Cited 0 time in webofscience Cited 2 time in scopus

DeepWiTraffic: Low cost WiFi-based traffic monitoring system using deep learning

Title
DeepWiTraffic: Low cost WiFi-based traffic monitoring system using deep learning
Authors
Won MyounggyuSahu SayanPark, Kyung-Joon
DGIST Authors
Park, Kyung-Joon
Issue Date
2019-11-07
Citation
16th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2019, 476-484
Type
Conference
ISBN
9781728146010
Abstract
A traffic monitoring system (TMS) is an integral part of Intelligent Transportation Systems (ITS). It is an essential tool for traffic analysis and planning. One of the biggest challenges is, however, the high cost especially in covering the huge rural road network. In this paper, we propose to address the problem by developing a novel TMS called DeepWiTraffic. DeepWiTraffic is a low-cost, portable, and non-intrusive solution that is built only with two WiFi transceivers. It exploits the unique WiFi Channel State Information (CSI) of passing vehicles to perform detection and classification of vehicles. Spatial and temporal correlations of CSI amplitude and phase data are identified and analyzed using a machine learning technique to classify vehicles into five different types: motorcycles, passenger vehicles, SUVs, pickup trucks, and large trucks. A large amount of CSI data and ground-truth video data are collected over a month period from a real-world two-lane rural roadway to validate the effectiveness of DeepWiTraffic. The results validate that DeepWiTraffic is an effective TMS with the average detection accuracy of 99.4% and the average classification accuracy of 91.1% in comparison with state-of-the-art non-intrusive TMSs. © 2019 IEEE.
URI
http://hdl.handle.net/20.500.11750/12882
DOI
10.1109/MASS.2019.00062
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • Author Park, Kyung-Joon CSI(Cyber-Physical Systems Integration) Lab
  • Research Interests Cyber-Physical Systems; 무선 센서-액츄에이터 네트워크; 스마트 팩토리
Files:
There are no files associated with this item.
Collection:
Department of Information and Communication EngineeringCSI(Cyber-Physical Systems Integration) Lab2. Conference Papers


qrcode mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE