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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
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November 23, 2018, Filed Under: Research

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

A new IEA EBC Annex on occupant-centric design and controls has been approved. The Annex will involve about 100 experts from 20 countries for five years and focus on fundamental research issues regarding occupant comfort and behaviour, application to design and operations practice, new technology and tool development, and case studies. The project will be led by Liam O’Brien of Carleton University (Canada) and Prof. Andreas Wagner of Karlsruhe Institute for Technology (Germany).

IEL will have a major role in this annex as Prof Nagy will co-lead a subtask together with Prof. Burak Gunay (Carleton University, Canada) and Dr Daniel Wölki (RWTH Aachen, Germany).

This Annex would follow the highly successful IEA EBC Annex 66 (Definition and Simulation of Occupant Behavior in Buildings).

Follow the project on its website: http://annex79.iea-ebc.org

IEA EBC: International Energy Agency, Energy in Buildings and Communities Program

Research Highlight

Reinforcement Learning in the Built Environment

We develop reinforcement learning techniques for energy efficient operation of buildings and systems without the need for mathematical models. Despite 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 !

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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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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
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nagy@utexas.edu

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