Abstract
This paper introduces how to fuse the data acquired from different sensors available in commodity smartphones to build accurate location-based services, pursuing a good balance between accuracy and performance. Using scale invariant features from the images captured using the smartphone camera, we perform a matching process against previously obtained images to determine the current location of the device. Several refinements are introduced to improve the performance and the scalability of our proposal. Location fingerprinting, based on IEEE 802.11, will be used to determine a cluster of physical points, or zone, where the device seems to be according to the received signal strength. In this way, we will reduce the number of images to analyze to those contained in the tentative zone. Additionally, accelerometers will be also considered in order to improve the system performance, by means of a motion estimator. This set of techniques enables a wide range of new location-based applications.
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Ruiz-Ruiz, A.J., Canovas, O., Rubio Muñoz, R.A., Lopez-de-Teruel Alcolea, P.E. (2012). Using SIFT and WiFi Signals to Provide Location-Based Services for Smartphones. In: Puiatti, A., Gu, T. (eds) Mobile and Ubiquitous Systems: Computing, Networking, and Services. MobiQuitous 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30973-1_4
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DOI: https://doi.org/10.1007/978-3-642-30973-1_4
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