Advances in Machine Learning, IoT and Big Data for Sustainable Communities

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

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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.

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.