Intelligent Environments Laboratory

CityLearn

Official reinforcement learning environment for demand response and load shaping

occupant_centric_grid_interactive_buildings_course

ProfileClustering

CityDNN

Surrogate model using deep neural networks that allows estimating the heating and cooling loads of buildings at the urban scale.

bevo_iaq

BEVO Beacon with more robust air quality monitoring

SBC_course

DOE_XStock

dashboard

Dashboard showcasing Covid-19 research by the Intelligent Environments Lab at UT Austin

airthings-waveplus-beacon

bleed-orange-measure-purple

Data and Analysis related to the Bleed Orange, Measure Purple low-cost sensor project on UT's campus

merlin-apen-2023

scafe

IEL_GettingStarted

Guides for various topics to get started with research at IEL

occupancy_BT

rlem-workshop.net

RLEM brings together researchers and industry practitioners for the advancement of (deep) reinforcement learning (RL) in the built environment as it is applied for managing energy in civil infrastructure systems (energy, water, transportation).

simbuild-2024-citylearn

utx000

Analysis related to the many studies under the UTx000 banner, a project under the Whole Communities, Whole Health initiative.

ALDI

bevo-pycom

Micropython implementation of OCC project with LoRaWAN and TTN integration

bevo_trh

All files, code, and documentation pertaining to a simplified bevo beacon that accurately measures temperature and relative humidity.

bevobeacon-RD

Repository for documentation related to research and development of the various versions of the BEVO Beacon

bleed-orange-measure-iaq

Data and analysis relateted to the Bleed Orange, Measure IAQ campaign at the University of Texas at Austin

Intro2EE4CAEE

osm_to_citysim

sustainable-dog-house-challenge

Information regarding the Sustainable Dog House Challenge at the University of Texas at Austin.

tcad

Download and parse Travis County Apprasal District export files