A New Generation of Artificial Intelligence Applications for Environmental Sustainability
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "AI-Enabled Process Engineering".
Deadline for manuscript submissions: closed (30 November 2023)
Special Issue Editors
Interests: environmental sustainability; chemometric simulation; artificial intelligence; optimization algorithms
Interests: chemometrics; air pollution; environmental pollution; machine learning; artificial intelligence; water resources
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Artificial intelligence (AI) has the potential to revolutionize environmental sustainability efforts by providing innovative solutions to complex challenges. AI can help to analyze vast amounts of data, identify patterns, and generate insights that can inform decision-making processes related to climate change, chemo-environmental factors, pollution, hydro-environmental factors, energy consumption, and natural resource management. One of the significant applications of AI in environmental sustainability is monitoring and managing natural resources. AI-powered systems can track real-time deforestation, water quality, soil degradation, and wildlife habitat destruction. This information can help conservationists and policymakers make informed decisions and take prompt action to mitigate environmental damage. AI can also help to reduce greenhouse gas emissions and combat climate change by optimizing energy consumption in buildings and transportation systems. Recently, new technologies and methods have also been used in environmental sustainability and management, such as satellite remote sensing technology, big data mining technology, artificial intelligence, etc. In addition, the impact of environmental modelling is of highly interest. Advanced modelling techniques and simulations may provide the necessary support for authorities, decisionmakers, and ordinary stakeholders. We sincerely invite authors to contribute original reviews and research manuscripts focused on developing and improving environmental modelling and investigating sustainable and built environment management applications. In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Environmental modelling and simulation;
- Chemometric-based intelligent systems;
- Hydro-environmental modelling;
- Process monitoring and simulation;
- Sustainable management and simulation;
- Machine learning-based environmental application.
Dr. Sani Isah Abba
Dr. Abdullahi Garba Usman
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes 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
- artificial intelligence
- process modelling
- environment
- sustainability
- chemometric application
- ecosystem
- simulation
- modelling
- emissions
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