Building utilization intelligence (BUI)
Building utilization intelligence concerns creating an understanding how users move through a building, how they interact with its facilities, how they are affected by environmental parameters such as temperature, and how they influence each other. Enabling building utilization intelligence entails having a quality assured understanding of historic utilization, the ability to monitor current and to predict future utilization, as well as being able to influence future utilization. By that venue operators will be able to optimize building utilization, for more efficient and sustainable use of resources in the buildings and higher degree of accessibility to users.
New methods will be developed to acquire and assess building information and utilization data using a large range of sources, covering mobiles, web browsers, sensor infrastructures, and geographic information systems. Further methodology to integrate this heterogeneous data together has to be developed, so that rich trajectories can be formed. This entails leveraging georeferenced data as weak constraints in the localization estimation, estimating reliability of measurements, and standardizing data to common scales. To learn about human utilization from the integrated data, a mobility data mining methodology will be developed. Here, trajectories will be compared and clustered to form mobility spaces that summarize mobility from large data sets, mobility models will be trained to fit human locomotion, and rich observables on the trajectories will be aggregated to maps. Finally, to interpret the data so that building utilization intelligence can be obtained from it, methods for knowledge discovery, utilization monitoring, and prediction will be investigated.