VeCare: Statistical Acoustic Sensing for Automotive In-Cabin Monitoring


Yi Zhang, The University of Hong Kong and Tsinghua University; Weiying Hou, The University of Hong Kong; Zheng Yang, Tsinghua University; Chenshu Wu, The University of Hong Kong


On average, every 10 days a child dies from in-vehicle heatstroke. The life-threatening situation calls for an automatic Child Presence Detection (CPD) solution to prevent these tragedies. In this paper, we present VECARE, the first CPD system that leverages existing in-car audio without any hardware changes. To achieve so, we explore the fundamental properties of acoustic reflection signals and develop a novel paradigm of statistical acoustic sensing, which allows to detect motion, track breathing, and estimate speed in a unified model. Based on this, we build an accurate and robust CPD system by introducing a set of techniques that overcome multiple challenges concerning sound interference and sensing coverage. We implement VECARE using commodity speakers and a single microphone and conduct experiments with infant simulators and adults, as well as 15 young children for the real-world in-car study. The results demonstrate that VECARE achieves an average detection rate of 98.8% with a false alarm rate of 2.1% for 15 children in various cars, boosting the coverage by over 2.3× compared to state-of-the-art and achieving whole-car detection with no blind spot.

NSDI '23 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

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This content is available to:

@inproceedings {286490,
author = {Yi Zhang and Weiying Hou and Zheng Yang and Chenshu Wu},
title = {{VeCare}: Statistical Acoustic Sensing for Automotive {In-Cabin} Monitoring},
booktitle = {20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23)},
year = {2023},
isbn = {978-1-939133-33-5},
address = {Boston, MA},
pages = {1185--1200},
url = {},
publisher = {USENIX Association},
month = apr

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