Digital library of construction informatics and information technology in civil engineering and construction
Digital library
Paper: lc3-2017-109
| Paper title: | Detecting Pavement Patches Utilizing Smartphones Technology and Vehicles |
| Authors: | Charalambos Kyriakou and Symeon E. Christodoulou |
| Summary: | Presented herein is a study on the utilization of low-cost technology for detection of roadway pavement anomalies (patches and potholes), by use of sensors on smartphones and of automobilesÕ on-board diagnostic (OBD-II) devices for the collection and analysis of vibration-related data while vehicles are in movement. The mobile data collection kit consists of a triaxial accelerometer, a gyroscope and a global positioning sensor. The smartphone-based data collection is complimented with robust regression analysis and a bagged-trees classification model for the classification of pavement anomalies. The proposed system is readily available, low-cost and adequately accurate, and can be utilized in crowd-sourced applications for pavement monitoring. Further, the proposed methodology has been field-tested, exhibiting detection accuracy levels higher than 90% for pavement patches, and it is currently expanded to include larger datasets and a bigger number of pavement defect types. |
| Type: | regular paper |
| Year of publication: | 2017 |
| Keywords: | Pavement Anomalies, Detection and Classification, Smartphones Technology, Robust Regression, Bagged Trees |
| Series: | jc3:2017 |
| Download paper: | /pdfs/LC3_2017_paper_109.pdf |
| Citation: | Charalambos Kyriakou and Symeon E. Christodoulou (2017). Detecting Pavement Patches Utilizing Smartphones Technology and Vehicles. Lean and Computing in Construction Congress (LC3): Volume I Ð Proceedings of the Joint Conference on Computing in Construction (JC3), July 4-7, 2017, Heraklion, Greece, pp. 859-866, http://itc.scix.net/paper/lc3-2017-109 |
hosted by University of Ljubljana
includes:
W78
includes:
W78
inspired by SciX, ported by Robert Klinc [2019]