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Intelligent Environments Laboratory

The University of Texas at Austin
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    • Prof. Zoltan Nagy, PhD
    • June Young Park
    • José Ramón Vázquez-Canteli
    • Megan K. McHugh, MSE
    • Ayşegül Demir Dilsiz
    • Hagen Fritz
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November 23, 2018, Filed Under: Past Projects I

Occupant Centered Lighting Control

The energy savings of buildings promised by automatic control systems are often ineffective due to occupants who may not use the features of the system to the full potential at best, or deactivate the system at worst. Therefore, systems that adapt to the occupant over time without compromising his/her comfort are needed.

final_control_para

Publications

Z. Nagy, F.Y. Yong, and A. Schlueter, Occupant Centered Lighting Control: A user study on comfort, acceptance, and energy consumption, Under Review

Z. Nagy, F.Y. Yong, M. Frei, and A. Schlueter, Occupant Centered Lighting Control for Comfort and Energy Efficient Building Operation, Energy & Buildings, Vol. 94, pp. 100-108, May 2015
doi: 10.1016/j.enbuild.2015.02.053

Z. Nagy, F.Y. Yong, and A. Schlueter, What should a building be controlled for? Ask the occupants!, in Proc. Sustainable Built Environment (SBE), Zurich, 2016

Z. Nagy, M. Hazas, M. Frei, D. Rossi, and A. Schlueter, Illuminating Adaptive Comfort: Dynamic Lighting for the Active Occupant, in Proc. 8th Windsor Conference: Counting the Cost of Comfort in a Changing World, April 2014, London, UK

 

Research Highlight

UT Energy App – Privacy Policy

  The Intelligent Environments Laboratory is releasing the first version of the UT Energy App. This app is intended to provide a way to Read more 

About Us

The Intelligent Environments Laboratory (IEL), led by Prof. Zoltán Nagy, is an interdisciplinary research group within the Building Energy & Environments (BEE) and Sustainable Systems (SuS) Programs of the Department of Civil, Architectural and Environmental Engineering (CAEE) in the Cockrell School of Engineering of the University of Texas at Austin.

The aim of our research is to rethink the built environment and define Smart Buildings and Cities as spaces that adapt to their occupants and reduce their energy consumption.

We combine data science with building science and apply machine learning to the building and urban scale

Take a look at our projects !

Tags

air handling unit Annex 79 architecture artificial neural network Bluetooth city learn Community engaged research earthquakes environmental monitoring fault detection and diagnostics HVAC integrated design intelligent energy management Lighting Control machine learning Megan McHugh multi-agent systems Occupancy Occupant Centered Control Reinforcement Learning Review Smart Building smart city teaching Thermal Comfort
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Research

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UT Energy App – Privacy Policy

Fault detection and diagnostics of air handling units using machine learning and expert rule-sets

Reinforcement Learning in the Built Environment

Reinforcement learning for urban energy systems & demand response

Multi-Agent Reinforcement Learning for demand response & building coordination

IEA-EBC Annex 79: Occupant Centric Design and Operation of Buildings

People

  • Prof. Zoltan Nagy, PhD
  • June Young Park
  • José Ramón Vázquez-Canteli
  • Megan K. McHugh, MSE

Tags

air handling unit Annex 79 architecture artificial neural network Bluetooth city learn Community engaged research earthquakes environmental monitoring fault detection and diagnostics HVAC integrated design intelligent energy management Lighting Control machine learning Megan McHugh multi-agent systems Occupancy Occupant Centered Control Reinforcement Learning Review Smart Building smart city teaching Thermal Comfort
ITS

301 E Dean Keeton St
Austin, TX 78712
512-555-5555
nagy@utexas.edu

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