Human Activity Recognition and People Count for a SMART Public Transportation System

被引：3

作者：

Alizadeh, Roya ^{[1
]}

Savaria, Yvon ^{[1
]}

Nerguizian, Chahe ^{[1
]}

机构：

[1] Ecole Polytech Montreal, Dept Elect & Comp Engn, Montreal, PQ, Canada

来源：

2021 IEEE 4TH 5G WORLD FORUM (5GWF 2021) | 2021年

关键词：

Feature Extraction and Analysis; Classification; Human Activity Recognition; People Count; Channel State Information (CSI); Machine Learning; SMART Public Transportation;

D O I：

10.1109/5GWF52925.2021.00039

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In public transportation networks, it is desirable to detect and count people around bus stations. To achieve this goal, a unified dynamic human activity recognition and people counting (HARC) is applied to a public dataset for Wi-Fi-based activity recognition (WiAR) and a performance evaluation is carried out using a machine learning-based data processing framework. The processing results reported in this paper show that the accuracy achieved by HARC is 94% when the Adam optimizer method is used.

引用

页码：182 / 187

页数：6

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