Persoonlijk Dynamisch licht en binnenklimaat voor kantoren

(Duration: 01/2018 – 03/2020  Funding: TKI Urban Energy 2017)


Office buildings are generally climatized in a uniform fashion during working hours, which results in higher energy usage than necessary. A constant temperature is equated to a higher experience of comfort by users, but there is a large amount of individual variation in experienced comfort. Furthermore, comfort should not be seen as a synonym for health. Research by the University of Maastricht shows that exposure to mildly cold temperatures can significantly improve people’s health by activating brown adipose tissue and improving glucose levels. DYNKA adds the dimension of light to this equation as another factors which can influence health. Research has shown that varying light levels can positively affect the circadian rhythm, comfort, alertness, and general health of workers, while simultaneously lowering energy consumption. PERDYNKA builds upon the project DYNKA by creating technology targeted at the individual user, which enable them to exert some degree of control on the system to further personalize its parameters to their own experience of comfort. These manual adjustments can also provide input for the system when it comes to learning about optimal temperature and lighting conditions, as well as lowering the adoption threshold from the user’s perspective by giving them back some control.

Almende’s contribution

Almende develops a software platform that can dynamically control the light and temperature in an office building based on principles of self-learning and self-organization, as well as manual input from individual users, and deploy said platform in an experimental pilot setting over the course of the project.


The project represents a bridge between the health and energy domains, both of which are highly relevant for Almende. We expect to be able to apply the insights and tools developed in the project in other energy-related projects, specifically when it comes to using self-learning systems to optimize energy usage over time. Finally, the insights from the personalization module will be useful in mapping individual preference levels.


Office environment, lighting, energy savings, office wellbeing, productivity, personalization