NSF: Future of Work

Ming Tang worked as a co-investigator on the project funded by the NSF Grant. 

Future of Work: Understanding the interrelationships between humans and technology to improve the quality of work-life in smart buildings.

Grant: #SES-2026594 PI:  David W. Wendell. co-PIs: Harfmann, Anton; Fry, Michael; Rebola, Claudia; co-Is: Pravin Bhiwapurkar, Ann Black, Annulla Linders, Tamara Lorenz, Nabil Nassif, John Seibert, Ming Tang, Nicholas Williams, and Danny T.Y. Wu.  01-01-2021 -12-31-2021 National Science Foundation $149,720. Awarded Level: Federal 


The primary goal of this proposed planning project is to assemble a diverse, multidisciplinary team of experts dedicated to devising a robust methodology for the collection, analysis, and correlation of existing discipline-specific studies and data. This endeavor focuses on buildings and their occupants, aiming to unearth previously undiscovered interactions. Our research will specifically delve into the intricate interrelationships between four key areas: 1) the overall performance of buildings, 2) the indoor and outdoor environmental conditions, 3) the physical health of the occupants, and 4) their satisfaction with the work environment. This comprehensive approach is designed to provide a holistic understanding of the dynamic between buildings and the well-being of the individuals within them.


Prof. Anton Harfmann developed the sensor towers.


Ming Tang spearheaded the development of a Digital Twin model, an innovative project integrating multiple historical sensor data sets into a comprehensive, interactive 3D model. This model encompasses several vital features: the capture, analysis, and visualization of historical data; cloud-based data distribution; seamless integration with Building Information Models (BIM); and an intuitive Web User Experience (UX). Building elements are extracted as metadata from the BIM model and then overlaid in screen-based and Virtual Reality (VR) interfaces, offering a multi-dimensional data view. Further details are available at the Cloud-based Digital Twin project for a more in-depth exploration of this work.


See more details on the Digital Twin workflow.