Smart Construction Project Management through UAV-Based Monitoring and Machine Learning-Driven Performance Optimization

Abstract

The construction industry is undergoing rapid digital transformation, driven by the need for accurate, real-time, and data-driven decision-making. This research presents an integrated Unmanned Aerial Vehicle (UAV)–based monitoring and Machine Learning (ML) framework designed to enhance the efficiency, safety, and sustainability of construction project management. The proposed framework systematically combines UAV-enabled data acquisition, photogrammetric mapping, and Building Information Modeling (BIM) integration with advanced ML analytics for predictive performance evaluation.

In stage one, the stage 3D reconstruction and high-resolution site mapping were carried out by the UAVs because the spatial data would be achieved at high resolution with the positional error of 2.5 cm on average and the monitoring time would be lessened by 63 percent relative to manual researches. The second action was to apply ML algorithms, which were Convolutional Neural Networks (CNN), Support Vector Machines (SVM), and Random Forests to the datasets acquired by UAVs and carried out anomaly detection, progress estimation, and delay forecasting. The most effective (94.5) was CNN, and the disparities in the conditions of the sites and compliance with safety were referred to.

The third step was the assessment of the integrated UAV-ML framework based on quantitative key performance indexes and qualitative feedbacks of the stakeholders. The outcome consisted of the fact that, the indicators of project performance had become visibly improved: Schedule Performance Index (SPI) rose by 16.9 percent, and cost variance by 72 percent and accuracy of defect detection by 31 percent. Moreover the number of safety incidents has been reduced by 56 per cent and CO2 emission during the inspections has been reduced by 65 per cent, this implies that this system has helped in ensuring sustainable and safe implementation of the projects.

In general, the developed scheme provides a potent platform of intelligent and live-time construction management, and proves that the UAVs with ML capabilities can change the paradigm of managing a project, and predict its management. The article will offer a practical and viable idea that will adhere to the provisions of the Industry 4.0, and will turn into the first stage in the creation of the fully digitalized and autonomous and performance-based construction sites.