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  • Title: Preparing the Future Workforce of Architecture, Engineering, and Construction for Robotic Automation Processes
  • Principal Investigator: Shahin Vassigh
  • Funding Amount: $1,000,000
  • Funding Source: National Science Foundation
  • Timeline: 09/01/19–05/31/21

The broader impacts of this project address a crucial national problem by preparing the nation's workers and businesses in the Architecture, Engineering, and Construction (AEC) industries for an increasingly automated future workplace. This convergent research and development project involves researchers in architecture, construction, engineering, computer science, STEM education and economic development, as well as industry collaborators from the robotics, architecture, engineering, construction and software industries.

Project deliverables will benefit businesses, workers and professionals in the AEC industry cluster, as well as regional and national economic development policy. The project provides the platform for critical solutions: maximizing employment opportunity, minimizing job displacement, and improving national economic competitiveness in the AEC industries. Improving AEC industry performance also promises solutions leading to a more energy efficient and sustainable built environment. This project will contribute to research and application of Artificial Intelligence (AI) and immersive virtual environments in education as well as examining economic impacts of automation technology adoption in the AEC industries. The rapid adoption of AI and automation promises new employment and business opportunities, but will also create job displacement and business disruption.

The project's research objectives are to develop 1) a prototype interactive virtual reality robotics training and educational software package, and 2) a new model to measure the economic impact of automation adoption. The goal is to provide a platform for an immersive virtual software to teach new skills, improve process workflows, and increase efficiency in the AEC industries. Integrating advanced technologies including Reinforcement Learning, Computer Vision, Augmented and Virtual Reality, the project will advance methods of remote and on-site training for a large segment of employees in the AEC industries. By applying STEM learning strategies, the project will contribute to understanding how people learn in technology rich environments and bridge the gap between technology advancement and application to practice. The project's economic analysis will utilize a "bottom-up" approach to estimating the employment impacts resulting from the adoption of AI and robotics.

Read more about this project in this FIU News article about the Convergence Accelerator program.

Publications

  • 2020

    Tao, Y., Coltey, E., Wang, T., Alonso, M., Shyu, M.-L., Chen, S.-C., Alhaffar, H., Elias, A., Bogosian, B., & Vassigh, S. (2020). Confidence Estimation Using Machine Learning in Immersive Learning Environments. 2020 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), 0. https://doi.org/10.1109/mipr49039.2020.00058 

    Bogosian, B., Bobadilla, L., Alonso, M., Elias, A., Perez, G., Alhaffar, H., & Vassigh, S. (2020). Work in Progress: Towards an Immersive Robotics Training for the Future of Architecture, Engineering, and Construction Workforce. 2020 IEEE World Conference on Engineering Education (EDUNINE), 0. https://doi.org/10.1109/edunine48860.2020.9149493

  • 2019

    Lin, C.-X., Pradhananga, N., & Vassigh, S. (2019). An Evaluation of the Effects of Team Projects and Augmented Reality on Student Learning in Sustainable Building Science. Volume 8: Heat Transfer and Thermal Engineering, 1–7. https://doi.org/10.1115/imece2019-11982

  • 2018

    Vassigh, S., Davis, D., Behzadan, A. H., Mostafavi, A., Rashid, K., Alhaffar, H., Elias, A., & Gallardo, G. (2018). Teaching Building Sciences in Immersive Environments: A Prototype Design, Implementation, and Assessment. International Journal of Construction Education and Research, 16(3), 180–196. https://doi.org/10.1080/15578771.2018.1525445