Industry 4.0 has been provided for the last 10 years to benefit the industry and the shortcomings; finally, the time for industry 5.0 has arrived. Smart factories are increasing the business productivity; therefore, industry 4.0 has limitations. In this paper, there is a discussion of the industry 5.0 opportunities as well as limitations and the future research prospects. Industry 5.0 is changing paradigm and brings the resolution since it will decrease emphasis on the technology and assume that the potential for progress is based on collaboration among the humans and machines. The industrial revolution is improving customer satisfaction by utilizing personalized products. In modern business with the paid technological developments, industry 5.0 is required for gaining competitive advantages as well as economic growth for the factory. The paper is aimed to analyze the potential applications of industry 5.0. At first, there is a discussion of the definitions of industry 5.0 and advanced technologies required in this industry revolution. There is also discussion of the applications enabled in industry 5.0 like healthcare, supply chain, production in manufacturing, cloud manufacturing, etc. The technologies discussed in this paper are big data analytics, Internet of Things, collaborative robots, Blockchain, digital twins and future 6G systems. The study also included difficulties and issues examined in this paper head to comprehend the issues caused by organizations among the robots and people in the assembly line.

This review paper provides a comprehensive analysis of the automation of smart education in the context of Industry 5.0 from 78 papers, focusing on the integration of advanced technologies and the development of innovative, effective, and ethical educational solutions for the future workforce. As the world transitions into an era characterized by human–machine collaboration and rapidly evolving technologies, there is an urgent need to recognize the pivotal role of smart education in preparing individuals for the opportunities and challenges presented by the new industrial landscape. The paper examines key components of smart education, including intelligent tutoring systems, adaptive learning environments, learning analytics, and the application of the Internet of Things (IoT) in education. It also discusses the role of advanced technologies such as artificial intelligence (AI), machine learning (ML), robotics, and augmented and virtual reality (AR/VR) in shaping personalized and immersive learning experiences. The review highlights the importance of smart education in addressing the growing demand for upskilling and reskilling, fostering a culture of lifelong learning, and promoting adaptability, resilience, and self-improvement among learners. Furthermore, the paper delves into the challenges and ethical considerations associated with the implementation of smart education, addressing issues such as data privacy, the digital divide, teacher and student readiness, and the potential biases in AI-driven systems. Through a presentation of case studies and examples of successful smart education initiatives, the review aims to inspire educators, policymakers, and industry stakeholders to collaborate and innovate in the design and implementation of effective smart education solutions. Conclusively, the paper outlines emerging trends, future directions, and potential research opportunities in the field of smart education, emphasizing the importance of continuous improvement and the integration of new technologies to ensure that education remains relevant and effective in the context of Industry 5.0. By providing a holistic understanding of the key components, challenges, and potential solutions associated with smart education, this review paper seeks to contribute to the ongoing discourse surrounding the automation of smart education and its role in preparing the workforce for the future of work.

In the quest to meet the escalating demands of citizens, future smart cities emerge as crucial entities. Their role becomes even more vital given the current challenges posed by rapid urbanization and the need for sustainable and inclusive living spaces. At the heart of these future smart cities are advancements in information and communication technologies, with Industry 5.0 playing an increasingly significant role. This paper endeavors to conduct an exhaustive survey to analyze future technologies, including the potential of Industry 5.0 and their implications for smart cities. The crux of the paper is an exploration of technological advancements across various domains that are set to shape the future of urban environments. The discussion spans diverse areas including but not limited to cyber–physical systems, fog computing, unmanned aerial vehicles, renewable energy, machine learning, deep learning, cybersecurity, and digital forensics. Additionally, the paper sheds light on the specific role of Industry 5.0 in the smart city context, illuminating its impact on enabling advanced cybersecurity measures, fostering human–machine collaboration, driving intelligent automation in urban services, and refining data management and decision making. The paper also offers an in-depth review of the existing frameworks that are shaping smart city applications, evaluating how Industry 5.0 technologies could augment these frameworks. In particular, the paper delves into the various technological challenges that smart cities face, bringing potential Industry 5.0-enabled solutions to the fore.

This paper investigates the integration of ChatGPT into educational environments, focusing on its potential to enhance personalized learning and the ethical concerns it raises. Through a systematic literature review, interest analysis, and case studies, the research scrutinizes the application of ChatGPT in diverse educational contexts, evaluating its impact on teaching and learning practices. The key findings reveal that ChatGPT can significantly enrich education by offering dynamic, personalized learning experiences and real-time feedback, thereby boosting teaching efficiency and learner engagement. However, the study also highlights significant challenges, such as biases in AI algorithms that may distort educational content and the inability of AI to replicate the emotional and interpersonal dynamics of traditional teacher–student interactions. The paper acknowledges the fast-paced evolution of AI technologies, which may render some findings obsolete, underscoring the need for ongoing research to adapt educational strategies accordingly. This study provides a balanced analysis of the opportunities and challenges of ChatGPT in education, emphasizing ethical considerations and offering strategic insights for the responsible integration of AI technologies. These insights are valuable for educators, policymakers, and researchers involved in the digital transformation of education.

The necessity for substantial societal transformations to meet the Sustainable Development Goals (SDGs) has become more urgent, especially in the wake of the COVID-19 pandemic. This paper examines the critical role of disruptive technologies, specifically Industry 5.0 and Society 5.0, in driving sustainable development. Our research investigation focuses on their impact on product development, healthcare innovation, pandemic response, and the development of nature-inclusive business models and smart cities. We analyze how these technologies influence SDGs 3 (Good Health and Well-Being), 4 (Quality Education), 9 (Industry, Innovation, and Infrastructure), and 11 (Sustainable Cities and Communities). By integrating these concepts into smart cities, we propose a coordinated framework to enhance the achievement of these goals. Additionally, we provide a SWOT analysis to evaluate this approach. This study aims to guide industrialists, policymakers, and researchers in leveraging technological advancements to meet the SDGs.

This study evaluates the capabilities and limitations of generative AI, specifically ChatGPT, in conducting systematic literature reviews. Using the PRISMA methodology, we analysed 124 recent studies, focusing in-depth on a subset of 40 selected through strict inclusion criteria. Findings show that ChatGPT can enhance efficiency, with reported workload reductions averaging around 60–65%, though accuracy varies widely by task and context. In structured domains such as clinical research, title and abstract screening sensitivity ranged from 80.6% to 96.2%, while precision dropped as low as 4.6% in more interpretive tasks. Hallucination rates reached 91%, underscoring the need for careful oversight. Comparative analysis shows that AI matches or exceeds human performance in simple screening but underperforms in nuanced synthesis. To support more reliable integration, we introduce the Systematic Research Processing Framework (SRPF) as a guiding model for hybrid AI–human collaboration in research review workflows.