Abstract
In this research, a vision system based on pixel-level deep learning image recognition algorithm is proposed. This system can be used to identify whether people entering and exiting a building are wearing a mask, and to calculate the cumulative number of people in a specific space. The system monitors and analyses crowd entering and exiting and as soon as finds that they are not wearing mask or the number of people in a specific space has reached the upper limit, the system sends a warning notification to the administrator. Through advanced detection systems, personnel can be controlled, especially for the prevention of infectious diseases during pandemics. The proposed system could be significant module for artificial intelligent systems developed for pandemics.
Publication Date
2021-08-01
Publication Title
Journal of Industrial Mechatronics
Publisher
Industrial Technology Research Institute
ISSN
0255-0075
Embargo Period
2024-11-22
Recommended Citation
Chen, D., Samani, H., Yang, C., & Jan, G. (2021) 'Crowd Monitoring for Pandemic using Mask R-CNN', Journal of Industrial Mechatronics, . Industrial Technology Research Institute: Retrieved from https://pearl.plymouth.ac.uk/secam-research/1896
