A New Covid-19 Tracing Approach using Machine Learning and Drones Enabled Wireless Network

A New Covid-19 Tracing Approach using Machine Learning and Drones Enabled Wireless Network

Contact Tracing

UAVs

Covid-19

wireless monitoring system

Wireless Mesh Networks

Reinforcement Learning

The continuous advancements in wireless network systems have reshaped the healthcare systems towards using emerging communication technologies at different levels. This paper makes two major contributions. Firstly, a new monitoring and tracking wireless system is developed to handle the COVID-19 spread problem. Unmanned aerial vehicles (UAVs), i.e., drones, are used as base stations as well as data collection points from Internet of Things (IoT) devices on the ground. These UAVs are also able to exchange data with other UAVs and cloud servers. Secondly, this paper introduces a new reinforcement learning (RL) framework for learning the optimal signal-aware UAV trajectories under quality of service constraints. The proposed RL algorithm is instrumental in making the UAV movement decisions that maximize the signal power at the receiver and the data collected from the ground agents. Simulation experiments confirm that the system overcomes conventional wireless monitoring systems and demonstrates efficiency especially in terms of flexible continues connectivity, line-of sight visibility, and collision avoidance.

Alsarhan, Ayoub

Almalkawi, Islam

Kilani, Yousef

International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 22 (2021); pp. 111-126

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2021-11-19

Copyright (c) 2021 Ayoub Alsarhan, Islam Almalkawi, Yousef Kilani

application/pdf

eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

Peer-reviewed Article