A. Suraji, A. Sudjianto, R. Riman, Candra Aditya, Aviv Yuniar Rahman, Rangga Pahlevi Putra
{"title":"基于移动车辆观测的GPS视频路面缺陷识别","authors":"A. Suraji, A. Sudjianto, R. Riman, Candra Aditya, Aviv Yuniar Rahman, Rangga Pahlevi Putra","doi":"10.1109/ICCoSITE57641.2023.10127782","DOIUrl":null,"url":null,"abstract":"Identification of road surface infrastructure defects is a very important requirement and requires fast and accurate information. The purpose of this study is to identify road surface defects using recording technology with GPS video. The data collection method was carried out by surveying road defects using GPS video with moving car observation. Furthermore, the image data from the video recording is compiled to determine the condition of the road surface damage in accordance with the coordinates of the road segment. The method of analyzing the types of road damage used the Pavement Condition Index (PCI) method, then a roadmap of road damage conditions was made. The research results using GPS video obtained that the percentage of road surface defects for each type of damage is good 10 %, fair 45%, light poor 35% and heavy poor 10%. The results of the identification of road surface defects with GPS video are generally in accordance with the conditions in the field. From the results of this study, it can be recommended that a road defect survey using GPS video can be used as an alternative survey method and has the advantage of being faster.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Moving Car Observation (MCO) for Road Surface Defect Identification Using GPS Video\",\"authors\":\"A. Suraji, A. Sudjianto, R. Riman, Candra Aditya, Aviv Yuniar Rahman, Rangga Pahlevi Putra\",\"doi\":\"10.1109/ICCoSITE57641.2023.10127782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identification of road surface infrastructure defects is a very important requirement and requires fast and accurate information. The purpose of this study is to identify road surface defects using recording technology with GPS video. The data collection method was carried out by surveying road defects using GPS video with moving car observation. Furthermore, the image data from the video recording is compiled to determine the condition of the road surface damage in accordance with the coordinates of the road segment. The method of analyzing the types of road damage used the Pavement Condition Index (PCI) method, then a roadmap of road damage conditions was made. The research results using GPS video obtained that the percentage of road surface defects for each type of damage is good 10 %, fair 45%, light poor 35% and heavy poor 10%. The results of the identification of road surface defects with GPS video are generally in accordance with the conditions in the field. From the results of this study, it can be recommended that a road defect survey using GPS video can be used as an alternative survey method and has the advantage of being faster.\",\"PeriodicalId\":256184,\"journal\":{\"name\":\"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCoSITE57641.2023.10127782\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCoSITE57641.2023.10127782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Moving Car Observation (MCO) for Road Surface Defect Identification Using GPS Video
Identification of road surface infrastructure defects is a very important requirement and requires fast and accurate information. The purpose of this study is to identify road surface defects using recording technology with GPS video. The data collection method was carried out by surveying road defects using GPS video with moving car observation. Furthermore, the image data from the video recording is compiled to determine the condition of the road surface damage in accordance with the coordinates of the road segment. The method of analyzing the types of road damage used the Pavement Condition Index (PCI) method, then a roadmap of road damage conditions was made. The research results using GPS video obtained that the percentage of road surface defects for each type of damage is good 10 %, fair 45%, light poor 35% and heavy poor 10%. The results of the identification of road surface defects with GPS video are generally in accordance with the conditions in the field. From the results of this study, it can be recommended that a road defect survey using GPS video can be used as an alternative survey method and has the advantage of being faster.