Data generated insights for ventilation systems

In times of energy transition and climate change, the focus is on particularly high energy consumption, which can be reduced through intelligent applications. Also public institutions have to contribute to a sustainable future. Nevertheless traditional ventilation systems are often inefficient and can lead to unnecessary energy consumption, since smart technologies are not yet being used in this context.

CoolVent, developed by the student team, is a user-friendly web-application that allows facility managers to increase efficiency of the controlling for the ventilation systems according to room occupancy and air quality data. The system utilizes data gathered by sensors installed in several rooms across the campus and obtains important information about the semester planning. The room plan is then aggregated and displayed in a transparent view to help the facility manager to efficiently adjust the ventilation at the beginning of the semester. In addition, with sensor data, very granular adjustments can be made regularly, based on recommendations from live sensor data, which measures whether a room was actually occupied at the planned times. This allows fine adjustments to be made at regular intervals throughout the semester.

The CoolVent system can be used by the facility management to improve operation times of their ventilation systems. This would lead to significant reductions of the universities energy demand, as well as operational costs.

The Project was carried out in collaboration with the Co-Innovation Lab at Munich University of Applied Sciences.