Why is fingerprint-based indoor localization still so hard?

Wireless indoor localization systems and especially signal strength fingerprinting techniques have been the subject of significant research efforts in the last decades. However, most of the proposed solutions require a costly site-survey to build the radio map which can be used to match radio signatures with specific locations. We investigate a novel indoor localization system that addresses the data collection problem by progressively and semi-autonomously creating a radio-map with limited interaction cost. Moreover, we investigate how spatiotemporal and hardware properties-based variations can affect the RSSI values collected and significantly influence the resulting localization. We show the impact of these fluctuations on our system and discuss possible mitigations.