Passenger Monitoring Using AI-Powered Radar

被引：8

作者：

Abedi, Hajar ^{[1
]}

Magnier, Clara ^{[2
]}

Shaker, George ^{[3
]}

机构：

[1] Univ Waterloo, Syst Design Engn, Waterloo, ON, Canada

[2] Univ Technol Compiegne, Biomech & Bioengn, Compiegne, France

[3] Univ Waterloo, Elect & Comp Engn, Waterloo, ON, Canada

来源：

2021 IEEE 19TH INTERNATIONAL SYMPOSIUM ON ANTENNA TECHNOLOGY AND APPLIED ELECTROMAGNETICS (ANTEM) | 2021年

关键词：

nun-wave radar; hot-cars act; artificial intelligence; autonomous vehicles;

D O I：

10.1109/ANTEM51107.2021.9518503

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Low-cost, contactless and privacy-preserving radar-based sensors are gaining attention for in-vehicle passenger monitoring. In this paper, we address two major topics in in-vehicle occupancy detection using radar technologies: 1. Detection of any living body left alone in a car. 2. Passenger counting. For the first one, we propose a novel, easy-to-implement and fast radar signal processing algorithm to detect the presence of alive subjects (e.g., infants, kids, pets), which is 100% accurate in detecting any tiny subject. For the latter one, we address radar low-resolution problems and propose machine learning to be coupled with radar signal processing to count the number of occupants and identify their occupied seats. Our proposed in-vehicle occupancy detection reaches more than 90% accuracy for each seat.

引用

页数：2