C. Moremada, C. Sandeepa, N. Dissanayaka, T. Gamage and M. Liyanage, "Energy efficient contact tracing and social interaction based patient prediction system for COVID-19 pandemic," in Journal of Communications and Networks, vol. 23, no. 5, pp. 390-407, Oct. 2021, doi: 10.23919/JCN.2021.000037
Energy efficient contact tracing and social interaction based patient prediction system for COVID-19 pandemic
|Author:||Moremada, Charuka1; Sandeepa, Chamara2; Dissanayaka, Nadeeka3;|
1Faculty of Engineering, Vrije Universiteit Brussel, Belgium
2School of Computer Science, University College Dublin, Ireland
3Department of Electrical and Information Engineering, University of Ruhuna, Galle, Sri Lanka
4Center for Wireless Communications, University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 2.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022013111512
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2022-01-31
Due to the spread of Coronavirus disease 2019 (COVID-19), the world has encountered an ongoing pandemic to date. It is a highly contagious disease. In addition to the vaccination, social distancing and isolation of patients are proven to be one of the commonly used strategies to reduce the spread of disease. For efficient social distancing, contact tracing is a critical requirement in the incubation period of 14-days of the disease to contain any further spread. However, we identify that there is a lack of reliable and practical social interaction tracking methods and prediction methods for the probability of getting the disease. This paper focuses on user tracking and predicting the infection probability based on these social interactions. We first developed an energy-efficient BLE (Bluetooth Low Energy) based social interaction tracking system to achieve this. Then, based on the collected data, we propose an algorithm to predict the possibility of getting the COVID-19. Finally, to show the practicality of our solution, we implemented a prototype with a mobile app and a web monitoring tool for healthcare authorities. In addition to that, to analyze the proposed algorithm’s behaviour, we performed a simulation of the system using a graph-based model.
Journal of communications and networks
|Pages:||390 - 407|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
The Academy of Finland partly supports this work in 6Genesis (grant no. 318927) project. This work was done with the collaboration of the University of Ruhuna, Sri Lanka.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© 2021 KICS. Creative Commons Attribution-NonCommercial (CC BY-NC). This is an Open Access article distributed under the terms of Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided that the original work is properly cited.