TY - GEN
T1 - Proposal for a Compressive Measurement-Based Acoustic Vehicle Detection and Identification System
AU - Dawton, Billy
AU - Ishida, Shigemi
AU - Hori, Yuki
AU - Uchino, Masato
AU - Arakawa, Yutaka
N1 - Funding Information:
ACKNOWLEDGMENTS This work was supported in part by JSPS KAKENHI Grant Number JP18K18041 and the Cooperative Research Project Program of RIEC, Tohoku University.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - As society becomes increasingly interconnected, the need for sophisticated signal processing and data analysis techniques becomes increasingly apparent, particularly in the field of Intelligent Transportation Systems (ITS) where various sensing applications generate data at an exponential rate. In this paper, we put a forward a compressive sensing-based system to extract information from passing vehicle sounds sampled at sub-Nyquist rates for Acoustic Vehicle Detection and Identification (AVDI) applications. The obtained compressive measurements are used to detect and identify passing vehicles. Initial evaluation performed using data obtained from roads on a university campus presents an accuracy of 86.2 % with a back-end ADC sample rate of 3 kHz.
AB - As society becomes increasingly interconnected, the need for sophisticated signal processing and data analysis techniques becomes increasingly apparent, particularly in the field of Intelligent Transportation Systems (ITS) where various sensing applications generate data at an exponential rate. In this paper, we put a forward a compressive sensing-based system to extract information from passing vehicle sounds sampled at sub-Nyquist rates for Acoustic Vehicle Detection and Identification (AVDI) applications. The obtained compressive measurements are used to detect and identify passing vehicles. Initial evaluation performed using data obtained from roads on a university campus presents an accuracy of 86.2 % with a back-end ADC sample rate of 3 kHz.
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U2 - 10.1109/VTC2020-Fall49728.2020.9348569
DO - 10.1109/VTC2020-Fall49728.2020.9348569
M3 - Conference contribution
AN - SCOPUS:85101391849
T3 - IEEE Vehicular Technology Conference
BT - 2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 92nd IEEE Vehicular Technology Conference, VTC 2020-Fall
Y2 - 18 November 2020
ER -