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For Wi-Fi positioning location fingerprinting is one of the most commonly employed localization technique. To achieve an\udacceptable level of positioning accuracy on the few meter level, i.e., to provide at least room resolution in buildings, such an\udapproach is very labour consuming as it requires a high density of reference points. Thus, the novel approach developed aims at a\udsignificant reduction of workload for the training phase. The basic idea is to intelligently choose waypoints along possible users’\udtrajectories in the indoor environment. These waypoints are termed intelligent checkpoints (iCPs) and serve as reference points for\udthe fingerprinting localization approach. They are selected along the trajectories in such a way that they define a logical sequence\udwith their ascending order. Thereby, the iCPs are located, for instance, at doors at entrances to buildings, rooms, along corridors,\udetc., or in low density along the trajectory to provide a suitable absolute user localization. Continuous positioning between these\udiCPs is obtained with the help of the smartphones’ inertial sensors. While walking along a selected trajectory to the destination a\uddynamic recognition of the iCPs is performed and the drift of the inertial sensors is reduced as the iCP recognition serves as absolute\udposition update. Conducted experiments in a multi-storey office building have shown that positioning accuracy of around 2.0 m are\udachievable which goes along with a reduction of workload by three quarter using this novel approach. The iCP concept and\udperformance are presented and demonstrated in this paper

INDOOR SMARTPHONE NAVIGATION USING A COMBINATION OF WI-FI AND INERTIAL NAVIGATION WITH INTELLIGENT CHECKPOINTS