Machine Learning for IoT Applications and Digital Twins-Reference-Cited by-同舟云学术

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Machine Learning for IoT Applications and Digital Twins

Published:2024-08-05 Issue:15 Volume:24 Page:5062
ISSN:1424-8220
Container-title:Sensors
language:en
Short-container-title:Sensors

Author:

Rezazadeh Javad¹^ORCID,Ameri Sianaki Omid²^ORCID,Farahbakhsh Reza³^ORCID

Affiliation:

1. Crown Institute of Higher Education (CIHE), Sydney, NSW 2060, Australia

2. Victoria University Business School, Victoria University, Melbourne, VIC 8001, Australia

3. Institute Polytechnique de Paris, Telecom SudParis, 91000 Evry, France

Abstract

The Internet of Things (IoT) stands as one of the most transformative technologies of our era, significantly enhancing the living conditions and operational efficiencies across various domains [...]

Publisher

MDPI AG

Link

https://www.mdpi.com/1424-8220/24/15/5062/pdf

Reference14 articles.

1. The application of internet of things in healthcare: A systematic literature review and classification;Ahmadi;Univers. Access Inf. Soc.,2019

2. Towards Intelligent Monitoring in IoT: AI Applications for Real-Time Analysis and Prediction;IEEE Access,2024

3. Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges;Hussain;IEEE Commun. Surv. Tutor.,2020

4. Machine learning for wireless communications in the Internet of Things: A comprehensive survey;Jagannath;Ad Hoc Netw.,2019

5. Kaur, M.J., Mishra, V.P., and Maheshwari, P. (2020). The Convergence of Digital Twin, IoT, and Machine Learning: Transforming Data into Action. Digital Twin Technologies and Smart Cities, Springer.

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