In the last years, Artificial Intelligence (AI) is emerging as a transformative force in enhancing operational efficiency, predictive analytics, and decision-making within construction processes. By leveraging AI-driven systems, the construction industry can achieve safer, smarter, and more sustainable construction practices. Consequently, the construction sector is undergoing a paradigm shift as AI technologies redefine traditional methods and address critical challenges, particularly in hazardous environments and physically demanding tasks. Research in this area is flourishing, creating a comprehensive framework of methods, data, and results, demonstrating the scalability and adaptability of AI in various construction-related fields. Studies highlight assessment models as key solutions for the construction industry, focusing on air pollutant estimation, concrete performance, and workforce safety. Worker health and air pollution in construction sites remain pivotal concerns. Also, the use of IoT and wearable sensors for human activity recognition in construction, combined with AI, demonstrates significant potential to improve occupational safety.

This Research Topic aims to demonstrate the flexibility and effectiveness of intelligent systems in meeting construction needs. There are still research gaps, including the need for wider AI integration across various construction settings and further validation of models in practical contexts. It will address the current limitations by expanding AI integration across diverse settings and validating models in real-world applications. The focus is on investigating new AI approaches and refining existing algorithms to improve robustness, accuracy, integration, and practical impact. The goal is to showcase AI's transformative potential in promoting sustainability, enhancing operational efficiency, and improving safety measures in the construction industry. Additionally, it provides a roadmap for future research, offering valuable insights for construction industry stakeholders interested in adopting AI technologies.

Topics of interest include but are not limited to:

-AI-driven safety monitoring systems for construction sites;
-Machine learning for predictive risk assessment in construction projects;
-AI-powered tools for optimizing construction workflows and resource allocation;
-Deep learning for analyzing worker health indicators and ensuring ergonomic practices;
-Intelligent systems for detecting hazards and monitoring structural integrity;
-Wearable and IoT-integrated AI systems for real-time worker health and safety monitoring;
-Generative AI in construction design and planning for efficiency and innovation;
-Data-driven management systems for sustainable construction practices;
-Ethical and regulatory considerations in AI adoption within the construction sector;
-AI for environmental impact assessments and reducing construction waste.

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Intelligent Systems in Construction: Predictive Insights and Advanced Solutions

Topic Coordinator