The DALPIM explores various types of data in the construction industry. The lab seeks data-driven solutions for better decision making throughout the project life cycle. The construction industry is behind the other industry sectors in taking advantage of ever growing data created from multiple sources at the departmental, organizational, and industry levels for intelligent business decisions. Statistics, simulation, artificial intelligence techniques, data mining, big data analytics, informatics are some of the representative methodologies used by the lab researchers. Some specific applications include a) Big data analytics for construction field data, b) infrastructure asset management – asset deterioration pattern prediction, and c) construction cost index prediction.
Digital Project Delivery: The adoption of various advanced computerized technologies such as 3D modeling, LiDAR, Geographic Information System (GIS), E-Construction, and automated machine guidance (AMG) is making a transformative change in how project information is produced, exchanged, and managed throughout the life cycle of a transportation project from an analog to a digital data based system. The significant improvement of data and information sharing between project participants and across various project development stages is possible with a model based project delivery process, and electronic and digital data transfer systems, which will, in turn, translate into increased productivity, efficiency in project delivery, accountability of decisions. However, in current practices, digital data and information of construction projects and assets are being used and managed independently in proprietary formats by separate project participants. We are passionate about developing new theories, processes and implementable tools to accelerate the industry’s transition to digital data based project delivery.
