Embracing crowdsensing: an Enhanced mobile sensing solution for road anomaly detection

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dc.contributor.authorLi, Xiao
dc.contributor.authorHuo, Da
dc.contributor.authorGoldberg, Daniel W.
dc.contributor.authorChu, Tianxing
dc.contributor.authorYin, Zhengcong
dc.contributor.authorTracy, Hammond
dc.creator.orcidhttps://orcid.org/0000-0002-6762-2475en_US
dc.creator.orcidhttps://orcid.org/0000-0001-9767-2855en_US
dc.creator.orcidhttps://orcid.org/0000-0001-7199-5517en_US
dc.creator.orcidhttps://orcid.org/0000-0001-7272-0507en_US
dc.creator.orcidhttps://orcid.org/0000-0002-6762-2475
dc.creator.orcidhttps://orcid.org/0000-0001-9767-2855
dc.creator.orcidhttps://orcid.org/0000-0001-7199-5517
dc.creator.orcidhttps://orcid.org/0000-0001-7272-0507
dc.creator.orcidhttps://orcid.org/0000-0002-6762-2475
dc.creator.orcidhttps://orcid.org/0000-0001-9767-2855
dc.creator.orcidhttps://orcid.org/0000-0001-7199-5517
dc.creator.orcidhttps://orcid.org/0000-0001-7272-0507https://orcid.org/0000-0002-6762-2475
dc.creator.orcidhttps://orcid.org/0000-0001-9767-2855
dc.creator.orcidhttps://orcid.org/0000-0001-7199-5517
dc.creator.orcidhttps://orcid.org/0000-0001-7272-0507
dc.date.accessioned2021-10-27T19:59:34Z
dc.date.available2021-10-27T19:59:34Z
dc.date.issued2019-09-13
dc.description.abstractRoad anomaly detection is essential in road maintenance and management; however, continuously monitoring road anomalies (such as bumps and potholes) with a low-cost and high-efficiency solution remains a challenging research question. In this study, we put forward an enhanced mobile sensing solution to detect road anomalies using mobile sensed data. We first create a smartphone app to detect irregular vehicle vibrations that usually imply road anomalies. Then, the mobile sensed signals are analyzed through continuous wavelet transform to identify road anomalies and estimate their sizes. Next, we innovatively utilize a spatial clustering method to group multiple driving tests’ results into clusters based on their spatial density patterns. Finally, the optimized detection results are obtained by synthesizing each cluster’s member points. Results demonstrate that our proposed solution can accurately detect road surface anomalies (94.44%) with a high positioning accuracy (within 3.29 meters in average) and an acceptable size estimation error (with a mean error of 14 cm). This study suggests that implementing a crowdsensing solution could substantially improve the effectiveness of traditional road monitoring systems.en_US
dc.description.abstractRoad anomaly detection is essential in road maintenance and management; however, continuously monitoring road anomalies (such as bumps and potholes) with a low-cost and high-efficiency solution remains a challenging research question. In this study, we put forward an enhanced mobile sensing solution to detect road anomalies using mobile sensed data. We first create a smartphone app to detect irregular vehicle vibrations that usually imply road anomalies. Then, the mobile sensed signals are analyzed through continuous wavelet transform to identify road anomalies and estimate their sizes. Next, we innovatively utilize a spatial clustering method to group multiple driving tests’ results into clusters based on their spatial density patterns. Finally, the optimized detection results are obtained by synthesizing each cluster’s member points. Results demonstrate that our proposed solution can accurately detect road surface anomalies (94.44%) with a high positioning accuracy (within 3.29 meters in average) and an acceptable size estimation error (with a mean error of 14 cm). This study suggests that implementing a crowdsensing solution could substantially improve the effectiveness of traditional road monitoring systems.
dc.identifier.citationLi, X., Huo, D., Goldberg, D.W., Chu, T., Yin, Z. and Hammond, T., 2019. Embracing crowdsensing: An enhanced mobile sensing solution for road anomaly detection. ISPRS International Journal of Geo-Information, 8(9), p.412.en_US
dc.identifier.citationLi, X., Huo, D., Goldberg, D.W., Chu, T., Yin, Z. and Hammond, T., 2019. Embracing crowdsensing: An enhanced mobile sensing solution for road anomaly detection. ISPRS International Journal of Geo-Information, 8(9), p.412.
dc.identifier.doihttps://doi.org/10.3390/ijgi8090412
dc.identifier.urihttps://hdl.handle.net/1969.6/89870
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherMDPIen_US
dc.publisherMDPI
dc.rightsAttribution 4.0 International*
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectmobile crowdsensingen_US
dc.subjectroad anomaly detectionen_US
dc.subjectmobile crowdsensing
dc.subjectroad anomaly detection
dc.titleEmbracing crowdsensing: an Enhanced mobile sensing solution for road anomaly detectionen_US
dc.titleEmbracing crowdsensing: an Enhanced mobile sensing solution for road anomaly detection
dc.typeArticleen_US
dc.typeArticle

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