Strategic Ai-Driven Innovation Management IN Nano-Engineered Construction Materials FOR Sustainable Smart City Infrastructure

Abstract

Artificial intelligence (AI) inclusion in innovation management is rebounding the design and implementation of nano-engineered construction materials flavoring on and to degrade sustainable smart cities. The paper establishes a new framework where stochastic nonlinear modeling of a system, AI-enabled decision-making and simulation techniques are integrated to address the innovation in next-generation materials like nano-silica reinforcement and nano-silica contains, as well as carbon nanotube-reinforced concrete. These materials have greater mechanical, thermal and environmental capabilities- ones which are essential to sustainable infrastructure. By utilising stochastic differential equations (SDEs) and bifurcation theory we evaluate how large fluctuations, the environmental noise and randomness of the microstructure impacts on long term material behaviour. The proposed framework assesses the performance prediction, performance optimization and lifecycle sustainability of nano-strengthened materials based on real-world data of infrastructure projects in climate-sensitive areas subjected to dynamics in the urban environment. The model is benchmarked by the case studies in Singapore, Dubai, and Helsinki. Our results indicate that the AI-empowered channels of innovation, which are regulated with nonlinear stochastic control processes, may enhance the sustainability, resilience, as well as adaptive capabilities of the urban construction systems to a very large extent. The study adds value to the interdisciplinary zone of AI, nanotechnology, and smart cities development and provides policymakers, urban planners, and material scientists with strategic plans. These results highlight the innovational power of integrating the AI with physical system uncertainties to streamline innovation made within the built environment.