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Wireless signal strength fingerprinting has become an increasingly popular technique for realizing indoor localization systems using existing WiFi infrastructures. However, these systems typically require a time-consuming and costly training phase to build the radio map. Moreover, since radio signals change and fluctuate over time, map maintenance requires continuous re-calibration. The authors introduce a new concept called "Asynchronous interval labeling" that addresses these problems in the context of user-generated place labels. By using an accelerometer to detect whether a device is moving or stationary, the system can continuously and unobtrusively learn from all radio measurements during a stationary period, thus greatly increasing the number of available samples.
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