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Erschienen in: Computing 6/2022

18.01.2022 | Regular Paper

Smart COVID-shield: an IoT driven reliable and automated prototype model for COVID-19 symptoms tracking

verfasst von: Hrudaya Kumar Tripathy, Sushruta Mishra, Shubham Suman, Anand Nayyar, Kshira Sagar Sahoo

Erschienen in: Computing | Ausgabe 6/2022

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Abstract

IoT technology is revolutionizing healthcare and is transforming it into more personalized healthcare. In the context of COVID-19 pandemic, IoT`s intervention can help to detect its spread. This research proposes an effective “Smart COVID-Shield” that is capable of automatically detecting prevalent symptoms like fever and coughing along with ensuring social distancing norms are properly followed. It comprises three modules which include Cough Detect Module (CDM) for dry cough detection, Temperature Detect module (TDM) for high-temperature monitoring, and Distance Compute Module (DCM) to track social distancing norm violator. The device comprises a combination of a lightweight fabric suspender worn around shoulders and a flexible belt wrapped around the waist. The suspender is equipped with a passive infrared (PIR) sensor and temperature sensor to monitor persistent coughing patterns and high body temperature and the ultra-sonic sensor verify 6 feet distance for tracking an individual's social distancing norms. The developed model is implemented in an aluminum factory to verify its effectiveness. Results obtained were promising and reliable when compared to conventional manual procedures. The model accurately reported when body temperature rises. It outperformed thermal gun as it accurately recorded a mean of only 4.65 candidates with higher body temperature as compared to 8.59% with the thermal gun. A significant reduction of 3.61% on social distance violators was observed. Besides this, the latency delay of 10.32 s was manageable with the participant count of over 800 which makes it scalable.

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Metadaten
Titel
Smart COVID-shield: an IoT driven reliable and automated prototype model for COVID-19 symptoms tracking
verfasst von
Hrudaya Kumar Tripathy
Sushruta Mishra
Shubham Suman
Anand Nayyar
Kshira Sagar Sahoo
Publikationsdatum
18.01.2022
Verlag
Springer Vienna
Erschienen in
Computing / Ausgabe 6/2022
Print ISSN: 0010-485X
Elektronische ISSN: 1436-5057
DOI
https://doi.org/10.1007/s00607-021-01039-0

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