Health crisis situation awareness using mobile multiple modalities
Signal Processing, Sensor/Information Fusion, and Target Recognition XXX 2021
; 11756, 2021.
Article
in English
| Scopus | ID: covidwho-1304145
ABSTRACT
Responding to health crises requires the deployment of accurate and timely situation awareness. Understanding the location of geographical risk factors could assist in preventing the spread of contagious diseases and the system developed, Covid ID, is an attempt to solve this problem through the crowd sourcing of machine learning sensor-based health related detection reports. Specifically, Covid ID uses mobile-based Computer Vision and Machine Learning with a multi-faceted approach to understanding potential risks related to Mask Detection, Crowd Density Estimation, Social Distancing Analysis, and IR Fever Detection. Both visible-spectrum and LWIR images are used. Real results for all modules are presented along with the developed Android Application and supporting backend. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
Information Fusion, and Target Recognition XXX 2021
Year:
2021
Document Type:
Article
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