Présentation des projets sur le site web

Chaque projet soutenu par Gebert Rüf Stiftung est présenté sur le site web de la fondation avec en particulier les données de base du projet. Par cette publication, la fondation informe sur les résultats du soutien accordé et contribue à la communication scientifique au sein de la société.


Viboo – Reducing buildings' energy consumption with predictive control


Für den Inhalt der Angaben zeichnet die Projektleitung verantwortlich.

Données de projet

  • Numéro du projet: GRS-028/22 
  • Subside accordé: CHF 150'000 
  • Consentement: 28.06.2022 
  • Durée: 08.2022 - 08.2023 
  • Champs d'activité:  InnoBooster, seit 2018

Direction du projet

Description du projet

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 transform our research software into a scalable cloud product that can be used by a variety of smart thermostat manufacturers. We are also conduct pilot projects with these manufacturers to further validate the potential of the technology and to demonstrate the integrability with common buildings.

Etat/résultats intermédiaires

In the first project phase, we have transformed our self-learning predictive control algorithm from a research software to a scalable cloud service platform, which in the future will host all of our product features. We have connected several buildings to our platform and are now verifying reliability, scalability and performance. Besides already supporting two manufacturers, we have partnered with Bouygues for a pre-release of our solution in Switzerland. In the second phase, we plan to conduct further pilot projects with major smart thermostat manufacturers, which will lead to B2B business relations and first long-term contracts for our start-up viboo. Moreover, we are working onproduct extensions in the area of demand-side-management.


Personnes participant au projet

Felix Bünning, project leadership
Benjamin Huber, project engineer
TBD, software engineer

Dernière mise à jour de cette présentation du projet  15.02.2023