Urban Wi-Fi fingerprinting along a public transport route

  • 1 Department of Geodesy and Geoinformation, Research Division Engineering Geodesy, TU Wien – Vienna University of Technology, Wien, Austria
Guenther RetscherORCID iD: https://orcid.org/0000-0001-6019-1548 and Aizhan Bekenova
  • Department of Geodesy and Geoinformation, Research Division Engineering Geodesy, 27259TU Wien – Vienna University of Technology, Wien, Austria
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The outreach of Wi-Fi localization is extended in this study for urban wide applications as they provide the high potential to employ them for numerous applications for localization and guidance in urban environments. The selected application presented in this paper is the localization and routing of public transport smartphone users. For the conducted investigations, Received Signal Strength Indicator (RSSI) values are collected for users who are travelling from home in a residential neighbourhood to work in the city centre and return along the same route. Special tramway trains are selected which provide two on-board Wi-Fi Access Points (APs). Firstly, the availability, visibility and RSSI stability of the Wi-Fi signal behavior of these APs and the APs in the surrounding environment along the routes is analyzed. Then the trajectories are estimated based on location fingerprinting. A first analyses reveals that significant differences exists between the six employed smartphones as well as times of the day, e. g. in the morning at peak hours or at off-peak hours. From the long-time observations it is seen that the two on-board APs show a high stability of the RSSI signals at the same times of the day and along the whole route. It is therefore currently investigated how they can confirm and validate user localization along the route and if they can contribute to constrain the overall positioning solution in combination with the inertial smartphone sensors. Moreover, the railway track can serve as a further constraint. As an outlook on future work, the development of a Simultaneous Localization and Mapping (SLAM) solution with a fusion with the smartphone inertial sensors is proposed.

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