Data Science Innovative Techniques and Applications for a Sustainable Environment
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: 20 May 2025 | Viewed by 125
Special Issue Editors
Interests: modeling and simulation; data analysis; programming; acoustics; field measurements
Special Issues, Collections and Topics in MDPI journals
Interests: acoustics; environmental acoustics; room acoustics; field measurements; modeling and simulation; data analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Data science (DS) techniques are present in many of our daily actions, from the procedures of social networks to economics decisions. The availability of Big Data in several domains of our lives makes it possible to use DS tools for improving the knowledge of complex systems and, consequently, the policy making processes. This is particularly important in the environmental domain, in which the development of innovative DS techniques is not only interesting from a scientific perspective, but is also necessary for sustainable growth.
In this framework, artificial intelligence and machine learning tools have been introduced alongside classical modeling approaches, leading to new investigations on environmental data, for a more sustainable management of natural resources and an improvement in the quality of life. This Special Issue is dedicated to advanced DS techniques and applications for any environmental dataset, measured or simulated, in urban areas, as well as rural and industrial contexts.
The potential themes for submissions to this Special Issue include, but are not limited to, the following:
- DS innovative techniques and applications for physical and chemical agents;
- Artificial intelligence and machine learning applications for environmental datasets;
- Usage of DS in environmental-sustainability-driven decisions;
- Case studies of DS applications to environmental data.
We encourage any submissions presenting original research contributions on these topics, as well as reviews of the most important and up-to-date applications in the literature. We look forward to receiving your contributions.
Dr. Domenico Rossi
Dr. Claudio Guarnaccia
Dr. Daljeet Singh
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. Sustainability 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.
Keywords
- data science
- machine learning
- artificial intelligence
- environmental data
- sustainable environment
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