Using a Decision Tree for Real-Time Distributed Indoor Localization in Healthcare Environments

Decision trees can be of great importance when trying to perform indoor localization on room level basis. These decision trees enable mobile nodes with limited computational resources to locate themselves inside a building without the need of heavy computations. This paper elaborates on the use of a decision tree for tracking moving mobile nodes inside healthcare facilities with possibly thousands of mobile nodes which need to be tracked at the same time. By avoiding a centralized localization attempt for all of the mobile nodes, we prove a distributed localization algorithm based on a decision tree can enable the tracking and tracing of this amount of mobile nodes. The same decision tree is used for determining if indoor localization without Line-Of-Sight between beacons and mobile nodes is feasible, for instance when people are standing between a mobile unit and a fixed beacon.

ISBN:9781479950942

Publication year:2014

BOF-keylabel:yes

IOF-keylabel:yes

Authors from:Private, Higher Education

Accessibility:Closed