Advances in Machine Learning, IoT and Big Data for Sustainable Communities
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 14963
Special Issue Editors
Interests: IoT; database systems; big data; deep learning; natural language processing; energy management systems; digital twins
Special Issues, Collections and Topics in MDPI journals
Interests: big data analysis; social media analysis; cloud computing; data mining; machine learning; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Interests: multi-vector energy systems; smart buildings; local flexibility markets
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The purpose of this Special Issue is to address, by using recent advances in artificial intelligence, machine learning and big data, the challenges of sustainable communities that generate large volumes of data from sensors, smart meters, IoT devices and smartphones. Sustainable communities imply a consistent use of technology for the benefit of citizens: smart grids, smart water management facilities, smart waste management systems, smart traffic and transportation systems, smart security systems or e-governance structures in such communities. These components ingest and generate a multitude of structured, semi-structured or unstructured data that require processing in real time or retrospect. Based on these big data, machine learning algorithms can be developed to aid in preventing problems (e.g., frauds, malfunctions, space scarcity, supply shortages) or identifying patterns and trends (e.g., analyzing electricity consumption, forecasting growth areas or equipment status). Numerous research opportunities can be explored for the safe operation of these components, flexibly running algorithms and avoiding big data bias, off-the-shelf machine learning algorithms and big data hubris.
Topics:
- Machine learning theory and applications;
- Big data management, processing and analytics;
- Smart cities and sustainable communities;
- IoT management and integration with utilities;
- Cloud, distributed and parallel computing;
- IoT, mobile-embedded and multimedia solutions.
New papers, or extended versions of papers presented at the 21st International Conference on Informatics on Economy (IE2022), are welcome. Submissions must not be currently under review for publication elsewhere. Conference papers may be submitted only if they are substantially extended (more than 50%), and must be referenced. All submitted papers will be peer-reviewed using the normal standards of the Electronics journal, and accepted based on quality, originality, novelty, and relevance to the theme of the Special Issue.
Dr. Simona-Vasilica Oprea
Dr. Fabrizio Marozzo
Dr. Xiaolong Jin
Guest Editors
Manuscript Submission Information
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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. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
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Keywords
- machine learning theory and applications
- big data management, processing and analytics
- smart cities and sustainable communities
- IoT management and integration with utilities
- cloud, distributed and parallel computing
- IoT, mobile-embedded and multimedia solutions
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