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AI from Industry 4.0 to Industry 5.0: Engineering for Social...
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AI from Industry 4.0 to Industry 5.0: Engineering for Social Change

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 August 2025 | Viewed by 5733

Special Issue Editors

Dr. Ching-Hung Lee

E-Mail Website
Guest Editor
School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China
Interests: AI in healthcare; service design; smart retail; knowledge-based systems; digital transformation; e-government; sectoral systems of innovation
Special Issues, Collections and Topics in MDPI journals
Dr. Lingguo Bu

E-Mail Website
Guest Editor
School of Software, Shandong University, Jinan, China
Interests: human factors; design methods; multimodal data fusion
Dr. Danni Chang

E-Mail Website
Guest Editor
School of Design, Shanghai Jiao Tong University, Shanghai, China
Interests: industrial design; smart product service system; design and human factors

Special Issue Information

Dear Colleagues,

The rapid evolution of Industry 4.0 has ushered in unprecedented advancements in automation, data exchange, and manufacturing technologies, primarily driven by artificial intelligence (AI). As we transition to Industry 5.0, the emphasis shifts from mere automation to a harmonious collaboration between humans and intelligent systems, focusing on sustainability, resilience, and societal wellbeing. This Special Issue aims to explore how AI and the upcoming Generative AI (GenAI) can be harnessed to engineer social change, fostering an inclusive, ethical, and human-centric industrial paradigm.

We are excited to announce a call for papers to be submitted to our upcoming Special Issue, dedicated to "AI From Industry 4.0 to Industry 5.0: Engineering for Social Change". This Special Issue will delve into the applications of AI technologies in Industry 4.0 and their evolution into the socially responsible frameworks of Industry 5.0, encompassing smart manufacturing and smart cities.

Scenes and topics of interest include, but are not limited to, the following:

  1. AI-Driven Sustainability in Smart Manufacturing
  • Waste Reduction: Using AI for predictive analytics and process optimization to minimize material waste and enhance recycling.
  • Supply Chain Sustainability: Integrating AI to develop sustainable supply chain practices, such as reducing carbon footprints and improving resource allocation.
  1. AI-driven Order Fulfillment and Smart Commercialization
  • Optimized Inventory Management: Using AI to predict demand and manage inventory levels efficiently.
  • Automated Order Processing: Implementing AI for real-time order processing and error reduction.
  • Personalized Customer Experience: Leveraging AI to analyze customer data and provide personalized shopping experiences and recommendations.
  1. Human–AI Collaboration for Enhanced Workplace Safety and Productivity
  • Training and Skill Development: Developing AI-driven training programs that adapt to individual learning needs and enhance worker skills in a dynamic industrial setting.
  • Augmented Workforce: Utilizing AI-powered wearable technology and robotics to assist workers in hazardous environments.
  • Ergonomics and Health Monitoring: Implementing AI systems to monitor worker health, ergonomics, and fatigue to prevent workplace injuries.
  1. Ethical AI and Governance Frameworks for Industry 5.0
  • AI for Resilience: Enhancing community and industrial resilience in the face of global challenges.
  • AI in Education and Skills Development: Advancing education and training to prepare the workforce for Industry 5.0.
  • Policy and Governance: Developing policies and governance models for ethical AI deployment.
  • Bias and Fairness: Developing methods to detect and mitigate biases in AI systems to ensure fair treatment of all stakeholders.
  • Transparency and Accountability: Creating frameworks that enhance the transparency of AI decision-making processes and establish accountability mechanisms.
  • Regulatory and Policy Recommendations: Proposing policy guidelines and regulatory measures that support ethical AI development and deployment in industrial applications.

We welcome original research articles, review papers, case studies, and perspectives that offer valuable insights into the application of AI technologies in the Industry 5.0 era and smart manufacturing and smart cities.

Dr. Ching-Hung Lee
Dr. Lingguo Bu
Dr. Danni Chang
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

  • Industry 4.0
  • Industry 5.0
  • digital product–service systems
  • smart manufacturing
  • human–AI collaboration
  • generative AI

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Published Papers (3 papers)

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30 pages, 6427 KiB  
Article
Artificial Intelligence of Things Infrastructure for Quality Control in Cast Manufacturing Environments Shedding Light on Industry Changes
by Cosmina-Mihaela Rosca, Gabriel Rădulescu and Adrian Stancu
Appl. Sci. 2025, 15(4), 2068; https://doi.org/10.3390/app15042068 - 16 Feb 2025
Cited by 4 | Viewed by 793
Abstract
The transition from Industry 4.0 to 5.0 raises concerns about integrating advanced quality control measures by replacing humans. The biggest challenge of this transition is infrastructure compatibility. This paper proposes a remote collaboration solution via the Internet of Things (IoT) infrastructure. The study [...] Read more.
The transition from Industry 4.0 to 5.0 raises concerns about integrating advanced quality control measures by replacing humans. The biggest challenge of this transition is infrastructure compatibility. This paper proposes a remote collaboration solution via the Internet of Things (IoT) infrastructure. The study identifies challenges in implementing such strategies and highlights the importance of AI–human collaboration, aligning with Industry 5.0 concepts. This research integrates data from multiple visual sensors (cameras) and devices into an IoT framework to create a monitoring system. This system’s application focuses on ensuring cast quality control standards. The proposed artificial AI method provides compatibility for the entire infrastructure. The Nonconformity Indicator Algorithm (NIA) was designed for defect detection. NIA, developed using Azure Custom Vision Service, identified and classified manufactured product defects based on image analysis with an Accuracy of 98.18%, Precision of 98.44%, Recall of 96.56%, and F1-Score of 97.50%. Furthermore, an IoT-based monitoring system was designed that employs real-time sensor fusion techniques for quality control in cast manufacturing environments. The system integrates data from multiple devices, including visual sensors like the ESP32-CAM, within an IoT framework powered by Azure IoT Hub and Azure Custom Vision Service. This infrastructure enables the compatibility of devices by facilitating communication via an Azure Event Grid Trigger integrated into an Azure Function through Azure IoT Hub. Full article
(This article belongs to the Special Issue AI from Industry 4.0 to Industry 5.0: Engineering for Social Change)
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28 pages, 2394 KiB  
Article
Industry 5.0: Are We Going to Accept Robots as Co-Workers in Office Environments? An Empirical Analysis
by Gozde Doven, Bulent Sezen, Kadir Alpaslan Demir and Yavuz Selim Balcioglu
Appl. Sci. 2025, 15(3), 1591; https://doi.org/10.3390/app15031591 - 5 Feb 2025
Viewed by 1038
Abstract
This research aims to assess the readiness of professionals working in offices to accept robots as co-workers, and to provide insight for robot developers and organizations in promoting robot acceptance. This study investigates the acceptance of robots in office environments using the Unified [...] Read more.
This research aims to assess the readiness of professionals working in offices to accept robots as co-workers, and to provide insight for robot developers and organizations in promoting robot acceptance. This study investigates the acceptance of robots in office environments using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, extended with a specific focus on perceived sociability. A two-country comparative approach was employed. The research involved participants from the United Kingdom and Turkey to explore differences on robot acceptance. Data were collected via a structured questionnaire with demographics, robot usage or intention to use, and robot appearance preferences, targeting working professionals in office environments. The findings highlight key factors influencing behavioral intentions to use robots, including performance expectancy, effort expectancy, social influence, and perceived sociability. Our research results indicate that robots will likely to be accepted in our future office work environments. The results provide actionable insights for designing socially interactive robots and utilizing them in diverse workplace environments. Future research directions include expanding the cultural scope and utilizing qualitative methods for the additional investigation of factors that may enhance our understanding of robot acceptance. Full article
(This article belongs to the Special Issue AI from Industry 4.0 to Industry 5.0: Engineering for Social Change)
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22 pages, 2251 KiB  
Article
Humanoid Robots in Tourism and Hospitality—Exploring Managerial, Ethical, and Societal Challenges
by Ida Skubis, Agata Mesjasz-Lech and Joanna Nowakowska-Grunt
Appl. Sci. 2024, 14(24), 11823; https://doi.org/10.3390/app142411823 - 18 Dec 2024
Cited by 1 | Viewed by 2978
Abstract
The paper evaluates the benefits and challenges of employing humanoid robots in tourism and hospitality, examining their roles, decision-making processes, human-centric approaches, and oversight mechanisms. Data will be collected from a variety of sources, including academic journals, websites of the companies where the [...] Read more.
The paper evaluates the benefits and challenges of employing humanoid robots in tourism and hospitality, examining their roles, decision-making processes, human-centric approaches, and oversight mechanisms. Data will be collected from a variety of sources, including academic journals, websites of the companies where the robots operate, case studies, and news articles. Specific attention will be given to concrete examples of humanoid robots deployed in the tourism and hospitality sector, such as Connie, Spencer, and Henn-na Hotel’s robots. Robots highlight the potential to assume roles traditionally occupied by humans. The presence of humanoid robots also influences cultural practices and social interactions within the hospitality context. Humanoid robots also have the potential to improve equity and accessibility in the tourism and hospitality industry. The interaction between humans and humanoid robots can have psychological and emotional effects on both guests and employees. Finally, the usage of humanoid robots intersects with broader sustainability operational efficiency and customer satisfaction across various sectors within the tourism and hospitality industry. Introducing humanoid robots represents a challenge in innovation that holds promise for revolutionizing service delivery and guest experiences. Full article
(This article belongs to the Special Issue AI from Industry 4.0 to Industry 5.0: Engineering for Social Change)
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