Machine Learning and AI Technology for Sustainable Development

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: 13 August 2024 | Viewed by 424

Special Issue Editors

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Guest Editor
Department of Finance, National Taipei University of Business, Taipei City 10051, Taiwan
Interests: machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung City 404348, Taiwan
Interests: e-learning; intelligent system; social computing; affective computing; multimedia system; artificial intelligence

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Guest Editor
Department of Information and Finance Management, National Taipei University of Technology, Taipei City 10608, Taiwan
Interests: artificial intelligence

Guest Editor
Department of Information Management, Shih Hsin University, Taipei 116005, Taiwan
Interests: spatial information integrated application technology; medical information; business intelligence and data exploration; data processing analysis

Special Issue Information

Dear Colleagues,

Machine learning, artificial intelligence and a wide field of related technologies (e.g., in data science and intelligent systems) have significantly contributed to research into sustainability. They have provided breakthrough concepts, state-of-the-art technology and a wide range of innovations to tackle the problems we face.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Machine learning and AI for environment and health;
  • Machine learning and AI for agriculture and industry 4.0;
  • Machine learning and AI for air, water and climate sustainability;
  • Machine learning and AI for smart energy, renewable energy and green fuel;
  • Machine learning and AI for smart cities;
  • Machine learning and AI for sustainable policy making;
  • Machine learning and AI for traffic management and transportation;
  • Machine learning benchmark datasets, platforms and tools for sustainability research.

We look forward to receiving your contributions.

Dr. Wei-Chen Wu
Dr. Jason C. Hung
Dr. Yuchih Wei
Dr. Jui-hung Kao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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. Big Data and Cognitive Computing is an international peer-reviewed open access monthly 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 1800 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.


  • machine learning
  • artificial intelligence
  • sustainability
  • deep learning
  • intelligent systems
  • industry 4.0
  • robotics
  • smart city
  • edge computing
  • data science
  • cognitive computing
  • big data

Published Papers

This special issue is now open for submission.
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