Indoor Navigation Ontology for Smartphone Semi- Automatic Self-Calibration Scenario

The indoor navigation within public environments and location-based service development are very interesting and promising tasks. This paper describes an ontology-based technique for human movement recognition using the hybrid indoor localization technique based on received signal strength multilateration and pedestrian dead reckoning which relies on internal smartphone sensors. This technique takes into account the anchor node proximity zones and using internal sensors performs the semi-automatic online calibration procedure of log- distance path loss propagation model in accordance with a certain semi-automatic self-calibration scenario. The usage of indoor navigation ontology allows to decrease the influence of radio signal obstructions induced by user's body and moving people