ISpot: An intelligent real-time pothole spot identification model using a CNN algorithm
Maintaining roads is a very intricate and significant global concern. Detecting road abnormalities, including potholes, is crucial in road monitoring and management. Identifying potholes is essential to minimize road accidents and car damage and improve travel comfort. Authorities have long seen roa...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2024/04/matecconf_icmed2024_01156.pdf |
| _version_ | 1797248910885912576 |
|---|---|
| author | Patthi Sridhar Padhy Neelamadhab |
| author_facet | Patthi Sridhar Padhy Neelamadhab |
| author_sort | Patthi Sridhar |
| collection | DOAJ |
| description | Maintaining roads is a very intricate and significant global concern. Detecting road abnormalities, including potholes, is crucial in road monitoring and management. Identifying potholes is essential to minimize road accidents and car damage and improve travel comfort. Authorities have long seen road maintenance as a significant concern. However, the absence of accurate identification and connecting of road potholes exacerbates the problem. An end-to-end system named Intelligent Spotting (iSpot) of Pathole has been developed to address this issue by providing real-time identification, tracking, and geographical mapping of potholes around the city. A Convolutional Neural Network (CNN) framework is suggested and assessed using a real-world dataset for detecting potholes. Real-time maps displaying pothole locations are created using the Google Maps Application Programming Interface (API). Both pothole identification and mapping are combined into an Android application to offer a comprehensive service via this technology. The suggested model outperforms the baseline techniques regarding accuracy, precision, and F score. |
| first_indexed | 2024-04-24T20:22:06Z |
| format | Article |
| id | doaj.art-ccb4f75ba76845fe92312613fcafc0a8 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-04-24T20:22:06Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-ccb4f75ba76845fe92312613fcafc0a82024-03-22T08:05:26ZengEDP SciencesMATEC Web of Conferences2261-236X2024-01-013920115610.1051/matecconf/202439201156matecconf_icmed2024_01156ISpot: An intelligent real-time pothole spot identification model using a CNN algorithmPatthi Sridhar0Padhy Neelamadhab1Department of CSE, GIETUDepartment of CSE, GIETUMaintaining roads is a very intricate and significant global concern. Detecting road abnormalities, including potholes, is crucial in road monitoring and management. Identifying potholes is essential to minimize road accidents and car damage and improve travel comfort. Authorities have long seen road maintenance as a significant concern. However, the absence of accurate identification and connecting of road potholes exacerbates the problem. An end-to-end system named Intelligent Spotting (iSpot) of Pathole has been developed to address this issue by providing real-time identification, tracking, and geographical mapping of potholes around the city. A Convolutional Neural Network (CNN) framework is suggested and assessed using a real-world dataset for detecting potholes. Real-time maps displaying pothole locations are created using the Google Maps Application Programming Interface (API). Both pothole identification and mapping are combined into an Android application to offer a comprehensive service via this technology. The suggested model outperforms the baseline techniques regarding accuracy, precision, and F score.https://www.matec-conferences.org/articles/matecconf/pdf/2024/04/matecconf_icmed2024_01156.pdf |
| spellingShingle | Patthi Sridhar Padhy Neelamadhab ISpot: An intelligent real-time pothole spot identification model using a CNN algorithm MATEC Web of Conferences |
| title | ISpot: An intelligent real-time pothole spot identification model using a CNN algorithm |
| title_full | ISpot: An intelligent real-time pothole spot identification model using a CNN algorithm |
| title_fullStr | ISpot: An intelligent real-time pothole spot identification model using a CNN algorithm |
| title_full_unstemmed | ISpot: An intelligent real-time pothole spot identification model using a CNN algorithm |
| title_short | ISpot: An intelligent real-time pothole spot identification model using a CNN algorithm |
| title_sort | ispot an intelligent real time pothole spot identification model using a cnn algorithm |
| url | https://www.matec-conferences.org/articles/matecconf/pdf/2024/04/matecconf_icmed2024_01156.pdf |
| work_keys_str_mv | AT patthisridhar ispotanintelligentrealtimepotholespotidentificationmodelusingacnnalgorithm AT padhyneelamadhab ispotanintelligentrealtimepotholespotidentificationmodelusingacnnalgorithm |