Journal of Applied Science and Engineering

Published by Tamkang University Press


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Daniel Adu-Gyamfi This email address is being protected from spambots. You need JavaScript enabled to view it.1,2, and Fengli Zhang This email address is being protected from spambots. You need JavaScript enabled to view it.1

1School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
2Department of Computer Science and Informatics, University of Energy and Natural Resources, P O Box 214 Sunyani, Ghana


Received: September 24, 2019
Accepted: February 13, 2020
Publication Date: September 1, 2020

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In recent decades, the public healthcare settings have devoted their attention to the derail of global pandemics. As a result, the public health professionals have adopted patients monitoring as one of the immediate measures to combat disease spreading. Incorrectness of data is a disadvantage of the traditional monitoring system as it is unable to efficiently handle the complex dynamic behavior of patients. The research community seeks to provide compelling techniques or algorithms that can be used to detect the location and travel of potentially hazardous and/or contagious patients in the case of pandemics. Heuristically, the mobility dynamics and activity records of patients are vital resources to support health researches. The activity records of patients contain their whereabouts in time, and that may provide some relevant knowledge for the analysis of disease spreading. This article presents a trajectory data mining technique to support the detection of outdoor mobile patient. The proposed technique examines the spatio-temporal trajectories of the patient via monitoring strategies with the aid of a global position system (GPS) device. The result of the experiment, using GeoLife big dataset has proven the proposed technique as efficient for monitoring an outdoor mobile patient, and it is easy to integrate into mobile health information systems that are intended for outdoor monitoring purposes towards derail of global pandemics.

Keywords: Health Information System, Mobile Data Analysis, Mobile Outdoor Patient, Patient Monitoring Technique, Spatio-Temporal Trajectory.



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