Artificial Intelligence for Smart Infrastructure System: Integrating Civil and Electrical Engineering

Le résumé fourni par la source

The rapid convergence of Artificial Intelligence (AI) with civil and electrical engineering is transforming traditional infrastructure into intelligent, adaptive, and sustainable smart infrastructure systems. This study presents a comprehensive review of AI-driven integration frameworks that bridge the physical domain of civil engineering with the energy and communication networks of electrical engineering. It highlights the role of machine learning, deep learning, and reinforcement learning techniques in enabling predictive modeling, real-time monitoring, and autonomous decision-making across infrastructure lifecycles. Key applications discussed include structural health monitoring using data-driven models, computer vision-based damage detection, and time-series forecasting for infrastructure performance. The paper further explores the critical role of smart grids in modern energy systems, emphasizing AI-based load forecasting, fault detection, and self-healing capabilities. Emerging paradigms such as Vehicle-to-Grid (V2G) systems and microgrid integration are examined as essential components of future urban resilience. Digital Twin technology is identified as a cornerstone of smart infrastructure, enabling real-time synchronization between physical assets and virtual models for predictive maintenance, lifecycle optimization, and risk-informed design. Additionally, the integration of smart materials, including self-healing concrete, shape memory alloys, and piezoelectric systems, introduces a new layer of material intelligence that enhances infrastructure durability and efficiency. Despite significant advancements, challenges such as data interoperability, cybersecurity, energy demands of AI systems, and regulatory constraints remain critical barriers. The study underscores the importance of interdisciplinary collaboration, standardization frameworks, and sustainable design strategies to fully realize the potential of AI-enabled infrastructure. Ultimately, the integration of AI with civil and electrical engineering offers a transformative pathway toward resilient, efficient, and future-ready built environments.

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