A framework for active construction inspection and visualization using uas

The highway infrastructure management sector has limited implementations of digital data collection and analysis procedures that can be utilized for Active Construction Inspection. The objective of this research is to provide UAS-based progress monitoring and quality inspection processes that can be integrated with the State DOTs’ construction inspection procedures and guidelines and visualize the construction information and create as-built Building Information Model (BIM) of the project. The proposed outcome of this research is a foundational framework for project managers to facilitate project progress monitoring and quality control during highway construction. The framework includes a methodology that collects construction data using UAS in main formats of RJPG, Geo-TIFFs, and 3D surface Digital Elevation Models (DEMs), and processes them to extract geometry/temperature parameters using Computer Vision. The geometry parameters are mapped on to a pavement BIM to create a as-built model of the project and estimate the project progress. The temperature parameters are also incorporated in the quality control guidelines of the project to estimate the potential segregated spots on the asphalt pavement. The main contribution of this research is the organization, and integration of UAS data to capture project management workflow information and reflect the final as-built BIM. The research outcomes pave the way for construction project managers and inspectors to track and identify potential performance/quality problems during construction and record them to support future decision-making.