thermal-comfort-classification
Model for classification of thermal comfort states based on multi-modal input data.
Science Score: 67.0%
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✓DOI references
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Low similarity (6.0%) to scientific vocabulary
Repository
Model for classification of thermal comfort states based on multi-modal input data.
Basic Info
- Host: GitHub
- Owner: az16
- License: mit
- Language: Python
- Default Branch: main
- Size: 431 KB
Statistics
- Stars: 3
- Watchers: 3
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
AutoTherm: A Dataset and Benchmark for Thermal Comfort Estimation Indoors and in Vehicles
IMWUT Paper doi: 10.1145/3678503
Mark Colley*, Sebastian Hartwig*, Albin Zeqiri, Timo Ropinski, Enrico Rukzio
For the full dataset, see the HuggingFace page.
Dataset
Basic description: * Age: M=24.64, SD= 3.03, range=[20, 33] * Gender : Male: 9, Female=12 * Weight: M=69.97, SD=15.02, range=[53, 106.9] * Height: M=174.50, SD=10.18, range=[155, 198] * BodyFat: M=0.22, SD=0.05, range=[0.14,0.34] * BodyTemp: M=36.38, SD=0.31, range=[35.8, 37.2] * Meal: M=4.23, SD=4.92, range=[0, 20] * Sport-Last-Hour: Yes: 3, No: 18 * Tiredness: M=4.12, SD=1.73, range=[2, 8] * Black-Globe-Temp: M=25.53, SD=3.92, range=[16.9, 33.6] * Clothing-Level: M=0.60, SD=0.05, range=[0.45, 0.69] * Heart-Rate: M=2.94, SD=13.46, range=[40.0, 191.99] * Wrist-Skin-Temperature: M=33.82, SD=1.75, range=[27.91, 36.95] * GSR: M=1.42, SD=2.81, range=[0.0, 16.9] * Ambient-Temp: M=25.31, SD=3.72, range=[17.1, 33.7] * Relative-Humidity: M=31.35, SD=8.86, range=[12.0, 55.0] * Emotion-ML: Anger: 0.1099, Disgust: 0.0008, Fear: 0.1348, Happy: 0.0898, Neutral: 0.4114, Sadness: 0.2087, Surprise: 0.0446 * Emotion-Self: Anger:0.0083, Contempt: 0.0003, Disgust: 0.0314, Fear: 0.0003, Happiness: 0.0835, Neutral: 0.8638, Sadness: 0.0073, Surprise: 0.0049
Preprocessing Steps
- Outlier removal based on continuous features
- Cleaning of empty lines
- Normalization
- Data augmentation
Contact Details
For inquiries, contact Mark Colley or Albin Zeqiri
Owner
- Name: Albin
- Login: az16
- Kind: user
- Location: Ulm
- Company: Ulm University
- Twitter: azeqiri6
- Repositories: 2
- Profile: https://github.com/az16
PhD Student and Research Associate
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Colley"
given-names: "Mark"
orcid: "https://orcid.org/0000-0001-5207-5029"
- family-names: "Hartwig"
given-names: "Sebastian"
- family-names: "Zeqiri"
given-names: "Albin"
- family-names: "Ropinski"
given-names: "Timo"
- family-names: "Rukzio"
given-names: "Enrico"
title: "AutoTherm: A Dataset and Benchmark for Thermal Comfort Estimation Indoors and in Vehicles"
version: 1.0.0
doi: 10.1145/3678503
date-released: 2024-09
publisher: "Association for Computing Machinery"
journal: "Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"
url: "https://github.com/az16/thermal-comfort-classification"
GitHub Events
Total
- Watch event: 3
- Push event: 8
Last Year
- Watch event: 3
- Push event: 8
Dependencies
- matplotlib *
- opencv-python *
- pandas *
- pythermalcomfort *
- pytorch-lightning ==1.6.2
- scikit-learn *
- seaborn *
- wandb *