Human Activity Recognition and People Count for a SMART Public Transportation System
- Resource Type
- Conference
- Authors
- Alizadeh, Roya; Savaria, Yvon; Nerguizian, Chahe
- Source
- 2021 IEEE 4th 5G World Forum (5GWF) 5GWF 5G World Forum (5GWF), 2021 IEEE 4th. :182-187 Oct, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Wireless communication
Performance evaluation
Time-frequency analysis
Time series analysis
Activity recognition
Data processing
Time-domain analysis
Feature Extraction and Analysis
Classification
Human Activity Recognition
People Count
Channel State Information (CSI)
Machine Learning
SMART Public Transportation
- Language
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.