| Title: | Technological and analytical review of contact tracing apps for COVID-19 management |
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| Authors: | ID Gupta, Rajan (Author)
ID Pandey, Gaurav (Author)
ID Chaudhary, Poonam (Author)
ID Pal, Saibal K. (Author) |
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| Files: |
This document has no files that are freely available to the public. This document may have a physical copy in the library of the organization, check the status via COBISS.  |
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| Language: | English |
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| Work type: | Unknown |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | UNG - University of Nova Gorica
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| Abstract: | Role of technology is improving for COVID-19 management all around the world. Usage of mobile applications, web applications, cloud computing, and related technologies have helped many public administrators worldwide manage the current pandemic. Contact tracing applications are such mobile app solutions that are used by more than 100 countries today. This study presents a structured research review-based framework related to multiple contact tracing applications. The various components of the framework are related to technological working, design architecture, and feature analysis of the applications, along with the analysis of the acceptance of such applications worldwide. Also, components focusing on the security features and analysis of these applications based on Data Privacy, Security Vetting, and different attacks have been included in the research framework. Many applications are yet to explore the analytical capabilities of the data generated through contact tracing. The various use-cases identified for these applications are detecting positive case probability, identifying a containment zone in the country, finding regional hotspots, monitoring public events & gatherings, identifying sensitive routes, and allocating resources in various regions during the pandemic. This study will act as a guide for the users researching contact tracings applications using the proposed four-layered framework for their app assessment. |
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| Keywords: | novel corona virus, location technology, contact tracing applications, Aarogya Setu App, data science, data analysis |
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| Year of publishing: | 2021 |
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| Number of pages: | str. 1-40 |
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| Numbering: | Vol. 15, no. |
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| PID: | 20.500.12556/RUNG-6427 |
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| COBISS.SI-ID: | 58233347 |
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| UDC: | 004 |
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| ISSN on article: | 1748-9725 |
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| DOI: | 10.1080/17489725.2021.1899319 |
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| NUK URN: | URN:SI:UNG:REP:HV2RWI1I |
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| Publication date in RUNG: | 02.04.2021 |
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| Views: | 2802 |
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| Downloads: | 0 |
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