RapidPD: Rapid Human and Pet Presence Detection System for Smart Vehicles via Wi-Fi

Heatstroke and life threatening incidents resulting from the retention of children and animals in vehicles pose a critical global safety issue. Current presence detection solutions often require specialized hardware or suffer from detection delays that do not meet safety standards. To tackle this issue, by remodeling channel state information (CSI) with theoretical analysis of path propagation, this study introduces RapidPD, an innovative system utilizing CSI in subcarrier dimension to detect the presence of humans and pets in vehicles. The system models the impact of motion on CSI and introduces motion statistics in subcarrier dimension using a multi-layer autocorrelation method to quantify environmental changes. RapidPD is implemented using commercial Wi-Fi chipsets and tested in real vehicle environments with data collected from 10 living organisms. Experimental results demonstrate that RapidPD achieves a detection accuracy of 99.05% and a true positive rate of 99.32% within a 1-second time window at a low sampling rate of 20 Hz. These findings represent a significant advancement in vehicle safety and provide a foundation for the widespread adoption of presence detection systems.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2025-04-21
DOI
https://doi.org/10.1109/taes.2025.3562838
Citations
2
Primary Topic
Video Surveillance and Tracking Methods
Type
article
Field-Weighted Citation Impact
2.55
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

RapidPD: Rapid Human and Pet Presence Detection System for Smart Vehicles via Wi-Fi

Xiu Yin Zhang, Mo Huang, Zhen Chen, Hong-Song Guo
2 citations
IEEE Transactions on Aerospace and Electronic Systems
Video Surveillance and Tracking Methods
2.55
article

RapidPD: Rapid Human and Pet Presence Detection System for Smart Vehicles via Wi-Fi

Xiu Yin Zhang, Mo Huang, Zhen Chen, Hong-Song Guo
article en
2 citations

Abstract

Heatstroke and life threatening incidents resulting from the retention of children and animals in vehicles pose a critical global safety issue. Current presence detection solutions often require specialized hardware or suffer from detection delays that do not meet safety standards. To tackle this issue, by remodeling channel state information (CSI) with theoretical analysis of path propagation, this study introduces RapidPD, an innovative system utilizing CSI in subcarrier dimension to detect the presence of humans and pets in vehicles. The system models the impact of motion on CSI and introduces motion statistics in subcarrier dimension using a multi-layer autocorrelation method to quantify environmental changes. RapidPD is implemented using commercial Wi-Fi chipsets and tested in real vehicle environments with data collected from 10 living organisms. Experimental results demonstrate that RapidPD achieves a detection accuracy of 99.05% and a true positive rate of 99.32% within a 1-second time window at a low sampling rate of 20 Hz. These findings represent a significant advancement in vehicle safety and provide a foundation for the widespread adoption of presence detection systems.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(4)
University of Macau (MO), Institute of Microelectronics (CN), South China University of Technology (CN)
Openalex Percentile: Top 11%
Video Surveillance and Tracking Methods
2.55
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

RapidPD: Rapid Human and Pet Presence Detection System for Smart Vehicles via Wi-Fi — Xiu Yin Zhang, Mo Huang, et al. · IEEE Transactions on Aerospace and Electronic Systems (2025) | TGRS Research Map | TGRS