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Special Issue "Machine Learning Techniques for Energy Efficient IoT Networks"
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".
Deadline for manuscript submissions: 30 October 2023 | Viewed by 2930
Special Issue Editors
Interests: Internet of Things; 5G and beyond networks; body area networks; low-power communication protocols; machine learning; public safety networks
Interests: AI & Machine Learning; 5G Networks & Beyond; Health Analytics; IoT
Special Issue Information
Internet of things (IoT) technologies are becoming part of our daily life thanks to the realization of a large set of applications and services. Most IoT devices are constrained by energy efficiency due to limited battery capacity. Energy-efficient solutions for both IoT devices and IoT networks with device-specific corresponding configurations are critical for viable applications and services.
Machine learning (ML) techniques can pave the way towards energy-efficient IoT networks. A greater understanding is needed regarding how different ML algorithms and methods can improve the performance if suitable data are obtained. Equally important are the methods themselves—how energy efficient they are for their implementation and execution. The objective of this Special Issue is to bring together recent progress in scientific and practical experiences, theory, modeling, design, implementation, deployment, and management of the IoT networks.
- Energy-efficient machine learning methods for Internet of things.
- Energy-efficient data prediction in IoT networks.
- Energy-efficient data analytics in IoT networks.
- Energy-efficient machine learning methods for edge-IoT networks.
- Machine-learning-enabled system architectures for IoT applications.
- Lightweight machine-learning-based security design for IoT networks.
- Machine-learning-enabled secure and privacy-preserving IoT communications.
- Low-energy energy-harvesting wireless communication in IoT networks.
- Machine-learning-based energy-efficient resource allocation in IoT networks.
- New application implementations by machine learning methods.
Prof. Dr. Muhammad Mahtab Alam
Dr. Ahmed Zoha
If you have any questions or need further information, please free to contact Special Issue Editor Larissa Zhang <email@example.com>.
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.