SML2010
Donated on 1/8/2014
This dataset is collected from a monitor system mounted in a domotic house. It corresponds to approximately 40 days of monitoring data.
Dataset Characteristics
Multivariate, Sequential, Time-Series, Text
Subject Area
Computer Science
Associated Tasks
Regression
Feature Type
Real
# Instances
4137
# Features
-
Dataset Information
Additional Information
The dataset could contain missing values. The data was sampled every minute, computing and uploading it smoothed with 15 minute means. The header of the data file is a commentary (begins with #) indicating which data is stored at which column (in Spanish). The data is time information is in UTC.
Has Missing Values?
Yes
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 10 of 24
Additional Variable Information
The attributes are: 1. Date: in UTC. 2. Time: in UTC. 3. Indoor temperature (dinning-room), in ºC. 4. Indoor temperature (room), in ºC. 5. Weather forecast temperature, in ºC. 6. Carbon dioxide in ppm (dinning room). 7. Carbon dioxide in ppm (room). 8. Relative humidity (dinning room), in %. 9. Relative humidity (room), in %. 10. Lighting (dinning room), in Lux. 11. Lighting (room), in Lux. 12. Rain, the proportion of the last 15 minutes where rain was detected (a value in range [0,1]). 13. Sun dusk. 14. Wind, in m/s. 15. Sun light in west facade, in Lux. 16. Sun light in east facade, in Lux. 17. Sun light in south facade, in Lux. 18. Sun irradiance, in W/m2. 19. Enthalpic motor 1, 0 or 1 (on-off). 20. Enthalpic motor 2, 0 or 1 (on-off). 21. Enthalpic motor turbo, 0 or 1 (on-off). 22. Outdoor temperature, in ºC. 23. Outdoor relative humidity, in %. 24. Day of the week (computed from the date), 1=Monday, 7=Sunday.
Dataset Files
| File | Size |
|---|---|
| NEW-DATA-1.T15.txt | 386.6 KB |
| NEW-DATA-2.T15.txt | 194.4 KB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset sml2010 = fetch_ucirepo(id=274) # data (as pandas dataframes) X = sml2010.data.features y = sml2010.data.targets # metadata print(sml2010.metadata) # variable information print(sml2010.variables)
Romeu-Guallart, P. & Zamora-Martinez, F. (2014). SML2010 [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5RS3S.
Creators
Pablo Romeu-Guallart
Francisco Zamora-Martinez
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.