One paper related to Acoustic Vehicle Detection and Identification was accepted to IEEE ACCESS

Our research result on vehicle detection and identification based on sound has been accepted by IEEE ACCESS. By applying compressed sensing, we have achieved highly accurate recognition even with low sampling rate. Specifically, we have succeeded in reducing the sampling rate to 1/16. As a result, a high-performance processor (especially in terms of memory) is no longer required for acoustic signals, and a low-power, inexpensive processor can be used for vehicle recognition, which greatly contributes to cost reduction. We have actually implemented the system in an inexpensive MCU and verified that the performance is close to the theory.

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.

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