Hybrid learning is a complex combination of face-to-face and online learning. This model combines the use of multimedia materials with traditional classroom work. Virtual hybrid learning is employed alongside face-to-face methods. That aims to investigate using Artificial Intelligence (AI) to increase student engagement in hybrid learning settings. Educators are confronted with contemporary issues in maintaining their students’ interest and motivation as the popularity of online and hybrid education continues to grow, where many educational institutions are adopting this model due to its flexibility, student-teacher engagement, and peer-to-peer interaction. AI will help students communicate, collaborate, and receive real-time feedback, all of which are challenges in education. This article examines the advantages and disadvantages of hybrid education and the optimal approaches for incorporating Artificial Intelligence (AI) in educational settings. The research findings suggest that using AI can revolutionize hybrid education, as it enhances both student and instructor autonomy while fostering a more engaging and interactive learning environment.

In this study, we critically examine the potential of recycled construction materials, focusing on how these materials can significantly reduce greenhouse gas (GHG) emissions and energy usage in the construction sector. By adopting an integrated approach that combines Life Cycle Assessment (LCA) and Material Flow Analysis (MFA) within the circular economy framework, we thoroughly examine the lifecycle environmental performance of these materials. Our findings reveal a promising future where incorporating recycled materials in construction can significantly lower GHG emissions and conserve energy. This underscores their crucial role in advancing sustainable construction practices. Moreover, our study emphasizes the need for robust regulatory frameworks and technological innovations to enhance the adoption of environmentally responsible practices. We encourage policymakers, industry stakeholders, and the academic community to collaborate and promote the adoption of a circular economy strategy in the building sector. Our research contributes to the ongoing discussion on sustainable construction, offering evidence-based insights that can inform future policies and initiatives to improve environmental stewardship in the construction industry. This study aligns with the European Union’s objectives of achieving climate-neutral cities by 2030 and the United Nations’ Sustainable Development Goals outlined for completion by 2030. Overall, this paper contributes to the ongoing dialogue on sustainable construction, providing a fact-driven basis for future policy and initiatives to enhance environmental stewardship in the industry.

This article explores the possible ramifications of incorporating ideas from AEC Industry 6.0 into the design and construction of intelligent, environmentally friendly, and long-lasting structures. This statement highlights the need to shift away from the current methods seen in the AEC Industry 5.0 to effectively respond to the increasing requirement for creative and environmentally sustainable infrastructures. Modern building techniques have been made more efficient and long-lasting because of AEC Industry 6.0’s cutting-edge equipment, cutting-edge digitalization, and ecologically concerned methods. The academic community has thoroughly dissected the many benefits of AEC Industry 5.0. Examples are increased stakeholder involvement, automation, robotics for optimization, decision structures based on data, and careful resource management. However, the difficulties of implementing AEC Industry 6.0 principles are laid bare in this research. It calls for skilled experts who are current on the latest technologies, coordinate the technical expertise of many stakeholders, orchestrate interoperable standards, and strengthen cybersecurity procedures. This study evaluates how well the principles of Industry 6.0 can create smart, long-lasting, and ecologically sound structures. The goal is to specify how these ideas may revolutionize the building industry. In addition, this research provides an in-depth analysis of how the AEC industry might best adopt AEC Industry 6.0, underscoring the sector-wide significance of this paradigm change. This study thoroughly analyzes AEC Industry 6.0 about big data analytics, the IoT, and collaborative robotics. To better understand the potential and potential pitfalls of incorporating AEC Industry 6.0 principles into the construction of buildings, this study examines the interaction between organizational dynamics, human actors, and robotic systems.

The normal development of “smart buildings,” which calls for integrating sensors, rich data, and artificial intelligence (AI) simulation models, promises to usher in a new era of architectural concepts. AI simulation models can improve home functions and users’ comfort and significantly cut energy consumption through better control, increased reliability, and automation. This article highlights the potential of using artificial intelligence (AI) models to improve the design and functionality of smart houses, especially in implementing living spaces. This case study provides examples of how artificial intelligence can be embedded in smart homes to improve user experience and optimize energy efficiency. Next, the article will explore and thoroughly analyze the thorough analysis of current research on the use of artificial intelligence (AI) technology in smart homes using a variety of innovative ideas, including smart interior design and a Smart Building System Framework based on digital twins (DT). Finally, the article explores the advantages of using AI models in smart homes, emphasizing living spaces. Through the case study, the theme seeks to provide ideas on how AI can be effectively embedded in smart homes to improve functionality, convenience, and energy efficiency. The overarching goal is to harness the potential of artificial intelligence by transforming how we live in our homes and improving our quality of life. The article concludes by discussing the unresolved issues and potential future research areas on the usage of AI in smart houses. Incorporating AI technology into smart homes benefits homeowners, providing excellent safety and convenience and increased energy efficiency.

Artificial Intelligence (AI) simulation models and digital twins (DT) are used in designing and treating the activities, layout, and functions for the new generation of buildings to enhance user experience and optimize building performance. These models use data about a building’s use, configuration, functions, and environment to simulate different design options and predict their effects on house function efficiency, comfort, and safety. On the one hand, AI algorithms are used to analyze this data and find patterns and trends that can guide the design process. On the other hand, DTs are digital recreations of actual structures that can replicate building performance in real time. These models would evaluate alternative design options, the performance of the building, and ways to improve user comfort and building efficiency. This study examined the important role of intelligent building design aspects, such as activities using multi-layout and the creation of particular functions based on AI simulation models, in developing DT-based smart building systems. The empirical data came from a study of architecture and engineering firms throughout the globe using a CSAQ (computer-administered, self-completed survey). For this purpose, the study employed structural equation modeling (SEM) to examine the hypotheses and build the relationship model. The research verifies the relevance of AI-based simulation models supporting the creation of intelligent building design features (activities, layout, functionalities), enabling the construction of DT-based smart building systems. Furthermore, this study highlights the need for further exploration of AI-based simulation models’ role and integration with DT in smart building design.

The Construction 5.0 paradigm is the next phase in industrial development that aims to combine the skills of human experts in partnership with efficient and precise machines to achieve production solutions that are resource-efficient and preferred by clients. This study reviewed the evolution of the Construction 5.0 paradigm by defining its features and diverse nature. It introduced the architecture, model, and system of Construction 5.0 and its key enablers: Operator 5.0, Society 5.0, human-centricity, sustainability, and resilience. The study used the SEM method to evaluate the research model and investigate the causal relationships among the key enablers of the Construction 5.0 paradigm. Nine vital hypotheses were proposed and assessed comprehensively. The critical enablers’ variables were measured to examine the constructs’ reliability and validity. The key findings showed that Construction 5.0 prioritizes collaboration between humans and machines, merges cyberspace with physical space, and balances the three pillars of sustainability (economy, environment, and society), creating a relationship among Operator 5.0, Society 5.0, human-Ccentricity, sustainability, and resilience. The study also discussed the limitations and challenges and offered suggestions for future research. Overall, Construction 5.0 aims to achieve sustainable development and become a robust and resilient provider of prosperity in an industrial community of a shared future. The study expects to spark debate and promote pioneering research toward the Construction 5.0 paradigm.