TY - GEN
T1 - Design of an IoT-Based Cross-Modality Pedestrian Monitoring System for Contact Tracing in COVID-19 Prevention
AU - Bian, Ziyang
AU - Ma, Liang
AU - Li, Jianan
AU - Xu, Tingfa
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - COVID-19 epidemic prevention and control has become a regular part of life, and tracking people’s trajectory (especially fever patients) in public areas can help curb the spread of the epidemic. IoT technology has dramatically improved the efficiency of epidemic prevention and control. In this paper, we propose an IoT-based cross-modality pedestrian surveillance system architecture with the following characteristics: (1) robust, the system accesses multiple modal information (visible light, infrared, temperature, mobile phone signals), and can achieve trajectory tracking in non-cooperative situations; (2) with flexibility, we develop a nodal visual artificial intelligence software platform for deep neural network training and optimization, using which the deployment can be iteratively optimized intuitively and quickly. Finally, we also discuss the research prospects of artificial intelligence and IoT technologies in the direction of epidemic prevention and control.
AB - COVID-19 epidemic prevention and control has become a regular part of life, and tracking people’s trajectory (especially fever patients) in public areas can help curb the spread of the epidemic. IoT technology has dramatically improved the efficiency of epidemic prevention and control. In this paper, we propose an IoT-based cross-modality pedestrian surveillance system architecture with the following characteristics: (1) robust, the system accesses multiple modal information (visible light, infrared, temperature, mobile phone signals), and can achieve trajectory tracking in non-cooperative situations; (2) with flexibility, we develop a nodal visual artificial intelligence software platform for deep neural network training and optimization, using which the deployment can be iteratively optimized intuitively and quickly. Finally, we also discuss the research prospects of artificial intelligence and IoT technologies in the direction of epidemic prevention and control.
KW - COVID-19 Epidemic
KW - Internet of things
KW - cross-modality
KW - pedestrian monitoring systems
UR - http://www.scopus.com/inward/record.url?scp=85161373134&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-2362-5_8
DO - 10.1007/978-981-99-2362-5_8
M3 - Conference contribution
AN - SCOPUS:85161373134
SN - 9789819923618
T3 - Lecture Notes in Electrical Engineering
SP - 57
EP - 64
BT - Communications, Signal Processing, and Systems - Proceedings of the 11th International Conference on Communications, Signal Processing, and Systems, Vol. 3
A2 - Liang, Qilian
A2 - Wang, Wei
A2 - Liu, Xin
A2 - Na, Zhenyu
A2 - Zhang, Baoju
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th International Conference on Communications, Signal Processing, and Systems, CSPS 2022
Y2 - 23 July 2022 through 24 July 2022
ER -