Modern mobile devices integrating sensors, like accelerometers and cameras, are paving the way to the definition of high-quality and accurate geolocation solutions based on the informations acquired by these sensors, and data collected and managed by GSM/3G networks. In this paper, we present a technique that provides geolocation and mobility prediction of mobile devices, mixing the location information acquired with the GSM/3G infrastructure and the results of a landmark matching achieved thanks to the camera integrated on the mobile devices. Our geolocation approach is based on an advanced Time-Forwarding algorithm and on database correlation technique over Received Signal Strength Indication (RSSI) data, and integrates information produced by a landmark recognition infrastructure, to enhance algorithm performances in those areas with poor signal and low accurate geolocation. Performances of the algorithm are evaluated on real data from a complex urban environment.
Landmark-assisted location and tracking in outdoor mobile network / M. Anisetti, C.A. Ardagna, V. Bellandi, E. Damiani, M. Döller, F. Stegmaier, T. Rabl, H. Kosch, L. Brunie. - In: MULTIMEDIA TOOLS AND APPLICATIONS. - ISSN 1380-7501. - 59:1(2012), pp. 89-111.
Landmark-assisted location and tracking in outdoor mobile network
M. Anisetti;C.A. Ardagna;V. Bellandi;E. Damiani;
2012
Abstract
Modern mobile devices integrating sensors, like accelerometers and cameras, are paving the way to the definition of high-quality and accurate geolocation solutions based on the informations acquired by these sensors, and data collected and managed by GSM/3G networks. In this paper, we present a technique that provides geolocation and mobility prediction of mobile devices, mixing the location information acquired with the GSM/3G infrastructure and the results of a landmark matching achieved thanks to the camera integrated on the mobile devices. Our geolocation approach is based on an advanced Time-Forwarding algorithm and on database correlation technique over Received Signal Strength Indication (RSSI) data, and integrates information produced by a landmark recognition infrastructure, to enhance algorithm performances in those areas with poor signal and low accurate geolocation. Performances of the algorithm are evaluated on real data from a complex urban environment.File | Dimensione | Formato | |
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