ENLITEN - A dataset and its associated analysis code for the paper entitled "Designing sensor sets for capturing energy events in buildings"
This dataset contains data and software source code supporting the paper entitled 'Design sensor sets for capturing energy events in buildings'. It contains raw data from sets of domestic sensors measuring temperature, humidity, levels of sound, light and carbon dioxide, and power consumption. It also contains analysis code and visualisation code written for R and Python.
Cite this dataset as:
Lee, J.,
Gabe-Thomas, E.,
Lovett, T.,
Padget, J.,
Natarajan, S.,
Coley, D.,
2016.
ENLITEN - A dataset and its associated analysis code for the paper entitled "Designing sensor sets for capturing energy events in buildings".
Bath: University of Bath Research Data Archive.
Available from: https://doi.org/10.15125/BATH-00241.
Export
Data
designing-sensor … analysis-code.zip
application/zip (19MB)
Creative Commons: Attribution 4.0
Raw data, analysis and visualisation code
Creators
Jeehang Lee
University of Bath
Elizabeth Gabe-Thomas
University of Bath
Tom Lovett
University of Bath
Julian Padget
University of Bath
Sukumar Natarajan
University of Bath
David Coley
University of Bath
Contributors
University of Bath
Rights Holder
Coverage
Collection date(s):
From 1 August 2013 to 1 October 2013
Documentation
Data collection method:
Details of the methodology may be found in the associated manuscript. All data was collected approximately from Aug 2013 to Oct 2013. An instruction for the participants attached here (instruction.pdf) shows the way how the data was collected in the individual homes.
Technical details and requirements:
The data files are in comma-separated (.csv) and tab-separated (.txt) plain text formats. The .py source code files target Python v2.x and use only standard libraries. The R source code files use the following libraries available from CRAN: entropy, ggplot2, plyr, randomForest, reshape2, scales. Some pre-compiled visualisations are included as PDF files.
Additional information:
The zip file contains a set of top level data and source code files, a further files arranged into 5 directories. The 'analysis_datasets' directory contains the main dataset used for the paper. It also includes the machine learning algorithm code (random forest in this case), its associated data and a document showing a selected feature set. The 'gt', 'sd', and 'tf' directories contain raw data collected by one of participants. The 'set_viz' directory contains visualisation code as well as knapsack (cost–benefit) optimisation code for the selection of minimal sensor sets subject to the budget.
Documentation Files
instructions.pdf
application/pdf (209kB)
Legal and Ethical Documents
instructions.pdf
application/pdf (209kB)
Creative Commons: Attribution 4.0
Participant information sheet
Funders
Engineering and Physical Sciences Research Council
http://dx.doi.org/10.13039/501100000266
Energy Literacy through an Intelligent Home Energy Advisor ENLITEN
EP/K002724/1
Publication details
Publication date: 1 October 2016
by: University of Bath
Version: 1
DOI: https://doi.org/10.15125/BATH-00241
URL for this record: https://researchdata.bath.ac.uk/id/eprint/241
Related papers and books
Lovett, T., Lee, J., Gabe-Thomas, E., Natarajan, S., Brown, M., Padget, J., and Coley, D., 2016. Designing sensor sets for capturing energy events in buildings. Building and Environment, 110, 11-22. Available from: https://doi.org/10.1016/j.buildenv.2016.09.004.
Contact information
Please contact the Research Data Service in the first instance for all matters concerning this item.
Contact person: Jeehang Lee
Faculty of Engineering & Design
Architecture & Civil Engineering
Faculty of Science
Computer Science