The research area sensor data fusion is based on raw data that are gathered by multiple different sensors in an intelligent building. It takes a big amount of data as given, so the research topic is to interpret them in an intelligent way and draw conclusions with for example artificial intelligence.
One approach is to analyze the data with deep learning algorithms and get to know how many people occupy a room. Therefore different combinations of sensors will be tested, to compare the quality of information they offer. If the accuracy of occupancy estimation is high enough, and the system has enough test-data with known occupancy-count, the next step is occupancy-prediction. If a system is able to predict how many people will be in a room in one hour, it can adjust the heating or cooling before the temperature becomes uncomfortable, not when sensors show that the air is already inconvenient.
The necessary information will be gathered by pre-installed sensors as part of a new intelligent building on the one side, and by sensors composed and placed for this research particularly on the other side. One more task of this research area is to build sensors useful for research area one and research area three of this institute.