News & Features

Zoltan Nagy – Teaching Lights to Think

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Nov. 6, 2018

A research team in the Department of Civil, Architectural and Environmental Engineering led by Assistant Professor Zoltan Nagy has an ambitious goal: save energy by teaching lights to think. The results of their design and experiment, LightLearn, were recently published in the Building and Environment journal.

Since lighting consumes nearly 20% of a typical electricity budget in buildings, Nagy and his team sought to increase energy savings by designing a lighting system that centers on the comfort level of a room’s occupant. LightLearn is a programmable system that uses reinforced learning to adapt to lighting preferences for each room’s occupant.

“It is important to focus on the occupant because ultimately we build buildings for people,” says Zoltan Nagy, an assistant professor in CAEE. “Our goal is to provide a comfortable environment while eliminating energy waste.”

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The team tested LightLearn in five offices in the Ernest Cockrell Jr. Hall on campus. The offices had different amounts of natural light, and occupants had varied comfort levels for lighting. The team found that their system reduced the amount of time that lights were on when compared to traditional motion sensors, with significant savings in electricity cost. LightLearn was also favorably rated by the occupants.

Historically, sensors have been used to reduce the amount of the energy waste when lights are left on longer than needed by a room’s occupant. While motion sensor technology does save a lot of energy, the system has room for improvement.

Two areas the research team seeks to improve are the programmed time delay before lights are switched off lights and the unexpected cutting of lighting if a room’s occupant is particularly motionless.

Electricity is also wasted if lights turn on while there is enough daylight. While technology such as luminosity sensors can help minimize energy waste from this issue, they don’t account for individual preference in natural versus artificial light.

“We are working to develop an intelligent system that understands the unique situation of an occupant and room environment and then decides the optimal action for both occupant comfort and energy savings,” says doctoral student June Young Park. “Our research shows that you can save about 21% more energy without sacrificing occupant comfort by developing a controller that adapts to each room’s conditions.”

In addition to Park and Nagy, two UT Austin undergraduates, and Hagen Fritz (Civil Engineering) and Thomas Dougherty (Mechanical Engineering) worked on this research. Funding for this project was partially provided by Green Fund, a competitive grant program funded by UT Austin tuition fees to support sustainability-related projects and initiatives proposed by university students, faculty or staff.