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Road Surface Monitoring Using Smartphone Sensors: A Review
Road surface monitoring is a key factor to providing smooth and safe road infrastructure to road users. The key to road surface condition monitoring is to detect road surface anomalies, such as potholes, cracks, and bumps, which affect driving comfort and on-road safety. Road surface anomaly detecti...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263868/ https://www.ncbi.nlm.nih.gov/pubmed/30423962 http://dx.doi.org/10.3390/s18113845 |
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author | Sattar, Shahram Li, Songnian Chapman, Michael |
author_facet | Sattar, Shahram Li, Songnian Chapman, Michael |
author_sort | Sattar, Shahram |
collection | PubMed |
description | Road surface monitoring is a key factor to providing smooth and safe road infrastructure to road users. The key to road surface condition monitoring is to detect road surface anomalies, such as potholes, cracks, and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become increasingly popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road maintenance. However, current smartphone sensors operate at a low frequency, and undersampled sensor signals cause low detection accuracy. In this study, current approaches for using smartphones for road surface anomaly detection are reviewed and compared. In addition, further opportunities for research using smartphones in road surface anomaly detection are highlighted. |
format | Online Article Text |
id | pubmed-6263868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-62638682018-12-12 Road Surface Monitoring Using Smartphone Sensors: A Review Sattar, Shahram Li, Songnian Chapman, Michael Sensors (Basel) Review Road surface monitoring is a key factor to providing smooth and safe road infrastructure to road users. The key to road surface condition monitoring is to detect road surface anomalies, such as potholes, cracks, and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become increasingly popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road maintenance. However, current smartphone sensors operate at a low frequency, and undersampled sensor signals cause low detection accuracy. In this study, current approaches for using smartphones for road surface anomaly detection are reviewed and compared. In addition, further opportunities for research using smartphones in road surface anomaly detection are highlighted. MDPI 2018-11-09 /pmc/articles/PMC6263868/ /pubmed/30423962 http://dx.doi.org/10.3390/s18113845 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Sattar, Shahram Li, Songnian Chapman, Michael Road Surface Monitoring Using Smartphone Sensors: A Review |
title | Road Surface Monitoring Using Smartphone Sensors: A Review |
title_full | Road Surface Monitoring Using Smartphone Sensors: A Review |
title_fullStr | Road Surface Monitoring Using Smartphone Sensors: A Review |
title_full_unstemmed | Road Surface Monitoring Using Smartphone Sensors: A Review |
title_short | Road Surface Monitoring Using Smartphone Sensors: A Review |
title_sort | road surface monitoring using smartphone sensors: a review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263868/ https://www.ncbi.nlm.nih.gov/pubmed/30423962 http://dx.doi.org/10.3390/s18113845 |
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