The Role of Artificial Intelligence and Digital Transformation in Smart and Sustainable Infrastructure Systems

Abstract

Artificial Intelligence (AI) and digitalization are rapidly transforming the planning, operation, maintenance and management of critical infrastructure. Planning, operation, maintenance and management of critical infrastructure is changing with Artificial Intelligence (AI) and digitalization. The review covers energy, transportation, water, building, and urban infrastructure sectors, focusing on predictive maintenance and forecasting, anomaly detection, adaptive control, digital twins, asset management, and resilience planning, highlighting the potential and limitations of AI and machine learning (ML) applications in these fields. AI's forecasting capabilities help with load balancing in electricity systems and the integration of renewable energy, while intelligent transportation systems enhance traffic management, safety, and infrastructure condition monitoring. AI is being used in water systems for leak detection, water quality monitoring, and drought forecasting, while in building applications, it's used for energy optimization, predictive control, and equipment fault detection. The review also explores cross cutting data quality, sensor reliability, interoperability, cybersecurity, human oversight, governance, ethics and regulatory compliance requirements. Although significant technology advancement has been realized, implementation is limited by existing legacy infrastructure, disparate data systems, limited technical capacity, funding and procurement barriers, cybersecurity, and demos from research and into large scale operating deployment. Special emphasis is placed on the concept of explainable AI, human in the loop decision making, risk based asset prioritization and ongoing model validation as ways to provide public accountability and reliability. Future directions are: climate adaptive infrastructure management, digital twins, edge computing, advanced remote sensing, continual and federated learning, dynamic network modeling, and hybrid human AI decision systems.