Improving indoor localization by user feedback

In this paper we introduce a new method to incorporate the user as an additional information source for the purpose of indoor localization. Therefore, the user is interrogated about certain characteristics in his/her environment. The questions are generated by a knowledge-based system built on ontologies. We provide a new statistical model to evaluate the user´s answer and integrate it into the particle filter, which is used for the localization system. Our results show that the user´s feedback significantly improves localization results.