ENLITEN - A dataset and its associated analysis code for the paper entitled "Designing sensor sets for capturing energy events in buildings"

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.

Keywords:
Sensors, Energy events, Human behaviour on energy use, Minimal sensor set, Low cost sensor set, energy data analysis
Subjects:
Energy
Information and communication technologies
Instrumentation, sensors and detectors

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". University of Bath. https://doi.org/10.15125/BATH-00241.

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Data

designing-senso ... alysis-code.zip
application/zip (19MB)
Creative Commons: Attribution 4.0

Raw data, analysis and visualisation code

Creators

Jeehang Lee
University of Bath

Tom Lovett
University of Bath

Julian Padget
University of Bath

Sukumar Natarajan
University of Bath

David Coley
University of Bath

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 (EPSRC)
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 articles

Lovett, T., Lee, J.H., 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, pp.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

Departments:

Faculty of Engineering & Design
Architecture & Civil Engineering

Faculty of Science
Computer Science