Buildings are made comparable by a well-being index

The vision of the project was that buildings become comparable through a well-being index. The index should be calculated from room and user data. The background for the topic was that health and the indoor climate are often in focus, but today there is no possibility to measure and certify them objectively.

Project goals

  1. Develop components of a well-being index
  2. Determine sensors, transmission technology and evaluation
  3. Create prototype and first experience with measurements

Project description

Under the question of benchmarking for buildings, the "Autodiagnosis" working group investigated whether a building can independently investigate and decide how the occupants feel inside (self-diagnosis). For this purpose, possible factors influencing the feeling of well-being were surveyed in a first step. These are divided into factors that can be measured with sensors (quantitative) and those that cannot be measured with sensors (qualitative). The quantitative factors include, for example: temperature, humidity, CO2 content, odorants and particles, brightness and light color, density of people and sound. Qualitative factors included: location, materialization, culture, personal health level, stress, sensations or fitness.

In an accompanying student project, a prototype was developed which measures a large part of the quantitative factors via various sensors. The qualitative factors are collected via a touch display. The evaluation is carried out via a cloud solution. The prototype was set up in two phases in the Department of Computer Science and the user feedback as well as the measured sensor values were recorded. By evaluating the correlations between the measured values, a first "well-being index" was calculated. This was verified in a second phase.

The project has shown what possibilities today's sensors and IoT (Internet of Things) devices offer. However, correlations between visualizations of an index and user reactions also became visible. Further research activities could follow here. At the same time, the working group thought about possible business models. It became clear that there is a conflict of interest between the stakeholders of a building and that the willingness to pay for such measurements is hardly given.


  • Definition of autodiagnosis
  • Layout of possible factors influencing well-being in buildings and selection of relevant factors for the prototype.
  • Measurement methods (sensors and qualitative measurement options)
  • Possible applications for the well-being index
  • Prototype based on a Raspberry Pi, various sensors (temp., humidity, CO2, particles, brightness, light temp., sound) and user feedback (UI).
  • Analysis of the correlations between user feedback and sensor values
  • Definition of an initial well-being index


Tim Weingärtner, 041 757 68 20,

Project Team

  • Roland Achermann, bbv
  • Sibylla Amstutz, HSLU T&A
  • Lukas Arnet, Siworks
  • Patrick Blaser, Condair
  • Marco Frühauf, Otto Fischer
  • Christian Hänggi, Steinel
  • Stefan Ineichen, HSLU T&A
  • Thomas Stadler, Bouygues
  • Olivier Steiger, HSLU T&A
  • Stefan Walker, Steinel
  • Tim Weingärtner, HSLU I
  • Melvin Werthmüller, HSLU I - Student
  • Lukas Arnold, HSLU I - Student