There is only one boss. The customer. And he can fire everybody in the company from the chairman on down, simply by spending his money somewhere else.
—— Sam Walton
Project 1: A human-centered approach to smart housing
In this project, the research team focused on developing a human-centered approach to smart housing. We undertook a multi-phase mixed-methods study, collecting data from high-performance housing units in the United States. This included energy usage data, occupant surveys, and semi-structured interviews. Using affinity diagramming, they categorized qualitative data and developed user personas for smart housing. These personas, based on data-driven insights, aimed to communicate the needs of smart housing users effectively, helping to guide the design of human-centered buildings and infrastructure.
Project Team: Dr. Philip R. Agee, Dr. Ray Gao, Dr. Frederick Paige, Dr. Andrew P. McCoy, and Dr. Brian Kleiner.
Project 2: Towards automated occupant profile creation in smart buildings
In this project, the research team developed a machine learning-based approach for automatically creating occupant profiles in smart buildings. We used the 2015 Residential Energy Consumption Dataset, applying six machine learning techniques to classify and predict 16 occupant characteristics, such as age, education, and thermal comfort. The models achieved moderate to high accuracy, demonstrating the feasibility of using machine learning for automating the development of building occupant personas, thus minimizing manual effort in the process.
Project Team: Sheik Anik, Dr. Ray Gao, and Dr. Na Meng.
Ray Gao's Cabinet of Curiosities 