TURKISH

Classification of Moving Ground Targets Using Measurement from Accelerometer on Road Surface

By Ismail Can Büyüktepe , Ali Köksal Hocaoğlu

Book information

ISBN
9781665450928
DOI
10.1109/SIU55565.2022.9864775
ISSN
2165-0608
Language
turkish
Format
PDF
Filesize
1 MB (1174813 bytes)
Pages
\4
DPI
600
Scanned
no
Time added
2023-08-30 17:46:30

Description

In this study, an algorithm that can classify human and car has been developed by using vibration signals obtained from a three-axis accelerometer sensor station placed on three different floors. Data were collected over soil, asphalt and concrete ground. As classifiers, k-Nearest Neighbor classifier (k-NN) and Support Vector Machine (SVM) classifiers are used. Using classifiers alone limits classification performance. A two-stage classifier model has been proposed to improve the classification performance. The classifier model, which is proposed in two stages, detects the presence of motion in the first stage. In the second stage, it performs the classification of moving targets. As a result of the experimental studies, it has been shown that the proposed two-stage classifier model improves the performance in solving the problem.

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