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--- |
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pretty_name: TTM4HVAC – Training dataset (source-default) |
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tags: |
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- ttm4hvac |
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- hvac |
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- time-series |
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- energy |
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task_categories: |
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- time-series-forecasting |
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license: mit |
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papers: |
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- title: "Transfer learning of building dynamics digital twin for HVAC control with Time-series Foundation Model" |
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url: https://arxiv.org/abs/XXXX.XXXXX |
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authors: "Ferran Aran Domingo" |
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--- |
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# TTM4HVAC – Training dataset (source-default) |
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This dataset contains HVAC and weather time-series data collected under **default building control schedules** for the source domain. |
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It is used to train the `gft/ttm4hvac-source-default` model. |
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Check out the paper [arXiv:XXXX.XXXXX]() (to be released) and visit the main repository [ttm4hvac](https://huggingface.co/gft/ttm4hvac) for further details. |
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## Columns |
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- `time` |
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- `Outdoor Air Temperature (C)` |
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- `Heating Setpoint (C)` |
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- `Cooling Setpoint (C)` |
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- `Room Air Temperature (C)` |
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- `Outdoor Humidity (%)` |
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- `Wind Speed (m/s)` |
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- `Direct Solar Radiation (W/m^2)` |
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- `HVAC Power Consumption (W)` |
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- `series_id` |
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- `is_default` |
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## Usage |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("gft/ttm4hvac-source-default-train") |
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df = ds["train"].to_pandas() |
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df.head() |
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``` |
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# ✒️ Citation |
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If you use this model or datasets, please cite: |
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``` |
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**F. Aran**, |
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*Transfer learning of building dynamics digital twin for HVAC control with Time-series Foundation Model*, |
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arXiv:XXXX.XXXXX, 2025. |
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https://arxiv.org/abs/XXXX.XXXXX |
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``` |
