Artificial Intelligence and IoNT for Multi-Disciplinary Applications

A special issue of IoT (ISSN 2624-831X).

Deadline for manuscript submissions: closed (1 June 2022) | Viewed by 5163

Special Issue Editors

Department of Computer Science, University of Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Tamil Nadu 600117, India
Interests: big data; knowledge mining; data mining; wireless sensor networks ubiquitous computin

Special Issue Information

Dear Colleagues,

Recent breakthroughs in artificial intelligence mean that we are witnessing many ground-breaking AI-based applications every day. Among all the new evolved concepts, Internet of Nano Things is the most exciting and futuristic approach. This book proposes to deliberate artificial intelligence insights, approaches and ingenuities of nanotechnology in multitudinous areas. The innovativeness of the book welcomes researchers from different areas to contribute with their discoveries, insights and approaches, as well as their specific inquiries about communities, whereas lifting the aggregate of investigations and applications of artificial intelligence insights is the reason for the book’s existence.

The book provides a space for academics, scholars, researchers, engineering, and many organizations to share novel and imaginative ideas and hypotheses. Expository approaches, numerical recreations, demonstrating exhibits and case studies have progressed, allowing research facilities to conduct field operational tests and progressing developments with noteworthiness to advances within the field of artificial intelligence and nanotechnology.

Prof. Dr. Vijayakumar Varadarajan
Dr. K. Kalaiselvi
Guest Editors

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.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. IoT is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 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.

Keywords

  • Internet of Nano Things using artificial intelligence
  • Advance components in Internet of Nano Things
  • 5G/big data Internet of Nano Things
  • Artificial intelligence (AI) in healthcare
  • Role of AI in national defense
  • IoNT in biometric system
  • Deep brain monitoring in e-healthcare system
  • Nano satellite and application
  • Security issues and application in AI
  • 6G mobile communication technology

Published Papers (1 paper)

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Research

31 pages, 1423 KiB  
Article
Big Data and Energy Security: Impacts on Private Companies, National Economies and Societies
by Hossein Hassani, Nadejda Komendantova, Daniel Kroos, Stephan Unger and Mohammad Reza Yeganegi
IoT 2022, 3(1), 29-59; https://0-doi-org.brum.beds.ac.uk/10.3390/iot3010002 - 23 Dec 2021
Cited by 4 | Viewed by 3594
Abstract
The importance of energy security for the successful functioning of private companies, national economies, and the overall society cannot be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the [...] Read more.
The importance of energy security for the successful functioning of private companies, national economies, and the overall society cannot be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the well-being of everybody. Uncertainty in terms of the availability of information, namely reliable data to make predictions and to plan for investment as well as for other actions of stakeholders in the energy markets is one of the factors with the highest influence on energy security. This uncertainty can be connected with many factors, such as the availability of reliable data or actions of stakeholders themselves. For example, the recent outbreak of the COVID-19 pandemic revealed negative impacts of uncertainty on decision-making processes and markets. At the time point when the market participants started to receive real-time information about the situation, the energy markets began to ease. This is one scenario where Big Data can be used to amplify information to various stakeholders to prevent panic and to ensure market stability and security of supply. Considering the novelty of this topic, our methodology is based on the meta-analysis of existing studies in the area of impacts of energy security on private companies, the national economy, and society. The results show that, in a fast-paced digital world characterized by technological advances, the use of Big Data technology provides a unique niche point to close this gap in information disparity by levering the use of unconventional data sources to integrate technologies, stakeholders, and markets to promote energy security and market stability. The potential of Big Data technology is yet to be fully utilized. Big Data can handle large data sets characterized by volume, variety, velocity, value, and complexity. Our conclusion is that the challenge for energy markets is to leverage this technology to mine available socioeconomic, political, geographic, and environmental data responsibly and to provide indicators that predict future global supply and demand. This information is crucial for energy security and ensuring global economic prosperity. Full article
(This article belongs to the Special Issue Artificial Intelligence and IoNT for Multi-Disciplinary Applications)
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