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# HOT Dataset: HVAC Operations Transfer
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## Overview
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The **HOT (HVAC Operations Transfer)** dataset is the first large-scale open-source dataset purpose-built for transfer learning research in building control systems. Buildings account for approximately 10-15% of global energy consumption through HVAC systems, making intelligent control optimization critical for energy efficiency and climate change mitigation.
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### Key Statistics
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- **159,744** unique building-weather combinations
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---
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license: mit
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tags:
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- engineering
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- RL
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- HVAC
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size_categories:
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- 100K<n<1M
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---
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# HOT Dataset: HVAC Operations Transfer
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## Overview
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The **HOT (HVAC Operations Transfer)** dataset is the first large-scale open-source dataset purpose-built for transfer learning research in building control systems. Buildings account for approximately 10-15% of global energy consumption through HVAC systems, making intelligent control optimization critical for energy efficiency and climate change mitigation.
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Beyond technical advances, the field needs standardized evaluation protocols analogous to machine learning's model cards - comprehensive building data cards that systematically document building characteristics, performance baselines, and transfer learning suitability. Such standardisation would accelerate deployment decisions and enable practitioners to confidently assess transfer feasibility without extensive pilot studies. HOT establishes the foundation for this transformation.
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### Key Statistics
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- **159,744** unique building-weather combinations
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