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Location data has become more and more accessible. Smartphone applications such as location-based services collect location data on a large scale. Up to now, most approaches have relied on past data, but new developments in machine learning and artificial intelligence will soon enable more dynamic real-time use of location data. Companies that embrace these technologies will be able to create competitive advantages.
Location data offers great potential to improve a variety of marketing decisions such as targeted pricing and advertising, store locations and in-store layout. Location based advertising is currently the most common application. It allows targeting all customers within a certain distance of a store. Besides advertising, location data can be used for dynamic pricing decisions. Customers close to competitor’s locations can be charged a lower price for particular products via discounts in order to reduce switching costs. Indoor tracking can help to optimize store design or the positioning of categories and brands. Granular location data about consumers’ movements hence further allows for minimizing potential offline transaction costs based on the distances to stores.
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An Analysis of Wi-Fi Based Indoor Positioning Accuracy
The increasing demand for location based services inside buildings has made indoor positioning a significant research topic. This study deals with indoor positioning using the Wireless Ethernet IEEE 802.11 (Wireless Fidelity, Wi-Fi) standard that has a distinct advantage of low cost over other indoor wireless technologies. The aim of this study is to examine several aspects of location fingerprinting based indoor positioning that affect positioning accuracy. Overall, the positioning accuracy achieved in the performed experiments is 2.0 to 2.5 meters.
Konstantinos Chatzikokolakis, Catuscia Palamidessi and Marco Stronati
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