Tool developed as part of the EngD thesis: DaylightGuide - A tool for personalized daylight recommendations for the home office

doi: 10.4121/3ab260d8-0bd5-499d-9638-697f82782f7f.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/3ab260d8-0bd5-499d-9638-697f82782f7f
Datacite citation style:
de Kok, Verena ; van Duijnhoven, Juliëtte ; Christoffersen, Jens (2024): Tool developed as part of the EngD thesis: DaylightGuide - A tool for personalized daylight recommendations for the home office . Version 1. 4TU.ResearchData. dataset.
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

The DaylightGuide tool (1) asks for input about the user’s home office setup , (2) provides insights in the daylighting conditions in the home office, and (3) presents recommendations for optimizing daylight in the home office. (Day)light metrics that are presented are melanopic Equivalent Daylight Illuminance (m-EDI), Daylight Glare Probability (DGP), spatial Daylight Autonomy (sDA), and Useful Daylight Illuminance (UDI). In the tool, these metrics are referred to as the daylight targets. The tool also provides recommendations for optimizing the daylight targets. The tool is developed for use in The Netherlands.


To establish this tool, three steps were taken. First, a questionnaire study was conducted to make an inventory of Dutch home office space characteristics, with a special focus on characteristics that contribute to the indoor daylight distribution. Second, based on these office characteristics, parametric simulation models were developed and annual daylight simulations were conducted using Radiance. The parameters used in the simulations were: the type of window, the orientation of the window, the density of the outside area surrounding the home office, the glazing area of the window, the color of the walls in the home office space, the placement of the window with respect to the occupant, and the distance between the workplace and the window. In specific, simulations were conducted to retrieve m-EDI, DGP, sDA, and UDI values. Third, the simulation results were processed such that the annual data were averaged per month for daytime working hours (i.e., 08.00-18.00). The data were processed to show, for each month of the year, the percentage of work hours during which a certain target was met. This analysis was done for each daylight metric.

A user interface was built for the processed simulation data, which is the developed DaylightGuide tool. Through the interface, anyone working (occasionally) from a home office in The Netherlands can gain insight into the daylighting conditions in their home office as well as recommendations on any changes they could make to their home office to optimize the daylight targets.

The tool is available in English and in Dutch.

The thesis describing the development of the tool can be found here:

  • 2024-07-05 first online, published, posted
Eindhoven University of Technology, Department of the Built Environment


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