A pothole detection using VGG16

A pothole is a flaw that can be discovered on the road surface and it is one of a major contribution to the road accident. The impact of a vehicle on a potholed road is not just making the ride uncomfortable. It can damage the vehicle's suspension system as well as the wheel of the vehicle, res...

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Main Authors: Mohd Rum, Siti Nurulain, Rajaratinam, Niventhiraan
Format: Article
Published: Horizon Research Publishing 2022
Online Access:http://psasir.upm.edu.my/id/eprint/100313/
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author Mohd Rum, Siti Nurulain
Rajaratinam, Niventhiraan
author_facet Mohd Rum, Siti Nurulain
Rajaratinam, Niventhiraan
author_sort Mohd Rum, Siti Nurulain
building UPM Institutional Repository
collection Online Access
description A pothole is a flaw that can be discovered on the road surface and it is one of a major contribution to the road accident. The impact of a vehicle on a potholed road is not just making the ride uncomfortable. It can damage the vehicle's suspension system as well as the wheel of the vehicle, resulting in costly repair. Therefore, a regular road maintenance activity and assessment are very important to ensure that it is safe to be used. However, due to the limited number of expensive inspection vehicles, the inspection is performed manually. In this study, we present a mobile pothole detection system, namely HOLETRACKER using VGG16, a deep learning model architecture. The built model is trained using a collection of images taken from Kaggle and Internet in a variety of settings. The experiment used 739 numbers of training images and 144 numbers of testing images. The experimental result achieved the accuracy level rate at 90%. This paper also presents the development of two versions of the HOLETRACKER system, the mobile and web application that can be used by the public users and authorities. With the HOLETRACKER system, people can make a complaint of potholes via their mobile phone at anytime and anywhere. The validation checking of the potholed and location tracking through the GPS are the two main features provided by the system that will be performed before the information reaches the authorities for immediate action. The system is a cost-effective solution as an alternative to the manual pothole inspection management in facilitating the authorities as a measure to reduce accidents caused by potholes.
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institution Universiti Putra Malaysia
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spelling upm-1003132023-12-28T04:02:23Z http://psasir.upm.edu.my/id/eprint/100313/ A pothole detection using VGG16 Mohd Rum, Siti Nurulain Rajaratinam, Niventhiraan A pothole is a flaw that can be discovered on the road surface and it is one of a major contribution to the road accident. The impact of a vehicle on a potholed road is not just making the ride uncomfortable. It can damage the vehicle's suspension system as well as the wheel of the vehicle, resulting in costly repair. Therefore, a regular road maintenance activity and assessment are very important to ensure that it is safe to be used. However, due to the limited number of expensive inspection vehicles, the inspection is performed manually. In this study, we present a mobile pothole detection system, namely HOLETRACKER using VGG16, a deep learning model architecture. The built model is trained using a collection of images taken from Kaggle and Internet in a variety of settings. The experiment used 739 numbers of training images and 144 numbers of testing images. The experimental result achieved the accuracy level rate at 90%. This paper also presents the development of two versions of the HOLETRACKER system, the mobile and web application that can be used by the public users and authorities. With the HOLETRACKER system, people can make a complaint of potholes via their mobile phone at anytime and anywhere. The validation checking of the potholed and location tracking through the GPS are the two main features provided by the system that will be performed before the information reaches the authorities for immediate action. The system is a cost-effective solution as an alternative to the manual pothole inspection management in facilitating the authorities as a measure to reduce accidents caused by potholes. Horizon Research Publishing 2022 Article PeerReviewed Mohd Rum, Siti Nurulain and Rajaratinam, Niventhiraan (2022) A pothole detection using VGG16. Civil Engineering and Architecture, 10 (3). 1222 - 1232. ISSN 2332-1091; ESSN: 2332-1121 https://www.hrpub.org/journals/article_info.php?aid=12031 10.13189/cea.2022.100337
spellingShingle Mohd Rum, Siti Nurulain
Rajaratinam, Niventhiraan
A pothole detection using VGG16
title A pothole detection using VGG16
title_full A pothole detection using VGG16
title_fullStr A pothole detection using VGG16
title_full_unstemmed A pothole detection using VGG16
title_short A pothole detection using VGG16
title_sort pothole detection using vgg16
url http://psasir.upm.edu.my/id/eprint/100313/
http://psasir.upm.edu.my/id/eprint/100313/
http://psasir.upm.edu.my/id/eprint/100313/