Automated pothole detection and notification system
There are a lot of studies regarding the detection of potholes using different methods. Most methods use image processing, but those methods require high cost materials like high quality camera in order for the image to be processed accurately. This study used a low cost sensor which is an accelerom...
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oai:animorepository.dlsu.edu.ph:etd_bachelors-97782021-08-25T02:58:51Z Automated pothole detection and notification system Celestial, Patricia Bianca M. Paden, Eirah Ritzel A. Pascual, Paolo G. San Buenaventua, Jose Ramon S. There are a lot of studies regarding the detection of potholes using different methods. Most methods use image processing, but those methods require high cost materials like high quality camera in order for the image to be processed accurately. This study used a low cost sensor which is an accelerometer. The accelerometer detected vibrations which was processed by a software. The sensor obtained the acceleration values depending on the intensity of the vibration which was assessed whether these values exceeded the threshold value set. When a pothole is detected, the camera and the GPS module attached to the system will be triggered. The camera took a snapshot of the pothole while the GPS module acquired the coordinates of its location in the form of latitude and longitude. After obtaining the coordinates, the system googled them and took a screenshot of the Google Maps view of the said location. The system then informed the Department of Public Works and Highways (DPWH) about the location and the image of the pothole by sending them an electronic mail. The average accuracy of the system in detecting potholes is 91.11%. Overall, the study showed that the system succesfully detected almost all of the potholes it passed through on the main roads. 2016-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/9133 Bachelor's Theses English Animo Repository System analysis Engineering |
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System analysis Engineering Celestial, Patricia Bianca M. Paden, Eirah Ritzel A. Pascual, Paolo G. San Buenaventua, Jose Ramon S. Automated pothole detection and notification system |
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There are a lot of studies regarding the detection of potholes using different methods. Most methods use image processing, but those methods require high cost materials like high quality camera in order for the image to be processed accurately.
This study used a low cost sensor which is an accelerometer. The accelerometer detected vibrations which was processed by a software. The sensor obtained the acceleration values depending on the intensity of the vibration which was assessed whether these values exceeded the threshold value set. When a pothole is detected, the camera and the GPS module attached to the system will be triggered. The camera took a snapshot of the pothole while the GPS module acquired the coordinates of its location in the form of latitude and longitude. After obtaining the coordinates, the system googled them and took a screenshot of the Google Maps view of the said location. The system then informed the Department of Public Works and Highways (DPWH) about the location and the image of the pothole by sending them an electronic mail. The average accuracy of the system in detecting potholes is 91.11%. Overall, the study showed that the system succesfully detected almost all of the potholes it passed through on the main roads. |
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Celestial, Patricia Bianca M. Paden, Eirah Ritzel A. Pascual, Paolo G. San Buenaventua, Jose Ramon S. |
author_facet |
Celestial, Patricia Bianca M. Paden, Eirah Ritzel A. Pascual, Paolo G. San Buenaventua, Jose Ramon S. |
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Celestial, Patricia Bianca M. |
title |
Automated pothole detection and notification system |
title_short |
Automated pothole detection and notification system |
title_full |
Automated pothole detection and notification system |
title_fullStr |
Automated pothole detection and notification system |
title_full_unstemmed |
Automated pothole detection and notification system |
title_sort |
automated pothole detection and notification system |
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Animo Repository |
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2016 |
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https://animorepository.dlsu.edu.ph/etd_bachelors/9133 |
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