This paper is in the following e-collection/theme issue:

Clinical engineering (7) Telehealth and Telemonitoring (1889) New Methods (1032) eHealth Infrastructures (396) Research Infrastructures and Registries (72)

Published on in Vol 9 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50175, first published .
Enhancing Energy Efficiency in Telehealth Internet of Things Systems Through Fog and Cloud Computing Integration: Simulation Study

Enhancing Energy Efficiency in Telehealth Internet of Things Systems Through Fog and Cloud Computing Integration: Simulation Study

Enhancing Energy Efficiency in Telehealth Internet of Things Systems Through Fog and Cloud Computing Integration: Simulation Study

Authors of this article:

Yunyong Guo1 Author Orcid Image ;   Sudhakar Ganti1 Author Orcid Image ;   Yi Wu1 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Jeyaraman N, Jeyaraman M, Yadav S, Ramasubramanian S, Balaji S, Muthu S, Lekha P C, Patro B. Applications of Fog Computing in Healthcare. Cureus 2024 View
  2. Kumar P, Bhatt A. HE-AO: An Optimization-Based Encryption Approach for Data Delivery Model in A Multi-Tenant Environment. Wireless Personal Communications 2024;138(2):1329 View
  3. Gao X, He P, Zhou Y, Qin X. A Smart Healthcare System for Remote Areas Based on the Edge–Cloud Continuum. Electronics 2024;13(21):4152 View
  4. Alsharif M, Jahid A, Kannadasan R, Singla M, Gupta J, Nisar K, Abdel-Aty A, Kim M. Survey of energy-efficient fog computing: Techniques and recent advances. Energy Reports 2025;13:1739 View

Books/Policy Documents

  1. Olajide A. Energy-Efficient Deep Learning Approaches in IoT, Fog, and Green Blockchain Revolution. View

Conference Proceedings

  1. Babu B, Prasad G, Sarma P, Neelima S. 2024 4th International Conference on Mobile Networks and Wireless Communications (ICMNWC). Hybrid Cloud Strategies: Balancing the Benefits of Public and Private Clouds for Optimal Performance and Security View