This article proposes the creation and evaluation of an AI based context-aware mobile learning system designed to provide real-time training and support for medical cleaning staff.
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This article proposes the creation and evaluation of an AI based context-aware mobile learning system designed to provide real-time training and support for medical cleaning staff.
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13 p.
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Abstract: Even with the adoption of modern technology within the medical system, the spread of deadly pathogens remains a silent, yet deadly killer. Indeed, e-health, and in particular m-health is at the forefront of the computing portion of modern medical care. It follows the ubiquity of mobile computing devices that has become synonymous with modern life. Although the focus of m-health is patient based, this paper attempts to provide a focus on the healthcare service provider in an attempt to reduce the fatalities due to pathogen transmissions in care facilities. This paper proposes, and describes the creation and evaluation of an AI based context-aware mobile learning system designed to provide real-time training and support for medical cleaning staff. This learning system aims to bridge the gap between context-aware learning systems and m-health. As such, the system provides context information to the learner about the various threats and best ways to deal with possible pathogens in a long-term care scenario. The evaluation, field tested within the adult long-term care system demonstrates the benefit and validity of the system in both training and ongoing usage within the medical system.
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Tortorella, Richard A. W. & Kinshuk.A Mobile Context-Aware Medical Training System for the Reduction of Pathogen Transmission,
article,
October 4, 2017;
New York, New York.
(https://digital.library.unt.edu/ark:/67531/metadc1042621/:
accessed April 24, 2025),
University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu;
crediting UNT College of Information.