Update README.md

README.md

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-license: mit
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+# HOT Dataset: HVAC Operations Transfer
+
+
+## Overview
+
+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.
+
+### Key Statistics
+- **159,744** unique building-weather combinations
+- **15,808** building models with controllable zone-level setpoints
+- **19** ASHRAE climate zones across **76** global locations
+- **16** commercial building types (office, retail, school, hospital, etc.)
+- **12** systematic occupancy patterns
+- **3** thermal performance scenarios
+- **15-minute** timestep resolution for control applications
+
+## Dataset Description
+
+HOT addresses the critical infrastructure gap in building control transfer learning by providing systematic variations across four key context dimensions:
+
+### 🏢 **Building Geometry** (16 Types)
+- **Office**: Small (511 m²), Medium (4,983 m²), Large (46,323 m²)
+- **Retail**: Standalone (2,294 m²), Strip Mall (2,294 m²)
+- **Educational**: Primary School (6,874 m²), Secondary School (19,592 m²)
+- **Healthcare**: Hospital (22,443 m²), Outpatient (3,805 m²)
+- **Hospitality**: Small Hotel (3,726 m²), Large Hotel (11,349 m²)
+- **Residential**: Midrise Apartment (2,825 m²), Highrise Apartment (7,063 m²)
+- **Food Service**: Sit-down Restaurant (511 m²), Fast Food (232 m²)
+- **Industrial**: Warehouse (4,835 m²)
+
+### 🌡️ **Thermal Performance** (3 Scenarios)
+- **Default**: Baseline thermal properties (R_mult = 1.0)
+- **High Performance**: Enhanced insulation (R_mult = 2.0, U_mult = 0.5)
+- **Low Performance**: Minimal insulation (R_mult = 0.5, U_mult = 2.0)
+
+### 🌍 **Climate Conditions** (76 Locations)
+- **Complete ASHRAE coverage**: All 19 climate zones (0A through 8)
+- **Global diversity**: From tropical (Ho Chi Minh) to subarctic (Fairbanks)
+- **Weather data types**: TMY (Typical Meteorological Year) + Real historical (2014-2024)
+- **Temperature range**: -44.4°C to 47.0°C
+- **HDD range**: 0 to 7,673 heating degree days
+- **CDD range**: 6 to 4,301 cooling degree days
+
+### 👥 **Occupancy Patterns** (12 Schedules)
+- **Standard**: Traditional office hours (8 AM - 5 PM weekdays)
+- **Low/High Occupancy**: 50%/150% intensity variations
+- **Shift Operations**: Early (6 AM-3 PM), Late (2 PM-11 PM)
+- **Sector-Specific**: Retail (10 AM-9 PM), School (7 AM-4 PM + evening)
+- **Healthcare**: Hospital 24/7 with shift patterns
+- **Modern Work**: Flexible hybrid with staggered hours
+- **Specialized**: Gym (morning/evening peaks), Warehouse logistics
+- **Continuous**: 24/7 operations
+
+## Dataset Structure
+
+```
+data/
+├── buildings/                          # Building model files (.epJSON)
+│   ├── base/                          # Original DOE reference buildings
+│   ├── variations/
+│   │   ├── occupancy/                 # Occupancy schedule variations
+│   │   ├── thermal/                   # Thermal performance variations
+│   │   └── combined/                  # Multi-variable combinations
+├── weather/                           # Weather data files (.epw)
+│   ├── tmy/                          # Typical Meteorological Year files
+│   └── real/                         # Historical weather (2014-2024)
+├── tables/                           # Metadata and combination tables
+│   ├── buildings.csv                 # Building characteristics
+│   ├── weather.csv                   # Weather file metadata
+│   └── combinations.csv              # Building-weather pairings
+└── tools/                            # Processing and analysis scripts
+    ├── preprocessing/
+    ├── variations/
+    └── analysis/
+```
+
+## Key Features
+
+### 🎮 **Reinforcement Learning Ready**
+- **Controllable setpoints**: Zone-level heating/cooling temperature control
+- **Gymnasium interface**: Standard RL environment wrapper
+- **Comprehensive state space**: Zone temperatures, outdoor conditions, energy consumption
+- **Multi-objective rewards**: Energy efficiency + thermal comfort + control stability
+- **EnergyPlus integration**: Physics-based building simulation
+
+### 🔬 **Transfer Learning Framework**
+- **Similarity metrics**: Quantitative compatibility assessment across 4 dimensions
+- **Zero-shot evaluation**: Direct policy transfer without retraining
+- **Systematic variations**: Single and multi-variable transfer scenarios
+- **Benchmark protocols**: Standardized evaluation methodology
+
+### 🌐 **Global Climate Coverage**
+- **All inhabited regions**: Complete ASHRAE climate zone representation
+- **Real vs. synthetic**: TMY baseline + historical weather variability
+- **Extreme conditions**: From subarctic (-44°C) to desert (+47°C)
+- **Transfer analysis**: Climate adaptation and geographic deployment
+
+### 📊 **Research Infrastructure**
+- **Standardized formats**: Consistent EnergyPlus epJSON structure
+- **Processing pipeline**: Automated building modification tools
+- **Validation tools**: Building model verification and testing
+- **Similarity analysis**: Transfer feasibility assessment toolkit
+
+## Research Applications
+
+### 🤖 **Reinforcement Learning**
+- **Multi-agent control**: Coordinate multiple HVAC zones
+- **Meta-learning**: Fast adaptation to new buildings (MAML, Reptile)
+- **Foundation models**: Pre-train on diverse building types
+- **Safe RL**: Constraint-aware control with comfort guarantees
+
+### 🔄 **Transfer Learning**
+- **Domain adaptation**: Geographic and climate transfer
+- **Few-shot learning**: Minimal data adaptation for new buildings
+- **Cross-building generalization**: Policy transfer across archetypes
+- **Similarity-guided selection**: Optimal source building identification
+
+### 📈 **Building Analytics**
+- **Energy benchmarking**: Performance comparison across climates
+- **Occupancy analysis**: Usage pattern impact on energy consumption
+- **Envelope optimization**: Thermal performance sensitivity analysis
+- **Climate resilience**: Building adaptation to changing conditions
+
+## Dataset Statistics
+
+| **Dimension** | **Count** | **Range** | **Examples** |
+|---------------|-----------|-----------|--------------|
+| Building Types | 16 | 232-46,323 m² | Office, Hospital, School |
+| Climate Zones | 19 | -44°C to +47°C | 0A (Tropical) to 8 (Subarctic) |
+| Occupancy Schedules | 12 | 53-168 hrs/week | Office, Retail, Hospital, 24/7 |
+| Thermal Scenarios | 3 | 0.5-2.0× resistance | High/Default/Low performance |
+| Weather Files | 192 | TMY + Real (2014-2024) | Geographic + temporal variation |
+
+## File Formats
+
+### Building Models (`.epJSON`)
+- **Format**: EnergyPlus JSON input files
+- **Features**: Zone-level controllable setpoints, comprehensive meters
+- **Compatibility**: EnergyPlus 24.1+
+- **Size**: ~50-500 KB per building
+
+### Weather Files (`.epw`)
+- **Format**: EnergyPlus Weather format
+- **Frequency**: Hourly meteorological data
+- **Variables**: Temperature, humidity, solar, wind
+- **Size**: ~1-2 MB per location-year
+
+### Metadata Tables (`.csv`)
+- **Buildings**: Physical characteristics, variations, file paths
+- **Weather**: Climate statistics, location data, file paths
+- **Combinations**: Valid building-weather pairings (159,744 total)
+
+## Benchmarks and Baselines
+
+### Control Algorithms
+- **Static Baseline**: Seasonal ASHRAE setpoint schedules
+- **PPO**: Proximal Policy Optimization with building-specific tuning
+
+### Transfer Learning Methods
+- **Zero-shot**: Direct policy application without retraining
+- **Fine-tuning**: Limited adaptation with target building data
+- **Meta-learning**: MAML and Reptile for fast adaptation
+
+### Evaluation Metrics
+- **Transfer Performance Ratio**: Transferred vs. target-trained performance
+- **Energy Efficiency**: HVAC consumption reduction vs. baseline
+- **Comfort Violations**: Hours outside desired temperature range
+- **Training Acceleration**: Reduced learning time through transfer
+
+## Citation
+
+If you use the HOT dataset in your research, please cite:
+
+```bibtex
+@inproceedings{berkes2025hot,
+  title={A HOT Dataset: 150,000 Buildings for HVAC Operations Transfer Research},
+  author={anonymous},
+  booktitle={x},
+  year={2025},
+  publisher={x}
+}
+```
+
+## License
+
+This dataset is released under the MIT License. See `LICENSE` file for details.
+
+## Contributing
+
+We welcome contributions to expand and improve the HOT dataset:
+
+- **New building types**: Additional commercial/residential archetypes
+- **Climate expansion**: More geographic locations and weather data
+- **Enhanced metadata**: Additional building characteristics
+- **Analysis tools**: Transfer learning evaluation scripts
+- **Bug reports**: Issues with building models or processing
+
+## Support and Contact
+
+- **Issues**: [GitHub Issues](https://github.com/your-org/building-generator/issues)
+- **Discussions**: [Hugging Face Discussions](https://huggingface.co/datasets/BuildingBench/HOT/discussions)
+- **Email**: anonymous for now
+
+
+---
+
+**HOT Dataset** - Advancing building energy research through comprehensive, standardized, and globally-representative data for intelligent HVAC control systems.