From Sky to Strategy: Construction Activity Index and Stage Estimation From Drone-Captured Imagery

Advait Gupta, Manan Padsala, Aastha Shayla, Tanmay Bisen, Susham Biswas, Abhemanyu Sarin

Abstract: In the rapidly evolving construction industry, timely and accurate monitoring of construction activities is paramount. This paper introduces a novel approach to quantifying construction activity using high-resolution drone imagery and advanced object detection models. We present a unique, high-quality dataset of construction site images captured from drones, which is distinct from the commonly used open-source or lower-quality datasets. Leveraging this dataset, we fine-tuned pre-trained object detection models to achieve remarkable accuracy in detecting construction materials from images. Building on this, we introduce the Composite Construction Activity Index (CAI), a metric formulated by combining the Material Diversity Ratio (MDR) and the Percentage of Image Covered by Construction Materials (PIC). This metric offers a comprehensive view of construction activity, capturing both its diversity and intensity. Additionally, we propose a methodology to map construction stages based on the detected materials, categorizing them into distinct phases of construction, providing insights into the project's lifecycle. The paper culminates in the visualization of CAI values through heatmaps, offering a spatial representation of construction activity across cities or countries. Our findings and methodologies pave the way for more informed decision-making by stakeholders, from urban planners to construction managers, emphasizing the potential of drone technology and machine learning in revolutionizing construction monitoring.