ReCognizing SUspect and PredictiNg ThE SpRead of Contagion Based on Mobile Phone LoCation DaTa (COUNTERACT): A system of identifying COVID-19 infectious and hazardous sites, detecting disease outbreaks based on the internet of things, edge computing, and artificial intelligence

Hemant Ghayvat; Muhammad Awais; Prosanta Gope; Sharnil Pandya; Shubhankar Majumdar

doi:10.1016/j.scs.2021.102798

ReCognizing SUspect and PredictiNg ThE SpRead of Contagion Based on Mobile Phone LoCation DaTa (COUNTERACT): A system of identifying COVID-19 infectious and hazardous sites, detecting disease outbreaks based on the internet of things, edge computing, and artificial intelligence

Sustain Cities Soc. 2021 Jun:69:102798. doi: 10.1016/j.scs.2021.102798. Epub 2021 Feb 24.

Authors

Hemant Ghayvat¹, Muhammad Awais², Prosanta Gope³, Sharnil Pandya⁴, Shubhankar Majumdar⁵

Affiliations

¹ Innovation Department, Technology University of Denmark, Denmark.
² Center for Intelligent Medical Electronics, Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433, China.
³ University of Sheffield, United Kingdom.
⁴ Symbiosis Centre for Applied Artificial Intelligence and Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, Maharashtra, India.
⁵ Department of Electronics and Communication Engineering, National Institute of Technology Meghalaya, Shillong, 793003, India.

Abstract

Human movement is a significant factor in extensive spatial-transmission models of contagious viruses. The proposed COUNTERACT system recognizes infectious sites by retrieving location data from a mobile phone device linked with a particular infected subject. The proposed approach is computing an incubation phase for the subject's infection, backpropagation through the subjects' location data to investigate a location where the subject has been during the incubation period. Classifying to each such site as a contagious site, informing exposed suspects who have been to the contagious location, and seeking near real-time or real-time feedback from suspects to affirm, discard, or improve the recognition of the infectious site. This technique is based on the contraption to gather confirmed infected subject and possibly carrier suspect area location, correlating location for the incubation days. Security and privacy are a specific thing in the present research, and the system is used only through authentication and authorization. The proposed approach is for healthcare officials primarily. It is different from other existing systems where all the subjects have to install the application. The cell phone associated with the global positioning system (GPS) location data is collected from the COVID-19 subjects.

Keywords: AI; Backtracking; Cross-path; Edge computing; GPS location; IoT; Outbreak; Pandemic.