Team Members:
Katie Frey – Master’s student in Architectural Engineering
Solana Honda – Master’s student in Architectural Engineering
Advisor: Dr. Josephine Lau
School: University of Nebraska–Lincoln
Challenge: Taking Comfort to the Extreme
The objective of this challenge is to improve occupant indoor thermal comfort in buildings in the United States located in extreme climates or locations prone to extreme weather events by focusing on the environmental factors that determine individual satisfaction within indoor atmospheres.
Project Title: Using Occupancy Surveys and Real-Time AI Responses to Improve the Thermal Comfort for Building Occupants
Solution: The condition of an indoor space has a big impact on a person’s day-to-day life. This is especially true during the workday. If a person is not comfortable in their workspace, it can negatively affect their productivity. This means that maximizing productivity of workers is an important cost saving metric for business owners. Indoor environments are designed and conditioned based on a set of industry best practices. However, these practices do not properly represent the current workforce. As climate change continues to increase the severity and frequency of extreme weather events, thermal comfort complaints will continue to rise, and the inequity in thermal comfort standards will become more detrimental. Women who work in office buildings in places with extreme heat such as Texas need a solution that incorporates their personal needs and preferences into the HVAC temperature controls. To bridge the gap between outdated standards and current users, a real-time occupant survey could be integrated with the heating, ventilation, and air conditioning (HVAC) controls system to regulate the temperature of the space. A company could deploy a simple software that polls building occupants on their current state of thermal comfort. The results of this survey could be fed back, in real-time, to artificial intelligence (AI) that resets the building management system (BMS) to match the average occupant’s preferences. AI can proactively optimize the building setpoint. This will create a more equitable workplace for all, ensuring more occupants are satisfied with the thermal comfort.