The campus will remain closed until 12 noon Thursday, 02/13/25. Students should log into Canvas for specific class information from their instructors. Please contact event organizers for information on specific activities. Normal operations will resume at 12pm on Thursday.
Primary Graduate Student: Pedro DeLaCruz-Checo
Project Advisor: Deok-Oh Woo, PhD
The Building Automation Systems (BAS) can broadly maintain occupant comfort by governing indoor thermal, visual, and air quality conditions in accordance with existing criteria (e.g., ASHRAE, LEED, etc.). However, the criteria-met spaces do not necessarily guarantee occupant comfort. Human perception of the environment is governed not only by the physical and the physiological aspects but also by the psychological aspect of the environment, and all of which may be seen to contribute to creating an individual preference for comfort. Thus, universal learning algorithms are essential for BAS to deal with various comfort preferences of people from different cultural, climatic, and social backgrounds.
High initial and maintenance costs for Building Automation Systems (BAS) are other obstacles that keep BAS from being applied widely for retrofit. For the data acquisition system set-up, a number of different types of sensors need to be installed; these sensors must be replaced at every exchange cycle, otherwise, they may read inaccurate data. Besides, building managers and homeowners are required to be trained to implement BAS properly. Therefore, to leverage BAS for retrofit, it is essential to provide affordable technology that can be integrated without requiring in-depth knowledge in BAS.
To address these challenges, this research proposes a novel Universal Artificial Intelligence (AI)- based occupant comfort control framework. The proposed framework is a “Plug and Play” technology that does not require in-depth knowledge because the framework will learn and calibrate the user’s comfort preference automatically with a machine learning algorithm. Also, the framework offers an “All-in-One” data acquisition system by replacing all other sensors for universal infrared (IR) array sensors. The IR array sensor reads a grid of surface temperatures and these data are used to infer information such as the number of occupants in a room, their activity level, indoor surface temperatures, irradiation, and illuminance levels. Additionally, the control framework is able to adjust to changing conditions in the room. In this adaptive control, the system algorithms allow controllers to track changes that are normally described as the ‘changing parameters’ within the control system. The proposed framework will be able to control all devices that are influencing the thermal comfort level of the space. Thus, the modular framework is seen to be universal.
The most significant advantage of this system is that the implementation of the controllers is relatively affordable and straightforward. The IR array sensor is available in the market at a price range between $100-150 in combination with a microcontroller unit, making the proposed framework affordable than the conventional BAS.
Use Your Cell Phone as a Document Camera in Zoom
From Computer
Log in and start your Zoom session with participants
From Phone
To use your cell phone as a makeshift document camera
