AI Reality Capture: Automated Detection of Safety, Risk, and Non-Compliance Observations in Construction Management.
Construction management is becoming increasingly data-driven, with reality capture technologies such as drones, 360-degree cameras, and IoT devices playing a critical role in monitoring site conditions. However, interpreting this data to identify safety hazards, risks, and compliance issues remains a manual, time-intensive process, prone to errors and inefficiencies. This directed research project explores how Artificial Intelligence (AI) and Machine Learning (ML) can enhance reality capture by automating the detection of observations requiring attention. The focus is on developing an AI-driven framework that identifies risks, safety hazards, and non-compliance issues in real-time, using object recognition and anomaly detection techniques. By automating these processes, the project aims to streamline construction workflows, reduce accidents, and ensure adherence to safety and quality standards.
This research will push the boundaries of AI-driven progress detection and real-time data processing, ultimately contributing to safer, more efficient, and compliant construction practices.
