994/11/1/32clustering-based optimizationlocation optimizationflood-filling algorithmmarine accidentrescue shipshortest distance |
| spellingShingle | Cho-Young Jung Sang-Lok Yoo Optimal Rescue Ship Locations Using Image Processing and Clustering Symmetry clustering-based optimization location optimization flood-filling algorithm marine accident rescue ship shortest distance |
| title | Optimal Rescue Ship Locations Using Image Processing and Clustering |
| title_full | Optimal Rescue Ship Locations Using Image Processing and Clustering |
| title_fullStr | Optimal Rescue Ship Locations Using Image Processing and Clustering |
| title_full_unstemmed | Optimal Rescue Ship Locations Using Image Processing and Clustering |
| title_short | Optimal Rescue Ship Locations Using Image Processing and Clustering |
| title_sort | optimal rescue ship locations using image processing and clustering |
| topic | clustering-based optimization location optimization flood-filling algorithm marine accident rescue ship shortest distance |
| url | http://www.mdpi.com/2073-8994/11/1/32 |
| work_keys_str_mv | AT choyoungjung optimalrescueshiplocationsusingimageprocessingandclustering AT sanglokyoo optimalrescueshiplocationsusingimageprocessingandclustering |