Small fixes abstract & intro
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\abstract{
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\abstract{
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Within this work we present an updated version of our \del{award-winning} indoor localization system for smartphones.
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Within this work we present an updated version of our \del{award-winning} indoor localization system for smartphones.
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The \add{pedestrian's} position is given by means of recursive state estimation using a particle filter to incorporate different probabilistic sensor models.
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The \add{pedestrian's} position is given by means of recursive state estimation using a particle filter to incorporate different probabilistic sensor models.
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Our \del{rapid computation} \add{recently presented approximation} scheme of the kernel density estimation allows to find an exact estimation of the current position\add{, instead of classical methods like weighted-average}.
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Our \del{rapid computation} \add{recently presented approximation} scheme of the kernel density estimation allows to find an exact estimation of the current position\add{, compared to classical methods like weighted-average}.
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%
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%
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Absolute positioning information is given by a comparison between recent \docWIFI{} measurements of nearby access points and signal strength predictions.
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Absolute positioning information is given by a comparison between recent \docWIFI{} measurements of nearby access points and signal strength predictions.
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Instead of using time-consuming approaches like classic fingerprinting or measuring the exact positions of access points, we use an optimization scheme based on a few reference measurements to estimate a corresponding \docWIFI{} model.
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Instead of using time-consuming approaches like classic fingerprinting or measuring the exact positions of access points, we use an optimization scheme based on a few reference measurements to estimate a corresponding \docWIFI{} model.
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@@ -28,7 +28,7 @@ Many unknown quantities, like the walls definitive material or thickness, make i
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Additionally, \del{most wireless} \add{many of these} approaches are based on a line-of-sight assumption.
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Additionally, \del{most wireless} \add{many of these} approaches are based on a line-of-sight assumption.
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Thus, the performance will be even more limited due to the irregularly shaped spatial structure of such buildings.
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Thus, the performance will be even more limited due to the irregularly shaped spatial structure of such buildings.
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Our approach tries to avoid those problems using an optimization scheme for Wi-Fi based on a \del{few} \add{set of} reference measurements.
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Our approach tries to avoid those problems using an optimization scheme for Wi-Fi based on a \del{few} \add{set of} reference measurements.
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We distribute a \del{small number} \add{set} of \del{simple} \add{small (\SI{2.8}{\centi\meter} x \SI{3.5}{\centi\meter})} and cheap \add{($\approx \SI{10}{\$}$)} \docWIFI{} beacons over the whole building \add{to ensure a reasonable coverage} and instead of measuring their position \add{and necessary parameters, we use our optimization scheme, initially presented in \cite{Ebner-17}}.
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We distribute a \del{small number} \add{set} of \del{simple} \add{small (\SI{2.8}{\centi\meter} x \SI{3.5}{\centi\meter})} and cheap \add{($\approx \$10$)} \docWIFI{} beacons over the whole building \add{to ensure a reasonable coverage} and instead of measuring their position \add{and necessary parameters, we use our optimization scheme, initially presented in \cite{Ebner-17}}.
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\add{An optimization scheme is able to compensate for wrongly measured access point positions, inaccurate building plans or other knowledge necessary for the Wi-Fi component.
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\add{An optimization scheme is able to compensate for wrongly measured access point positions, inaccurate building plans or other knowledge necessary for the Wi-Fi component.
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}
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}
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@@ -65,11 +65,11 @@ The goal of this work is to propose a fast to deploy \del{and low-cost} localiza
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\add{However, many state-of-the-art solutions are evaluating their systems within office or faculty buildings, offering a modern environment and well described infrastructure.}
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\add{However, many state-of-the-art solutions are evaluating their systems within office or faculty buildings, offering a modern environment and well described infrastructure.}
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Consequently, we believe that by utilizing our localization approach to such a challenging scenario, it is possible to prove those characteristics.
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Consequently, we believe that by utilizing our localization approach to such a challenging scenario, it is possible to prove those characteristics.
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\add{To initially set up the system we only require a blueprint to create the floorplan, some Wi-Fi infrastructure, without any further information about access point positions or parameters, and a smartphone carried by the pedestrian to be localized.
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\add{To initially set up the system we only require a blueprint to create the floorplan, some Wi-Fi infrastructure, without any further information about access point positions or parameters, and a smartphone carried by the pedestrian to be localized.
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The existing Wi-Fi infrastructure can consist of the aforementioned Wi-Fi beacons and / or already existing access points.
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The existing Wi-Fi infrastructure can consist of the aforementioned Wi-Fi beacons and/or already existing access points.
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The combination of both technologies is feasible, depending on the scenario and building.
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The combination of both technologies is feasible, depending on the scenario and building.
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Nevertheless, the museum considered in this work has no Wi-Fi infrastructure at all, not even a single access point.
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Nevertheless, the museum considered in this work has no Wi-Fi infrastructure at all, not even a single access point.
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Thus, we distributed a set of \SI{42}{beacons} throughout the complete building by simply plugging them into available power outlets.
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Thus, we distributed a set of \SI{42}{beacons} throughout the complete building by simply plugging them into available power outlets.
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Despite evaluating the novel contributions and the overall performance of the system, we have carried out additional experiments to determine the performance of our Wi-Fi optimization in such a complex scenario as well as a detailed comparison between KDE-based and weighted-average position estimation.}
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In addition to evaluating the novel contributions and the overall performance of the system, we have carried out further experiments to determine the performance of our Wi-Fi optimization in such a complex scenario as well as a detailed comparison between KDE-based and weighted-average position estimation.}
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%novel experiments to previous methods due to the complex scenario blah und blub.}
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%novel experiments to previous methods due to the complex scenario blah und blub.}
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%Finally, it should be mentioned that the here presented work is an highly updated version of the winner of the smartphone-based competition at IPIN 2016 \cite{Ebner-15}.
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%Finally, it should be mentioned that the here presented work is an highly updated version of the winner of the smartphone-based competition at IPIN 2016 \cite{Ebner-15}.
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