Intelligent Wi-Fi Based Child Presence Detection System
Xiaolu Zeng, Beibei Wang, Chenshu Wu, Sai Deepika Regani, K. J. Ray Liu
Abstract
Heat-stroke and death of children being left alone in a parked car has attracted more and more attentions. As a result, car manufactures start to reward solutions for in-car Child Presence Detection (CPD) system to save lives recently. However, most of the existing works rely on dedicated sensors and only achieve limited accuracy and coverage. This paper presents the first-of-its-kind intelligent CPD system using commodity Wi-Fi. Based on a statistical electromagnetic wave model to fully leverage the information in all the multi-path components, the proposed CPD system mainly consists of a motion target detector to detect a child in awake/motion status, a stationary target detector to detect a sleeping child by extracting breathing rate information, and a transition target detector based on a Naive Bayes Classifier using multipath profiles as features. We build a real-time testbed and show through extensive experiments that the proposed system can achieve ≥ 99.34% detection rate and ≤ 4.38% false alarm rate, regardless of the location and motion status of a child. Built upon 2.4/5GHz Wi-Fi, the proposed system can integrate with the existing in-car Wi-Fi system with no additional hardware and calls for low CPU and memory consumptions, thus promising a practical candidate for CPD applications.
BibTeX
@inproceedings{icassp2022_intelligentwifib,
title = {Intelligent Wi-Fi Based Child Presence Detection System},
author = {Xiaolu Zeng and Beibei Wang and Chenshu Wu and Sai Deepika Regani and K. J. Ray Liu},
booktitle = {ICASSP 2022},
year = {2022}
}