Accurate indoor positioning methods for smart devices using improved pedestrian dead-reckoning and collaborative positioning techniques

This thesis investigates and proposes methods that can accurately estimate the locations of smart-device users in indoors, by leveraging on only smart-devices and Wi-Fi access points. Today’s smart-devices contain various sensors which can be utilized to predict user’s motion, e.g. how far its user has walked and what direction is he/she moving towards. The estimation accuracy can be further enhanced by making use of the wireless signals emitted from surrounding Wi-Fi access points and smart-devices of other users. The research contributes to the development of indoor positioning system (IPS) which will make Location-Based Services possible in indoor environments whereby the Global Positioning System (GPS) is unavailable.