Towards cybernetic buildings: integrated intelligent sensing to create responsive environments
Lead PI:
Junsong Yuan
Co-Pi:
Abstract

The essential building blocks of a community are buildings. Like the larger community, buildings have to accommodate all the needs of a diverse group of people. Some "smart" systems are employed in the built environment, but they are designed to facilitate operations and improve efficiency. Do these systems benefit the inhabitants of the whole community, especially marginalized groups who often do not have a say in shaping policy and practices related to building management? In a democratic society, connected communities must be safe, comfortable, healthy, easy to use, and support productivity, contributing to the advancement of a just society for all. To meet these needs, a truly smart system should be cybernetic: it can incorporate feedback for self-regulation toward desirable goals. This research will develop and test an integrated platform to collect feedback on building performance, communicate that information to all building users, and create an online community through which members can influence the operation of building services and facilities. A proactive intelligent, or cybernetic system that engages the community of building users will provide the data to evaluate connected community strategies from a social perspective.

The system will leverage smart phones and commercial augmented reality equipment to develop an inexpensive system of feedback and control that could be implemented in any building. It will include a sensor array for innovative building performance measurement, a set of dashboards for communicating and controlling the status of systems, and automated participatory processes that assess and communicate outcomes like satisfaction, comfort, and social engagement to facilities managers. The system will combine technologies from sensing, artificial intelligence, psychophysical research and social media. Implementing such systems on a large scale will provide data to create benchmarks for performance, identify unknown health threats, and understand the design features that contribute to productivity, satisfaction and community building. Once a working system has been implemented successfully for buildings, it can be scaled up for community wide use.

Junsong Yuan
Dr. Junsong Yuan is Professor and Director of Visual Computing Lab at Department of Computer Science and Engineering (CSE), State University of New York at Buffalo, USA. Before joining SUNY Buffalo, he was Associate Professor (2015-2018) and Nanyang Assistant Professor (2009-2015) at Nanyang Technological University (NTU), Singapore. He obtained his Ph.D. from Northwestern University in 2009, M.Eng. from National University of Singapore in 2005, and B.Eng. from Huazhong University of Science Technology (HUST) in 2002. He received Chancellor's Award for Excellence in Scholarship and Creative Activities from SUNY, Nanyang Assistant Professorship from NTU, Outstanding EECS Ph.D. Thesis award from Northwestern University, and Best Paper Award from IEEE Trans. on Multimedia. He serves as Senior Area Editor of Journal of Visual Communication and Image Representation (JVCI), Associate Editor of IEEE Trans. on Pattern Analysis and Machine Intelligence (T-PAMI), IEEE Trans. on Image Processing (T-IP), IEEE Trans. on Circuits and Systems for Video Technology (T-CSVT), and Machine Vision and Applications (MVA). He also serves as General/Program Co-chair of ICME and Area Chair for CVPR, ICCV, ECCV, ACM MM, etc. He was elected Faculty Senator at Both SUNY Buffalo and NTU. He is a Fellow of IEEE and IAPR.
Performance Period: 10/01/2020 - 09/30/2022
Institution: SUNY at Buffalo
Award Number: 1951952