Construction Progress Monitoring

Construction progress monitoring aims to efficiently and accurately track project development, ensuring timely completion and adherence to budget. Current research focuses on automating this process using computer vision techniques, including convolutional neural networks for object detection (e.g., helmet detection, building element identification) and large language models for automated report generation from multi-modal data collected by robots (e.g., drones, quadrupedal robots). These advancements offer significant potential for improving safety, reducing costs, and enhancing overall project management efficiency through real-time data acquisition and analysis, particularly in large-scale or remote construction projects.