The precision of RSSI-fingerprinting based on connected Wi-Fi devices

University essay from Högskolan i Borås/Akademin för bibliotek, information, pedagogik och IT; Högskolan i Borås/Akademin för bibliotek, information, pedagogik och IT

Abstract: Received Signal Strength Indication (RSSI) fingerprinting is a popular technique in the fieldof indoor positioning. Many studies on the subject exist acknowledging Wi-Fi signal variationconnected to Wi-Fi signals, but does not discuss possible signal variation created byconnected devices nor consequential precision loss.Understanding more about the origins of signal variation in received signal strength indication(RSSI) fingerprinting would help deal with or prevent them as well as provide moreknowledge for applications based on such signals. Environments with a varying number ofconnected devices would benefit from knowing changes in localization precision resultingfrom the devices connecting and disconnecting from the access point because it wouldindicate whether workarounds for such circumstances would be necessary.To address this issue, the work presented here focuses on how the precision of RSSIfingerprinting vary given different levels of connected Wi-Fi devices. It was carried out byconducting real world experiments at times of low- and normal levels of connected devices toaccess points on two separate locations and evaluating precision changes between statedactivity levels. These experiments took place at the University of Borås as well as at Ericssonin Borås.Experimental findings indicate that the accuracy does deteriorate in higher levels of activitythan in low activity, even though not enough evidence to determine the precision ofdeterioration. The experiments thereby provide a foundation for location-based applicationsand services that can communicate the level of positional error that exist in differentenvironments which would make the users aware but also make the applications adaptaccordingly to different environments. Based on the precision achieved, we identify variousapplications that would benefit from our proposed model. These were applications that wouldtrack mobile resources, find immobile resources, find the movement flows of users as well asnavigation- and Wi-Fi coverage applications.Further research for investigating the exact correlation between access point stress andprecision loss is proposed to fully understand the implications connected devices have onRSSI fingerprinting.

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