Multi-level indoor navigation ontology for high assurance location-based services

© 2017 IEEE. Indoor navigation will become an importantapplication on a smartphone for Location-Based Service (LBS). An indoor navigation system should work under normalcircumstances and during emergencies, such as fires, during abuilding power shut down, alarm, etc. The LBS should be able tohelp users find the best exit route to the outside of the buildingunder all circumstances and with high reliability. In thisresearch, we develop an indoor ontology model for indoornavigation. This ontology model defines the indoor environmentattributes such as location nodes, and connection points. Thelocation nodes with the location information allow navigation inthe indoor environment. Connection points are able to separatethe map zones and the building floors into a 'Map sheet.' Thisontology approach allows the LBS works in both normalcircumstances and emergencies. This model provides a reliableindoor navigation system for LBS

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