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Applied Sciences
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AI for Sustainability and Innovation—2nd Edition
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AI for Sustainability and Innovation—2nd Edition

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 July 2025 | Viewed by 5719

Special Issue Editors

Prof. Dr. Ah-Lian Kor

E-Mail Website
Guest Editor
School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds LS6 3QS, UK
Interests: machine learning; intelligent agents; cloud and edge intelligence; IoT; smart buildings; smart manufacturing; qualitative reasoning
Special Issues, Collections and Topics 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: networks; green IT/neworking; industrial networks
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Karl Andersson

E-Mail Website
Guest Editor
Pervasive and Mobile Computing Luleå, University of Technology, SE-93187 Skellefteå, Sweden
Interests: pervasive and mobile computing
Special Issues, Collections and Topics in MDPI journals

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 systems; 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). As such, this Special Issue calls for AI-enabled research (positional, theoretical, or applied) that addresses 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. This is a cutting-edge research theme, considering the pervasiveness of AI in every sector (see the summary for details). We 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 your submissions.

Prof. Dr. 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 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. 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 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
  • sustainable IT
  • innovation
  • smart and pervasive technologies
  • smart systems
  • cloud computing
  • green networking
  • mobile technologies
  • machine learning
  • Internet of Things

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

11 pages, 1727 KiB  
Article
JLMS25 and Jiao-Liao Mandarin Speech Recognition Based on Multi-Dialect Knowledge Transfer
by Xuchen Li, Yiqun Wang, Xiaoyang Liu, Kun Su, Zhaochen Li, Yitian Wang, Bin Jiang, Kang Xie and Jie Liu
Appl. Sci. 2025, 15(3), 1670; https://doi.org/10.3390/app15031670 - 6 Feb 2025
Viewed by 638
Abstract
Jiao-Liao Mandarin, a distinguished dialect in China, reflects the linguistic features and cultural heritage of the Jiao-Liao region. However, the labor-intensive and costly nature of manual transcription limits the scale of transcribed corpora, posing challenges for speech recognition. We present JLMS25, a transcribed [...] Read more.
Jiao-Liao Mandarin, a distinguished dialect in China, reflects the linguistic features and cultural heritage of the Jiao-Liao region. However, the labor-intensive and costly nature of manual transcription limits the scale of transcribed corpora, posing challenges for speech recognition. We present JLMS25, a transcribed corpus for Jiao-Liao Mandarin, alongside a novel multi-dialect knowledge transfer (MDKT) framework for low-resource speech recognition. By leveraging phonetic and linguistic knowledge from neighboring dialects, the MDKT framework improves recognition in resource-constrained settings. It comprises an acoustic feature extractor, a dialect feature extractor, and two modules—WFAdapter (weight decomposition adapter) and AttAdapter (attention-based adapter)—to enhance adaptability and mitigate overfitting. The training involves a three-phase strategy: multi-dialect AID-ASR multi-task learning in phase one, freezing the dialect feature extractor in phase two, and fine-tuning only the adapters in phase three. Experiments on the Jiao-Liao Mandarin subset of the KeSpeech dataset and JLMS25 dataset show that MDKT outperforms full-parameter fine-tuning, reducing Character Error Rate (CER) by 5.4% and 7.7% and Word Error Rate (WER) by 6.1% and 10.8%, respectively. Full article
(This article belongs to the Special Issue AI for Sustainability and Innovation—2nd Edition)
►▼ Show Figures

Figure 1

Figure 1
<p>Dataset Construction Workflow.</p> Full article ">Figure 2
<p>Data statistics. (<b>a</b>) Percentage distribution of volunteers’ ages. (<b>b</b>) Percentage distribution of transcription topics in JLMS25.</p> Full article ">Figure 3
<p>The structure of MDKT.</p> Full article ">Figure 4
<p>The structure of the proposed WFAdapter (<b>a</b>) and AttAdapter (<b>b</b>).</p> Full article ">
30 pages, 2386 KiB  
Article
Sustainable Development in the Digital Age: Harnessing Emerging Digital Technologies to Catalyze Global SDG Achievement
by Claudiu George Bocean
Appl. Sci. 2025, 15(2), 816; https://doi.org/10.3390/app15020816 - 15 Jan 2025
Viewed by 1292
Abstract
The digital revolution, characterized by rapid technological advancements, presents a unique opportunity to accelerate progress towards the United Nations’ Sustainable Development Goals (SDGs). This research explores the transformative potential of cutting-edge digital technologies—including artificial intelligence, big data analytics, cloud computing, and the Internet [...] Read more.
The digital revolution, characterized by rapid technological advancements, presents a unique opportunity to accelerate progress towards the United Nations’ Sustainable Development Goals (SDGs). This research explores the transformative potential of cutting-edge digital technologies—including artificial intelligence, big data analytics, cloud computing, and the Internet of Things—in fostering sustainable development across economic, social, and environmental dimensions. Our study employs a rigorous empirical approach to quantify the impact of digital innovation on SDG achievement within the European Union. Utilizing the Digital Economy and Society Index (DESI) as a comprehensive measure of technological progress, we apply structural equation modeling to emphasize the complex interplay between digital advancement and sustainable development indicators. A key focus of our analysis is the mediating role of economic performance, measured by GDP per capita, in the relationship between digital technology adoption and SDG progress. This nuanced examination provides insights into how economic factors influence the effectiveness of digital solutions in addressing global challenges. Our findings underscore the need for adaptive policies that harness the power of digital technologies while addressing potential challenges and ensuring inclusive growth. Full article
(This article belongs to the Special Issue AI for Sustainability and Innovation—2nd Edition)
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Figure 1

Figure 1
<p>Research model of digitalization influences on sustainability. Source: author’s design.</p> Full article ">Figure 2
<p>Models for the direct and indirect influence of DESI on SDGi, and SDG1–SDG5. Source: author’s design using SmartPLS v3.0.</p> Full article ">Figure 3
<p>Models for the direct and indirect influence of the DESI on SDG6–SDG11. Source: authors’ design using SmartPLS v3.0.</p> Full article ">Figure 4
<p>Models for the direct and indirect influence of DESI on SDG12–SDG17. Source: author’s design using SmartPLS v3.0.</p> Full article ">
20 pages, 2007 KiB  
Article
Hybrid Intelligence: Design for Sustainable Multiverse via Integrative Cognitive Creation Model through Human–Computer Collaboration
by Yuqi Liu and Zhiyong Fu
Appl. Sci. 2024, 14(11), 4662; https://doi.org/10.3390/app14114662 - 29 May 2024
Cited by 2 | Viewed by 2687
Abstract
The unprecedented development of artificial intelligence (AI) makes it possible for computers to imitate and surpass human intelligence (HI). Hybrid intelligence is the result of the co-evolution of AI and HI and has huge application potential in promoting the sustainable development of human [...] Read more.
The unprecedented development of artificial intelligence (AI) makes it possible for computers to imitate and surpass human intelligence (HI). Hybrid intelligence is the result of the co-evolution of AI and HI and has huge application potential in promoting the sustainable development of human society. This study starts from the similarities and differences between biological neural networks and artificial neural networks, compares the cognitive foundations of human intelligence and artificial intelligence, highlights the difference and connection between AI and HI, and puts forward the necessity and inevitability of their co-evolution to achieve hybrid intelligence with complementary advantages. Hybrid intelligence stands to become the pivotal force driving purposeful and planned sustainable creative behavior in the artificial intelligence era. This study proposes a design cognitive creation model based on human–computer collaboration that considers computational design thinking as the central concept. Moreover, the paradigm shift of design under hybrid intelligence intervention are explored from five aspects: “tool evolution”, “response mode”, “output result”, “iterative optimization” and “system innovation”. Finally, this article constructs a creative intervention mechanism of design creation driven by hybrid intelligence and discusses its role playing in the design activities of sustainable multiverse construction in the future. The proposal of the multiverse model transcends the confines of the metaverse’s virtual worldview and embraces sustainable development for value guidance. It advocates a future trajectory for humanity that hinges on technological progress, fostering a prosperous, balanced, and harmonious coexistence between the natureverse, socialverse, and digitalverse. This approach is not only rational and scientific, but also inherently sustainable. Full article
(This article belongs to the Special Issue AI for Sustainability and Innovation—2nd Edition)
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Figure 1

Figure 1
<p>The cognitive foundations of artificial intelligence and human intelligence. Note: the figure is drawn by the authors.</p> Full article ">Figure 2
<p>The design cognitive model of hybrid intelligence via human–computer collaboration. Note: the figure is drawn by the authors.</p> Full article ">Figure 3
<p>The evolution of human society, production, and design tools. Note: the figure is drawn by the authors.</p> Full article ">Figure 4
<p>Design for sustainable multiverse via hybrid intelligence creation mode. Note: the figure is drawn by the authors.</p> Full article ">
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