Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development Program
Road damage can cause discomfort while driving and even lead to accidents. According to the National Road Network Condition Map Data in 2017, the level of severe and minor road damage in the East Java region had reached 288 kilometers. Based on this data, periodic road condition assessments and main...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/13/e3sconf_isst2024_03016.pdf |
| _version_ | 1797334029799784448 |
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| author | Hardiyanti Siska Aprilia Kristanto Sepyan Purnama Yustita Aprilia Divi Alfarisi Ridho |
| author_facet | Hardiyanti Siska Aprilia Kristanto Sepyan Purnama Yustita Aprilia Divi Alfarisi Ridho |
| author_sort | Hardiyanti Siska Aprilia |
| collection | DOAJ |
| description | Road damage can cause discomfort while driving and even lead to accidents. According to the National Road Network Condition Map Data in 2017, the level of severe and minor road damage in the East Java region had reached 288 kilometers. Based on this data, periodic road condition assessments and maintenance are essential to minimize damage. Road maintenance efforts are crucial to support road infrastructure development programs. The initial step in road maintenance is to identify road damage, determining the necessary actions to be taken. In this research, road pavement damage identification is carried out using the Yolov5, Yolov6, and Yolov7 methods. Test results indicate that the Yolov5 method performed the best with a validation mAP (mean Average Precision) score of 42%, a Precision value of 0.544, and a Recall value of 0.453. These scores indicate that the accuracy of road pavement damage detection using the YOLO algorithm for depression, corrugation, potholes, and alligator cracking is at its maximum level. |
| first_indexed | 2024-03-08T08:14:58Z |
| format | Article |
| id | doaj.art-eb2a087b624a49aa837ffc72f396bea1 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-08T08:14:58Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-eb2a087b624a49aa837ffc72f396bea12024-02-02T07:57:18ZengEDP SciencesE3S Web of Conferences2267-12422024-01-014830301610.1051/e3sconf/202448303016e3sconf_isst2024_03016Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development ProgramHardiyanti Siska Aprilia0Kristanto Sepyan Purnama1Yustita Aprilia Divi2Alfarisi Ridho3Politeknik Negeri Banyuwangi, Civil Engineering DepartmentPoliteknik Negeri Banyuwangi, Informatics Engineering DepartmentPoliteknik Negeri Banyuwangi, Tourism Business Management DepartmentUniversitas Jember, Mathematics Education DepartmentRoad damage can cause discomfort while driving and even lead to accidents. According to the National Road Network Condition Map Data in 2017, the level of severe and minor road damage in the East Java region had reached 288 kilometers. Based on this data, periodic road condition assessments and maintenance are essential to minimize damage. Road maintenance efforts are crucial to support road infrastructure development programs. The initial step in road maintenance is to identify road damage, determining the necessary actions to be taken. In this research, road pavement damage identification is carried out using the Yolov5, Yolov6, and Yolov7 methods. Test results indicate that the Yolov5 method performed the best with a validation mAP (mean Average Precision) score of 42%, a Precision value of 0.544, and a Recall value of 0.453. These scores indicate that the accuracy of road pavement damage detection using the YOLO algorithm for depression, corrugation, potholes, and alligator cracking is at its maximum level.https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/13/e3sconf_isst2024_03016.pdf |
| spellingShingle | Hardiyanti Siska Aprilia Kristanto Sepyan Purnama Yustita Aprilia Divi Alfarisi Ridho Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development Program E3S Web of Conferences |
| title | Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development Program |
| title_full | Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development Program |
| title_fullStr | Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development Program |
| title_full_unstemmed | Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development Program |
| title_short | Applying Digital Images to Identify Pavement Damage in Support of The Road Infrastructure Development Program |
| title_sort | applying digital images to identify pavement damage in support of the road infrastructure development program |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/13/e3sconf_isst2024_03016.pdf |
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