2013 · 47 citations · 18 references
ComputingElectrical EngineeringInformation TechnologyMobile ComputingMobile SystemsWireless CommunicationsEnergy-efficient Mobile ComputingIndoor LocalizationRadio-frequency Identification SystemsWireless Channel ModelingWireless Communication ProtocolsWireless NetworksDeploymentEnergy-efficient LocalizationFingerprint-based LocalizationFingerprintingIeee 802.15.4Pervasive ComputingWireless LocalizationZigbee
Indoor localization is essential to enable location-based services in wireless pervasive computing environment. In recent years, WiFi fingerprint-based localization has received considerable attention due to its deployment practicability. In order to achieve on-the-fly localization, WiFi receivers (e.g., mobile phones or laptops) being located need to scan WiFi signals continuously. Since they are normally battery driven, energy efficiency is a very important consideration in WiFi fingerprinting localization systems. Motivated by the fact that IEEE 802.11 (WiFi) and 802.15.4 (ZigBee) channels overlap in the 2.4GHz ISM band, in this work, we develop a WiFi fingerprint-based localization system using ZigBee radio, called ZiLoc. We first present a novel RSS-location fingerprint model to identify the features of surrounding APs. We then propose a simple yet effective method to compute the similarity of two RSS fingerprints. Experimental results demonstrate that ZiLoc can achieve an average of 85% room-level localization accuracy and reduce more than 60% energy consumption compared with the method using WiFi interfaces to collect RSS fingerprints.
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