Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi

Shaohu Zhang; Myounggyu Won; Sang H. Son

doi:10.1145/2994551.2996705

Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi

Shaohu Zhang, Myounggyu Won, Sang H. Son

Department of Electrical Engineering and Computer Science

South Dakota State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

We present WiTraffic: The first WiFi-based traffic monitor-ing system. The unique WiFi Channel State Information (CSI) patterns of passing vehicles are captured and analyzed to perform vehicle classification. We implemented WiTraf-fic with off-The-shelf WiFi devices and performed real-world experiments with over a week of field data collection. The results show that the classification accuracy is around 96%.

Original language	English
Title of host publication	Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Publisher	Association for Computing Machinery, Inc
Pages	358-359
Number of pages	2
ISBN (Electronic)	9781450342636
DOIs	https://doi.org/10.1145/2994551.2996705
State	Published - 14 Nov 2016
Event	14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 - Stanford, United States Duration: 14 Nov 2016 → 16 Nov 2016

Publication series

Name	Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

Conference

Conference	14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Country/Territory	United States
City	Stanford
Period	14/11/16 → 16/11/16

Bibliographical note

Publisher Copyright:
© 2016 Copyright held by the owner/author(s).

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10.1145/2994551.2996705

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Zhang, S., Won, M., & Son, S. H. (2016). Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi. In Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 (pp. 358-359). (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016). Association for Computing Machinery, Inc. https://doi.org/10.1145/2994551.2996705

@inproceedings{e498e2439c4348a78b16ce0393c00fdf,

title = "Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi",

abstract = "We present WiTraffic: The first WiFi-based traffic monitor-ing system. The unique WiFi Channel State Information (CSI) patterns of passing vehicles are captured and analyzed to perform vehicle classification. We implemented WiTraf-fic with off-The-shelf WiFi devices and performed real-world experiments with over a week of field data collection. The results show that the classification accuracy is around 96%.",

author = "Shaohu Zhang and Myounggyu Won and Son, {Sang H.}",

note = "Publisher Copyright: {\textcopyright} 2016 Copyright held by the owner/author(s).; 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 ; Conference date: 14-11-2016 Through 16-11-2016",

year = "2016",

month = nov,

day = "14",

doi = "10.1145/2994551.2996705",

language = "English",

series = "Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016",

publisher = "Association for Computing Machinery, Inc",

pages = "358--359",

booktitle = "Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016",

}

Zhang, S, Won, M & Son, SH 2016, Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi. in Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016, Association for Computing Machinery, Inc, pp. 358-359, 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016, Stanford, United States, 14/11/16. https://doi.org/10.1145/2994551.2996705

Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi. / Zhang, Shaohu; Won, Myounggyu; Son, Sang H.
Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Association for Computing Machinery, Inc, 2016. p. 358-359 (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T2 - 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

AU - Zhang, Shaohu

AU - Won, Myounggyu

AU - Son, Sang H.

PY - 2016/11/14

Y1 - 2016/11/14

N2 - We present WiTraffic: The first WiFi-based traffic monitor-ing system. The unique WiFi Channel State Information (CSI) patterns of passing vehicles are captured and analyzed to perform vehicle classification. We implemented WiTraf-fic with off-The-shelf WiFi devices and performed real-world experiments with over a week of field data collection. The results show that the classification accuracy is around 96%.

AB - We present WiTraffic: The first WiFi-based traffic monitor-ing system. The unique WiFi Channel State Information (CSI) patterns of passing vehicles are captured and analyzed to perform vehicle classification. We implemented WiTraf-fic with off-The-shelf WiFi devices and performed real-world experiments with over a week of field data collection. The results show that the classification accuracy is around 96%.

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DO - 10.1145/2994551.2996705

M3 - Conference contribution

AN - SCOPUS:85007109691

T3 - Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

SP - 358

EP - 359

BT - Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

PB - Association for Computing Machinery, Inc

Y2 - 14 November 2016 through 16 November 2016

ER -

Zhang S, Won M, Son SH. Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi. In Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Association for Computing Machinery, Inc. 2016. p. 358-359. (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016). doi: 10.1145/2994551.2996705

Poster Abstract: WiTraffic-non-intrusive vehicle classification using WiFi

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