Smart Self-Healing Concrete using AI-Optimized Microbial Agents for Sustainable Infrastructure

Abstract

The rapid deterioration of concrete structures due to cracks and environmental stressors poses significant challenges for sustainable infrastructure. Traditional repair methods are often costly, labor-intensive, and environmentally damaging. Smart self-healing concrete, integrated with AI-optimized microbial agents, presents a revolutionary solution to enhance structural longevity and resilience. This technology leverages bio-mineralization by bacteria such as Bacillus subtilis and Sporosarcina pasteurii to induce calcium carbonate precipitation, effectively sealing cracks. Artificial intelligence (AI) plays a crucial role in optimizing microbial growth conditions, predicting crack propagation, and ensuring efficient healing through advanced data analytics. This paper explores the integration of AI-driven models with microbial healing agents to create a smart, self-sustaining material. A comprehensive analysis of microbial selection, AI-driven optimization techniques, and sustainability assessments is provided. Results from recent experimental studies indicate that AI-optimized microbial self-healing concrete significantly enhances durability, reduces maintenance costs, and lowers carbon footprints compared to conventional materials. The findings emphasize the potential of AI and biotechnology in revolutionizing civil engineering, paving the way for greener and more resilient infrastructure.