Wireless indoor localisation using received signal strength fingerprinting with Context Aware Partitioning

We presented a wireless indoor localisation system that tracked users in an indoor environment, using the FCAP tracking model. The FCAP model used RSSI fingerprinting combined with context-aware information, such as a building floorplan. The use of context aware information allowed the FCAP model to improve position accuracy. We evaluated and compared the FCAP model to conventional multilateration. The FCAP model performed better than multilateration, where the layout of the wireless indoor localisation network did not restrict the position of the mobile node to areas covered by multiple reference nodes. This was advantageous by not restricting the placement of the reference nodes. Further work involves investigating the use of multiple operating mobile nodes with the FCAP model and how 3-dimensional localisation can be achieved with context awareness of the surrounding environment.