音による車両検知と車種推定に研究成果がIEEE ACCESSに採択されました．圧縮センシングを応用することで低サンプリングであっても高精度な認識を達成しています．具体的にはサンプリングレートを1/16にすることに成功しました．これにより，音響信号のために高性能なプロセッサ（特にメモリ量）を必要としなくなり，低消費電力で安価なプロセッサでも車両認識が可能となりコスト削減に大きく寄与します．実際に安価なMCUにも実装し，理論に近い性能が出ることも検証しています．
Billy Dawton; Shigemi Ishida; Yutaka Arakawa
C-AVDI: Compressive Measurement-Based Acoustic Vehicle Detection and Identification Journal Article
In: IEEE Access, vol. 9, pp. 159457-159474, 2021, ISSN: 2169-3536.
@article{9632588,
title = {C-AVDI: Compressive Measurement-Based Acoustic Vehicle Detection and Identification},
author = {Billy Dawton and Shigemi Ishida and Yutaka Arakawa},
doi = {10.1109/ACCESS.2021.3132061},
issn = {2169-3536},
year = {2021},
date = {2021-12-01},
urldate = {2021-01-01},
journal = {IEEE Access},
volume = {9},
pages = {159457-159474},
abstract = {As society grows ever more interconnected, the need for sophisticated signal processing and data analysis techniques becomes increasingly apparent. This is particularly true in the field of intelligent transportation systems (ITSs), where various sensing applications generate data at an exponential rate. In this paper, we present C-AVDI, a compressive measurement-based acoustic vehicle detection and identification architecture capable of extracting information from vehicle audio signals while sampling at sub-Nyquist rates. In addition, we further reduce the overall complexity by performing any necessary signal filtering during the acquisition process, removing the need for a separate filtering stage in the system’s front-end. Our results obtained from data collected under a range of weather conditions present an accuracy of 80% with a back-end analog-to-digital converter (ADC) sample rate of 3kHz, with initial results from a microcontroller (MCU) implementation of our proposed system presenting an accuracy of 72%.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As society grows ever more interconnected, the need for sophisticated signal processing and data analysis techniques becomes increasingly apparent. This is particularly true in the field of intelligent transportation systems (ITSs), where various sensing applications generate data at an exponential rate. In this paper, we present C-AVDI, a compressive measurement-based acoustic vehicle detection and identification architecture capable of extracting information from vehicle audio signals while sampling at sub-Nyquist rates. In addition, we further reduce the overall complexity by performing any necessary signal filtering during the acquisition process, removing the need for a separate filtering stage in the system’s front-end. Our results obtained from data collected under a range of weather conditions present an accuracy of 80% with a back-end analog-to-digital converter (ADC) sample rate of 3kHz, with initial results from a microcontroller (MCU) implementation of our proposed system presenting an accuracy of 72%.