COVIDSAVIOR: A Novel Sensor-Fusion and Deep Learning Based Framework for Virus Outbreaks

Sharnil Pandya*, Anirban Sur, Nitin Solke

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


The presented deep learning and sensor-fusion based assistive technology (Smart Facemask and Thermal scanning kiosk) will protect the individual using auto face-mask detection and auto thermal scanning to detect the current body temperature. Furthermore, the presented system also facilitates a variety of notifications, such as an alarm, if an individual is not wearing a mask and detects thermal temperature beyond the standard body temperature threshold, such as 98.6°F (37°C). Design/methodology/approach—The presented deep Learning and sensor-fusion-based approach can also detect an individual in with or without mask situations and provide appropriate notification to the security personnel by raising the alarm. Moreover, the smart tunnel is also equipped with a thermal sensing unit embedded with a camera, which can detect the real-time body temperature of an individual concerning the prescribed body temperature limits as prescribed by WHO reports. Findings—The investigation results validate the performance evaluation of the presented smart face-mask and thermal scanning mechanism. The presented system can also detect an outsider entering the building with or without mask condition and be aware of the security control room by raising appropriate alarms. Furthermore, the presented smart epidemic tunnel is embedded with an intelligent algorithm that can perform real-time thermal scanning of an individual and store essential information in a cloud platform, such as Google firebase. Thus, the proposed system favors society by saving time and helps in lowering the spread of coronavirus.

Original languageEnglish
Article number797808
Number of pages13
JournalFrontiers in Public Health
Publication statusPublished - 30 Nov 2021
Externally publishedYes

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