C-AVDI: Compressive Measurement-Based Acoustic Vehicle Detection and Identification

Billy Dawton, Shigemi Ishida, Yutaka Arakawa

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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%.

Original languageEnglish
Pages (from-to)159457-159474
Number of pages18
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Materials Science
  • General Engineering

Fingerprint

Dive into the research topics of 'C-AVDI: Compressive Measurement-Based Acoustic Vehicle Detection and Identification'. Together they form a unique fingerprint.

Cite this