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Machine Learning for IoT Applications and Digital Twins.

Authors :
Rezazadeh, Javad
Ameri Sianaki, Omid
Farahbakhsh, Reza
Source :
Sensors (14248220); Aug2024, Vol. 24 Issue 15, p5062, 3p
Publication Year :
2024

Abstract

This document discusses the integration of machine learning (ML), Internet of Things (IoT), and digital twin (DT) technologies and their transformative potential across various fields. The authors highlight the challenges posed by the vast amounts of data generated by IoT and the need for advanced tools like ML to process and extract meaningful insights from this data. They also explore the concept of digital twins, which create virtual replicas of physical entities and enable real-time simulation and optimization. The document includes a collection of research papers that showcase the innovative applications of these technologies in areas such as maintenance scheduling, healthcare services, structural integrity, safety management, security, traffic control, and physical activity coaching. The authors hope that readers will find inspiration and insights from these studies to drive further innovation in this dynamic field. [Extracted from the article]

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
15
Database :
Complementary Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
178950125
Full Text :
https://doi.org/10.3390/s24155062