Special Issue "AI for Sustainability and Innovation"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 April 2022.

Special Issue Editors

Dr. Ah-Lian Kor
E-Mail Website
Guest Editor
School of Built Environment, Engineering and Computing, Leeds Beckett University, Headingley Campus, Leeds LS6 3QS, UK
Interests: sustainability; cognitive systems; knowledge-based systems
Special Issues and Collections in MDPI journals
Prof. Dr. Eric Rondeau
E-Mail Website
Guest Editor
Faculté des Sciences et Technologies, University of Lorraine, Vandoeuvre Les Nancy, France
Interests: sustainable networking; software defined networks; network function virtualization; smart IoT systems
Prof. Dr. Karl Andersson
E-Mail Website
Guest Editor
Pervasive and Mobile Computing Luleå, University of Technology, SE-93187 Skellefteå, Sweden
Interests: mobile and pervasive technologies; wireless networks; 5G networks

Special Issue Information

Dear Colleagues,

“AI for Sustainability and Innovation” aims to support GESI’s Smarter2030 initiative and the UN’s Sustainable Development Goals in order to contribute to a sustainable future. This theme encompasses theoretical and applied research to address challenges relating to society and human needs (SDG2 Zero Hunger: autonomous machines, smart, and precision agriculture to increase productivity and reduce waste;  SDG3 Good Health and Well Being: smart and personalized health;  SDG4 Quality Education: smart  and personalized educational technologies), sustainable amenities and utilities for the environment (SDG7 Affordable and Clean Energy: smart grid, smart microgrid, and smart renewable energy management system; SDG13 Climate Change via Low Carbon Growth: smart technologies to reduce energy, as well as resource consumption and waste emissions; SDG11 Sustainable Cities and Communities: smart  sustainable cities and infrastructure), and sustainable industry (SDG9 Industry, Innovation, and Infrastructure: smart technologies to support Industry 4.0; SDG12 Responsible Consumption and Production: smart technologies for resource optimization, energy efficiency, and waste reduction). In summary, this Special Issue, titled “AI for Sustainability and Innovation”, calls for AI-enabled research (position, theoretical, or applied) that address relevant SDGs across the following sectors (listed in GESI’s Smarter 2020 initiative): business, power, transportation, manufacturing, services (education and health), agriculture, and buildings.

We are honored to be given the opportunity to undertake this Special Issue titled “AI for Sustainability and Innovation”. This research theme is very current and cutting edge, considering the pervasiveness of AI in every sector (see the summary for details). We would like to cordially invite you to submit any of the following: survey papers that encompass a relevant comprehensive and critical literature review; theoretical research papers that address underlying design concepts, theories, principles, or algorithms; or applied research papers that address the implementation, deployment, and evaluation of relevant smart technologies.

Thank you very much and we look forward to receiving submission of your quality research work.

Kind Regards,

Assoc. Prof. Ah-Lian Kor
Prof. Dr. Eric Rondeau
Prof. Dr. Karl Andersson
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 papers will be 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. Applied Sciences 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 2000 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
  • sustainable IT
  • innovation
  • smart and pervasive technologies
  • smart systems
  • cloud computing
  • green networking
  • mobile technologies
  • machine learning
  • Internet of Things

Published Papers (2 papers)

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Article
AI Approaches to Environmental Impact Assessments (EIAs) in the Mining and Metals Sector Using AutoML and Bayesian Modeling
Appl. Sci. 2021, 11(17), 7914; https://doi.org/10.3390/app11177914 - 27 Aug 2021
Viewed by 175
Abstract
Mining engineers and environmental experts around the world still identify and evaluate environmental risks associated with mining activities using field-based, basic qualitative methods The main objective is to introduce an innovative AI-based approach for the construction of environmental impact assessment (EIA) indexes that [...] Read more.
Mining engineers and environmental experts around the world still identify and evaluate environmental risks associated with mining activities using field-based, basic qualitative methods The main objective is to introduce an innovative AI-based approach for the construction of environmental impact assessment (EIA) indexes that statistically reflects and takes into account the relationships between the different environmental factors, finding relevant patterns in the data and minimizing the influence of human bias. For that, an AutoML process developed with Bayesian networks is applied to the construction of an interactive EIA index tool capable of assessing dynamically the potential environmental impacts of a slate mine in Galicia (Spain) surrounded by the Natura 2000 Network. The results obtained show the moderate environmental impact of the whole exploitation; however, the strong need to protect the environmental factors related to surface and subsurface runoff, species or soil degradation was identified, for which the information theory results point to a weight between 6 and 12 times greater than not influential variables. Full article
(This article belongs to the Special Issue AI for Sustainability and Innovation)
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Review
Six-Gear Roadmap towards the Smart Factory
Appl. Sci. 2021, 11(8), 3568; https://doi.org/10.3390/app11083568 - 15 Apr 2021
Cited by 1 | Viewed by 774
Abstract
The fourth industrial revolution is the transformation of industrial manufacturing into smart manufacturing. The advancement of digital technologies that make the trend Industry 4.0 are considered as the transforming force that will enable this transformation. However, Industry 4.0 digital technologies need to be [...] Read more.
The fourth industrial revolution is the transformation of industrial manufacturing into smart manufacturing. The advancement of digital technologies that make the trend Industry 4.0 are considered as the transforming force that will enable this transformation. However, Industry 4.0 digital technologies need to be connected, integrated and used effectively to create value and to provide insightful information for data driven manufacturing. Smart manufacturing is a journey and requires a roadmap to guide manufacturing organizations for its adoption. The objective of this paper is to review different methodologies and strategies for smart manufacturing implementation to propose a simple and a holistic roadmap that will support the transition into smart factories and achieve resilience, flexibility and sustainability. A comprehensive review of academic and industrial literature was preformed based on multiple stage approach and chosen criteria to establish existing knowledge in the field and to evaluate latest trends and ideas of Industry 4.0 and smart manufacturing technologies, techniques and applications in the manufacturing industry. These criteria are sub-grouped to fit within various stages of the proposed roadmap and attempts to bridge the gap between academia and industry and contributes to a new knowledge in the literature. This paper presents a conceptual approach based on six stages. In each stage, key enabling technologies and strategies are introduced, the common challenges, implementation tips and case studies of industrial applications are discussed to potentially assist in a successful adoption. The significance of the proposed roadmap serve as a strategic practical tool for rapid adoption of Industry 4.0 technologies for smart manufacturing and to bridge the gap between the advanced technologies and their application in manufacturing industry, especially for SMEs. Full article
(This article belongs to the Special Issue AI for Sustainability and Innovation)
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