| | --- |
| | pretty_name: TTM4HVAC – Training dataset (source-all) |
| | tags: |
| | - ttm4hvac |
| | - hvac |
| | - time-series |
| | - energy |
| | task_categories: |
| | - time-series-forecasting |
| | 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" |
| | license: mit |
| | --- |
| | |
| | # TTM4HVAC – Training dataset (source-all) |
| |
|
| | This dataset contains HVAC and weather time-series data used to train the **source-all** TinyTimeMixer model (`gft/ttm4hvac`), the main model of the TTM4HVAC project. |
| |
|
| | It aggregates all available source-building data under *default* and *non-default* conditions. |
| |
|
| | Check out the paper [arXiv:XXXX.XXXXX]() (to be released) and visit the main repository [ttm4hvac](https://huggingface.co/gft/ttm4hvac) for further details. |
| |
|
| | ## Columns |
| |
|
| | - `time` |
| | - `Outdoor Air Temperature (C)` |
| | - `Heating Setpoint (C)` |
| | - `Cooling Setpoint (C)` |
| | - `Room Air Temperature (C)` |
| | - `Outdoor Humidity (%)` |
| | - `Wind Speed (m/s)` |
| | - `Direct Solar Radiation (W/m^2)` |
| | - `HVAC Power Consumption (W)` |
| | - `series_id` |
| | - `is_default` |
| |
|
| | ## Usage |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | ds = load_dataset("gft/ttm4hvac-source-all-train") |
| | df = ds["train"].to_pandas() |
| | ``` |
| |
|
| | # ✒️ 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 |
| | ``` |
| |
|
