LifeCount: A Device-free CSI-based Human Counting Solution for Emergency Building Evacuations

被引：2

作者：

Konings, Daniel ^{[1
]}

Alam, Fakhrul ^{[1
]}

机构：

[1] Massey Univ, Dept Mech & Elect Engn, Auckland 0632, New Zealand

来源：

2020 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS 2020) | 2020年

关键词：

Device-free; indoor counting; MLP; LSTM; neural networks; CSI; LOCALIZATION; RSSI;

D O I：

10.1109/sas48726.2020.9220032

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：

During large scale building evacuations, it is difficult to ascertain how many people have left the premises safely. To assist in the rescue effort, indoor counting solutions can provide emergency personnel with the number of people who have evacuated the building, and from which floors. LifeCount implements a novel two stage neural network-based algorithm to accurately count the number of people passing through a hallway. Experimental results show that LifeCount can attain a zero counting error accuracy of 96.9%.

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页数：5

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