Smart Infrastructure Systems: Integrating AI, Building Information Modeling, and Sustainable Materials for Enhanced Construction Safety

Abstract

The swift evolution of the infrastructure development has made the demand for construction systems that are able to predictively respond to safety issues and enhance environmental and operational performance even greater. Traditional safety management methods are still very reactive and mostly rely on manual checks, past history, and reactive measures to deal with hazardous situations. Smart infrastructure systems provide an integrated approach with the use of Artificial Intelligence (AI), Building Information Modeling (BIM), Internet of Things (IoT) technologies, sustainable materials, digital twins, robotics and automation throughout the infrastructure lifecycle. The review compares and contrasts the technologies and their potential to bolster construction safety by providing continuous monitoring, predictive risk assessment, better design coordination, and automated intervention. With AI, the patterns of accidents, unsafe behaviors, equipment failures, and structural anomalies can be identified, whereas computer vision can automatically detect violations of personal protective equipment, falls, entry into restricted areas, and unsafe proximity. BIM supports the safety focused design, construction sequencing, spatial coordination, and lifecycle information management. Digital twins link dynamic digital representations of physical infrastructure to real time data from IoT devices and environmental sensors, which relay worker movement, equipment condition and hazardous exposure data. Sustainable materials can also play a role in safety, impacting structural performance, material handling, durability and construction practices. The review points out that an integrated smart infrastructure system can transform construction safety from being a reactive process of control to being a predictive process of continuous and lifecycle risk management.