ISPRS-Annals ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Annals ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9050 Copernicus Publications Göttingen, Germany 10.5194/isprs-annals-IV-4-W1-105-2016 REAL TIME LOCALIZATION OF ASSETS IN HOSPITALS USING QUUPPA INDOOR POSITIONING TECHNOLOGY van der Ham M. F. S. 1 Zlatanova S. 2 Verbree E. 3 Voûte R. 4 Delft University of Technology, Faculty of Architecture and the Built Environment, MSc Geomatics, Julianalaan 134, 2628 BL, Delft, the Netherlands Delft University of Technology, Faculty of Architecture and the Built Environment, Department of Urbanism, 3D Geoinformation, Julianalaan 134, 2628 BL, Delft, the Netherlands Delft University of Technology, Faculty of Architecture and the Built Environment, OTB - Research Institute for the Built Environment, GIS Technology, Julianalaan 134, 2628 BL, Delft, the Netherlands CGI Nederland BV, Meander 901, P.O. Box 7015, 6801 HA Arnhem, the Netherlands 05 09 2016 IV-4/W1 105 110 This article is available from https://isprs-annals.copernicus.org/articles/isprs-annals-IV-4-W1-105-2016.html The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/isprs-annals-IV-4-W1-105-2016.pdf

At the most fundamental level, smart buildings deliver useful building services that make occupants productive. Smart asset management in hostipals starts with knowing the whereabouts of medical equipment. This paper investigates the subject of indoor localization of medical equipment in hospitals by defining functional spaces. In order to localize the assets indoors, a localization method is developed that takes into account several factors such as geometrical influences, characteristics of the Quuppa positioning system and obstructions in the indoor environment. For matching the position data to a real world location, several location types are developed by subdividing the floor plan into location clusters. The research has shown that a high-performance level can be achieved for locations that are within the high-resolution range of the <i>receiver</i>. The performance at the smallest subspaces can only be achieved when having a dense distribution of <i>receivers</i>. Test cases that were defined for specific situations in the test-area show successful localization in these subspaces for the majority of the test data.