AITel: eHealth Augmented-Intelligence-Based Telemedicine Resource Recommendation Framework for IoT Devices in Smart Cities
- Authors
- Ahmed, S.T.; Kumar, V.; Kim, Jungyoon
- Issue Date
- Nov-2023
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Augmented Intelligence; Ecosystems; eHealth; Internet of Things; Medical diagnostic imaging; Reliability; Remote medicine; Resource management; Resource Recommendations; Smart cities; Smart EMS; Telemedicine; Telemedicine
- Citation
- IEEE Internet of Things Journal, v.10, no.21, pp 18461 - 18468
- Pages
- 8
- Journal Title
- IEEE Internet of Things Journal
- Volume
- 10
- Number
- 21
- Start Page
- 18461
- End Page
- 18468
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/89666
- DOI
- 10.1109/JIOT.2023.3243784
- ISSN
- 2327-4662
- Abstract
- Telemedicine was introduced on connected IoT based resource networking infrastructure. With technological evolution and artificial intelligence, the framework has expanded the grips beyond connecting remote patients. Augmented Intelligence (AuI) adds value to current telemedicine framework by coordinating with resource management pools of IoT devices and communication channels to provide a reliable enterprise ecosystem of smart cities. In this article, a novel approach for resource recommendation in telemedicine via AuI and IoT is proposed. The framework acquires data from the existing eHealth infrastructure of smart cities and telemedicine environment of IoT to provide an intelligent recommendation based on telemedicine services. The proposed framework is based on smart Enterprise Management System (EMS) for eHealth services. The proposed Augmented Intelligent Telemedicine (AITel) framework postulates the 94.83% accuracy from augmented intelligence assisted telemedicine and would create a reliable ecosystem on resource recommendations to build a resilient healthcare system for remote patients, communities and healthcare infrastructure. IEEE
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