Title: Artificial Intelligence in Construction: Enhancing Efficiency and Experiential Learning
Abstract: The presentation will focus on my experimentation with Computer Vision algorithms or Artificial Intelligence in general, which aim to assist construction personnel at various stages of construction. Specifically, I will present methods that enhance efficiency and speed during the 'preconstruction' stage by processing engineering drawings for automated 2D to 3D conversion, as well as Piping and Instrumentation drawings for equipment counting and BOQ preparation. For the 'operations' stage, I will discuss my investigation into the suitability of using Neural Radiance Fields to create lightweight and portable 3D scenes. Lastly, I will briefly touch on my exploratory research that leverages Large Language Models to assimilate information from various communication modes and channels among construction teams, allowing project teams and organizations to reflect upon their experiential learning and fill gaps in project execution.