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Device-free localization (DFL) is an emerging technology for estimating theposition of a human or object that is not equipped with any electronic tag, norparticipate actively in the localization process. Similar to device-basedlocalization, the initial phase in DFL is to build the fingerprint databasewhich is usually done manually using site surveying. This process is tedious,time-consuming, and vulnerable to environmental dynamics. Motivated by therecent advances in the Internet of Things (IoT), this paper introducesRadioGrapher; a system that automates the process of device-free fingerprintcalibration in IoT environments. RadioGrapher leverages the device-basedlocations of entities in the area of interest in a crowd-sensing manner, aidedwith Fresnel zones of the wirelessly connected IoT devices to automaticallyconstruct a device-free fingerprint. Experimental evaluation of RadioGrapher inan IoT testbed using multiple entities shows that it can construct DFLfingerprints with high accuracy. Moreover, its median localization accuracy iscomparable to that of manual fingerprinting. This comes with no calibrationoverhead, highlighting the promise of RadioGrapher as a crowdsourcingdevice-free fingerprint constructor in IoT environments.

Zero-Calibration Device-free Localization for the IoT based on Participatory Sensing