This research is aimed to answer the main research question: to what extent we can use LiDAR point clouds directly in the PostgreSQL by means of FDW, and thus a FDW supporting the Point Cloud Data Management System is implemented. Then, the range and performance of its functionality are evaluated. The results shows this FDW solution is feasible while the querying time is relevant to the number of returned points. The benefit and problem of this FDW are analyzed.

Indoor localisation is a highly relevant topic. It can be used for many applications,
such as indoor navigation. Current indoor localisation approaches all have certain
downsides. In this report, the results of a completely new indoor localisation approach are described. The aim of this approach is to perform indoor localisation on room level based on a fingerprint solution using point clouds of the ceilings. The ceiling is used, because the ceiling does generally not change much and therefore it is easier to keep an up-to-date database. This research considers both the use of Dense Image Matching (DIM) input from pictures or videos made with a mobile phone and Light Detection And Ranging (LiDAR) input.