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@article{172746,
        author = {Maharishi Thula},
        title = {AI-Driven Self-Healing Smart Concrete: A Paradigm Shift in Sustainable Architecture and Structural Resilience},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {1021-1024},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172746},
        abstract = {The integration of Artificial Intelligence (AI) in self-healing smart concrete represents a ground-breaking advancement in sustainable architecture and structural resilience. Traditional concrete, despite its widespread use, is prone to cracking and degradation, leading to high maintenance costs and environmental concerns. This research explores the role of AI in optimizing self-healing concrete by enhancing its material composition, predictive maintenance, and autonomous repair mechanisms. AI-driven algorithms can analyse vast datasets to identify the most effective bacteria-based, polymeric, or chemical healing agents, while embedded sensors and LOT systems enable real-time structural monitoring and predictive analytics. The study further examines the economic, environmental, and structural benefits of AI-enhanced self-healing concrete compared to conventional materials. Through case studies, computational modelling, and comparative analysis, the research aims to establish AI-driven smart concrete as a transformative solution for resilient and sustainable urban infrastructure. The findings will provide architects, engineers, and urban planners with insights into how AI-powered materials can redefine the future of construction, promoting long-lasting, eco-friendly, and self-sufficient built environments.},
        keywords = {Smart concrete, Artificial Intelligence in construction, Advanced construction materials},
        month = {February},
        }