WiFi Based Indoor Localization System by Using Weighted Path Loss and Extreme Learning Machine
نویسندگان
چکیده
The methodology of our WiFi based indoor localization system is built upon passive cooperation of occupants only which does not interrupt the daily lives of them. Instead of modifying the hardware or software of occupants’ mobile devices, we upgrade the software of the existing commercial WiFi access points (APs) in the indoor environment to WiFi sniffers, which can detect the received signal strength (RSS) of each mobile device. The RSS and MAC addresses of mobile devices are then sent to a location processor. The location processor will leverage on appropriate localization algorithms to figure out the position of each mobile device and thus its user. Based on our experimental results, our system can provide around 2m localization accuracy consistently in different indoor scenarios. The deployment components of our system are only numbers of software upgraded WiFi APs which can cover the entire competition testbed, and a laptop as the location processor.
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تاریخ انتشار 2014