An Artificial Intelligence application for drone-assisted 5G remote e-Health

Magaia, Naercio, Ribeiro, Igor de L, de Aguiar, André W O, Fonseca, Ramon, Muhammad, Khan and de Albuquerque, Victor Hugo C (2021) An Artificial Intelligence application for drone-assisted 5G remote e-Health. Internet of Things Magazine, 4 (4). pp. 30-35. ISSN 2576-3199

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Abstract

Artificial intelligence (AI) algorithms are experiencing growing research interest due to their ability to improve decision making capabilities for promising applications in different economic sectors. The growing shift toward the Internet of Everything environments brought by devices embedded with sensors that can share information brings immense opportunity for new applications (apps). While these new apps thrive in resource-rich areas (i.e., capitals), neighboring cities that lack the resources and infrastructure to support them may be left behind. It is vital that new technologies can reach those who need them the most, especially healthcare-based. This article proposes an app-based approach for long-distance patient monitoring and care. The app would serve as a platform of communication between patients and healthcare staff, where the latter can send standardized video footage or pictures to the former (e.g., their primary care doctor). This feature is enhanced with a recurrent neural network algorithm as a validation tool for healthcare-related videos exchanged between patients and staff. Thus, the healthcare team does not need to check each video for validity, freeing their time for other activities.

Item Type: Article
Additional Information: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Artificial Intelligence, Drone, 5G, e-Health, Remote, Application, RNN, IoD
Schools and Departments: School of Engineering and Informatics > Informatics
Research Centres and Groups: Foundations of Software Systems
Subjects: Q Science > Q Science (General) > Q0300 Cybernetics > Q0325 Self-organizing systems. Conscious automata > Q0334 Artificial intelligence
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication > TK5105.5 Computer networks
Depositing User: Naercio Magaia
Date Deposited: 06 Dec 2021 09:54
Last Modified: 07 Mar 2022 14:15
URI: http://sro.sussex.ac.uk/id/eprint/103237

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