Edge Intelligence for Empowering IoT-based Healthcare Systems
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Abstract (arXiv)
The demand for real-time, affordable, and efficient smart healthcare services is increasing exponentially due to the technological revolution and burst of population. To meet the increasing demands on this critical infrastructure, there is a need for intelligent methods to cope with the existing obstacles in this area. In this regard, edge computing technology can reduce latency and energy consumption by moving processes closer to the data sources in comparison to the traditional centralized cloud and IoT-based healthcare systems. In addition, by bringing automated insights into the smart healthcare systems, artificial intelligence (AI) provides the possibility of detecting and predicting high-risk diseases in advance, decreasing medical costs for patients, and offering efficient treatments. The objective of this article is to highlight the benefits of the adoption of edge intelligent technology, along with AI in smart healthcare systems. Moreover, a novel smart healthcare model is proposed to boost the utilization of AI and edge technology in smart healthcare systems. Additionally, the paper discusses issues and research directions arising when integrating these different technologies together.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 2 of its 20 references that are in the map. First posted on arXiv 22 Mar 2021.
Builds on
2 of 20 references.
References · 2
Built on by
Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 4; 2026: 1.
8 papers.
- 2025Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Modelscited by 44
- 2022Trustworthy Federated Learning via Blockchaincited by 15
- 2022Differentially Private Federated Learning via Reconfigurable Intelligent Surfacecited by 5
- 2024Edge AI-based Radio Frequency Fingerprinting for IoT Networkscited by 3
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networkscited by 3
- 2025Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AIcited by 3
- 2025Diffusion Learning with Partial Agent Participation and Local Updatescited by 0
- 2026Two-Valued Symmetric Circulant Matrices: Applications in Deep Learningcited by 0
- 2026Two-Valued Symmetric Circulant Matrices: Applications in Deep Learning15 May 2026
- 2025Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI28 Aug 2025
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks26 Aug 2025
- 2025Diffusion Learning with Partial Agent Participation and Local Updates16 May 2025
- 2025Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Models8 Mar 2025
- 2024Edge AI-based Radio Frequency Fingerprinting for IoT Networks13 Dec 2024
- 2022Trustworthy Federated Learning via Blockchain13 Aug 2022
- 2022Differentially Private Federated Learning via Reconfigurable Intelligent Surface31 Mar 2022