Datasets:

gft
/

ttm4hvac-target-cool-test

pretty_name: TTM4HVAC – Evaluation dataset (target-cool-test)
tags:
  - ttm4hvac
  - hvac
  - time-series
  - energy
task_categories:
  - time-series-forecasting
license: mit
papers:
  - title: >-
      Transfer learning of building dynamics digital twin for HVAC control with
      Time-series Foundation Model
    url: https://arxiv.org/abs/XXXX.XXXXX
    authors: Ferran Aran Domingo

TTM4HVAC – Evaluation dataset (target-cool-test)

This dataset contains target-building time-series data under cooling-dominated operating conditions (July).

It is intended for evaluation / benchmarking of TTM4HVAC models on a cooling-focused scenario.

Check out the paper arXiv:XXXX.XXXXX (to be released) and visit the main repository ttm4hvac for further details.

Columns

time
Room Air Temperature (C)
Outdoor Air Temperature (C)
Outdoor Humidity (%)
Direct Solar Radiation (W/m^2)
Wind Speed (m/s)
Cooling Setpoint (C)
Heating Setpoint (C)
HVAC Power Consumption (W)

Usage

from datasets import load_dataset

ds = load_dataset("gft/ttm4hvac-target-heat-test")
df = ds["test"].to_pandas()
df.head()

✒️ Citation

If you use this model or datasets, please cite:

**F. Aran**,  
*Transfer learning of building dynamics digital twin for HVAC control with Time-series Foundation Model*,  
arXiv:XXXX.XXXXX, 2025.  
https://arxiv.org/abs/XXXX.XXXXX