An SVM based Algorithm for Road Disease Detection using Accelerometer

Yanjun Ren, Guanghua Wen, Xiuyun Li

Abstract


A signal processing algorithm based on the principle of support vector machines as well as the analysis to the characteristics of road surface diseases is proposed to detect pavement disease. Measurements from vehicle-mounted sensors (e.g., accelerometers and Global Positioning System (GPS) receivers) are properly combined to produce higher quality road roughness data for road surface condition monitoring. By using the proposed algorithm to identify the measurements, the test results show that this algorithm is suitable for pavement disease detection and is an efficient algorithm.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3264

 


Keywords


pahavement distress detection; Support vector machine; Signal processing

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The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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