Project presentations on the website

Every project supported by Gebert Rüf Stiftung is made accessible with a web presentation that informs about the core data of the project. With this public presentation, the foundation publishes the funding results achieved and contributes to the communication of science to society.


viboo – Reducing buildings' energy consumption with predictive control


Für den Inhalt der Angaben zeichnet die Projektleitung verantwortlich.

Project data

  • Project no: GRS-028/22 
  • Amount of funding: CHF 150'000 
  • Approved: 28.06.2022 
  • Duration: 08.2022 - 09.2023 
  • Area of activity:  InnoBooster, seit 2018

Project management

Project description

Heating and cooling of buildings are responsible for a third of the global CO2 emissions. With climate change and emerging discussions regarding energy security and geopolitical conflicts, there is a sincere need to reduce building's energy use. At viboo, we provide self-learning data predictive control algorithms via a Predictive Control as a Service (PCaaS) platform to manufacturers of heating equipment (such as smart thermostats). Our algorithms learn the thermal behavior of a particular building from a single week of measured data and predict how the temperature in the building will evolve in the next couple of hours depending on several factors such as the weather forecast. This allows it to calculate precisely how much heating is required to keep the desired user's comfort. Manufacturers of smart thermostats can use our cloud software service to increase energy efficiency of their products at very low costs, and the end-users can simply book the service through their smart-phone or web app. In our research studies and in pilot projects, one with the market leader Danfoss, we have shown energy savings of up to 20-40%, while improving comfort. The algorithms can also be used to provide electricity reserves (Demand-Side-Managment, DSM) with buildings to allow a higher share of volatile renewables in in the electricity grid.
In this InnoBooster project, we have transformed our research software into a scalable cloud product that can be used by a variety of smart thermostat manufacturers. We have also conducted pilot projects with these manufacturers as well as business and public end-users to further validate the potential of the technology and to demonstrate the integrability with common buildings.


We have transformed our self-learning predictive control algorithm from a research software to a scalable cloud service platform, which hosts all our product features. We have connected several buildings to our platform and verified reliability, scalability, and performance over the course of one heating season. Our platform supports various manufacturers, and we have partnered with national installation companies for a product roll-out in Switzerland. Packages of thermostats, installation and a subscription can now be bought by B2B and B2G customers.


Persons involved in the project

Felix Bünning, project leadership
Benjamin Huber, project engineer
Nicolas Lefebure, software and development engineer

Last update to this project presentation  18.03.2024