Classification of Steps on Road Surface Using Acceleration Signals
Journal Title: EAI Endorsed Transactions on Cognitive Communications - Year 2015, Vol 1, Issue 5
Abstract
In order to reduce a road monitoring cost, we propose a system to monitor extensively road condition by cyclists with a smartphone. In this paper, we propose two methods towards road monitoring. First is to classify road signals to four road conditions. Second is to extract road signal from a smartphone's accelerometer in three positions: pants' side pocket, chest pocket and a bag in a front basket. In pants' side pocket, road signal is extracted by Independent Component Analysis. In chest pocket and bag in a front basket, road signal is extracted by selecting 1-axis affected from gravitational acceleration. In the experiment of the classification method, overall accuracy was 75%. The experimental results of the extraction methods with correlation coefficient showed the overall accuracy were more than 0.7 in pants' side pocket and chest pocket, the overall accuracy was less than 0.3 in bag in a front basket.
Authors and Affiliations
Junji Takahashi, Yusuke Kobana, Yoshito Tobe, Gullaume Lopez
Keywords
Related Articles
- EP ID EP45636
- DOI http://dx.doi.org/10.4108/eai.22-7-2015.2260293
- Views 265
- Downloads 0
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