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toni
2018-10-18 09:58:53 +02:00
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tex_review/chapters/conclusion.tex
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\section{Conclusion} \section{Conclusion}
\commentByToni{Wie wirkt sich das jetzt auf ein generelles Gebäude aus?}
%what you have seen %what you have seen
Within this work we provided an extensive overview of our smartphone-based indoor localization system. Within this work we provided an extensive overview of our smartphone-based indoor localization system.
The thorough evaluation demonstrated the good performance under multiple scenarios within a complex environment. The thorough evaluation demonstrated the good performance under multiple scenarios within a complex environment.

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tex_review/chapters/experiments.tex
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@@ -53,30 +53,35 @@ Adding knowledge like semantic information such as room numbers would of course
All other steps were performed on-site using our smartphone app for localization. All other steps were performed on-site using our smartphone app for localization.
As the museum did not provide any Wi-Fi infrastructure, we installed the \SI{42}{} beacons as explained above. As the museum did not provide any Wi-Fi infrastructure, we installed the \SI{42}{} beacons as explained above.
Thanks to the great support of the museum's janitor, this step took only \SI{30}{\minute}, as he was well aware of all available power outlets and also helped plugging them in. Thanks to the great support of the museum's janitor, this step took only \SI{30}{\minute}, as he was well aware of all available power outlets and also helped plugging them in.
After that, each of the \SI{133}{} reference points was scanned 30 times ($\approx \SI{25}{\second}$ scan time) using the a Motorola Nexus 6 at \SI{2.4}{GHz}. After that, each of the \SI{133}{} reference points was scanned 30 times ($\approx \SI{25}{\second}$ scan time) using a Motorola Nexus 6 at \SI{2.4}{GHz}.
This took \SI{85}{\minute}, as all measurements were conducted using the same smartphone. This took \SI{85}{\minute}, as all measurements were conducted using the same smartphone.
The optimized Wi-Fi model and the mesh can be created automatically within a few seconds directly on the smartphone, which then enables the pedestrian to start the localization. The optimized Wi-Fi model and the mesh can be created automatically within a few seconds directly on the smartphone, which then enables the pedestrian to start the localization.
Of course, for the experiments conducted below several additional knowledge was obtained to evaluate the quality of the proposed methods and the overall localization error. Of course, for the experiments conducted below several additional knowledge was obtained to evaluate the quality of the proposed methods and the overall localization error.
Thus the above provided times were measured for a pure localization installation, as for example a customer would order, while the experiments were performed in a 2-day period. Thus the above provided times were measured for a pure localization installation, as for example a customer would order, while the experiments were performed in a 2-day period.
Nevertheless, we believe that an on-site setup-time of less then \SI{120}{\minute} is a big step for the practicability of localization systems. Nevertheless, we believe that an on-site setup-time of less then \SI{120}{\minute} is a big step for the practicability of localization systems.
%TODO: In addition the steps are very easy in our opinion, enabling not only people who are familier with the system to install... In addition, the above steps do not require a high level of detail in their execution, which should also allow unbiased persons to set up the system.}
}
%TODO: Experimente sind wissenschaftlich und deswegen haben wir.. extra app, um ungaben über die activity zu machen über so button. (eventl bild beider apps? also lokalisierung und aufnahme app? platz ist jetzt ja :D.
Sensor measurements are recorded using a simple mobile application that implements the standard Android sensor functionalities. \add{As mentioned, the here presented localization system was implemented as an Android App.
It was written in high performant C++ code, enabling to run completely on the smartphone and thus not requiring any connection to a server.
However, since the experiments required a lot of different information to evaluate the methods, a second, very simple application was developed to record them.
It implements the standard Android sensor functionalities and provides a very simple user interface so that even non-technical users can use it.}
As smartphones we used either a Samsung Note 2, Google Pixel One or Motorola Nexus 6. As smartphones we used either a Samsung Note 2, Google Pixel One or Motorola Nexus 6.
The computation of the state estimation as well as the \docWIFI{} optimization are done offline using an Intel Core i7-4702HQ CPU with a frequency of \SI{2.2}{GHz} running \add{\SI{8}{threads} on \SI{4}{cores}} and \SI{16}{GB} main memory. The computation of the state estimation as well as the \docWIFI{} optimization are done offline using an Intel Core i7-4702HQ CPU with a frequency of \SI{2.2}{GHz} running \add{\SI{8}{threads} on \SI{4}{cores}} and \SI{16}{GB} main memory.
However, similar to our \add{previously presented system}, the setup is able to run completely on commercial smartphones as it \add{is} written in high performant C++ code \cite{torres2017smartphone}. \add{An offline computation has practical advantages, such as easier evaluation of the results or shorter waiting times due to higher computing power.
Nevertheless, Android App and offline application are both based on the same C++ backend for localization.}
%However, similar to our \add{previously presented system}, the setup is able to run completely on commercial smartphones as it \add{is} written in high performant C++ code \cite{torres2017smartphone}.
%Sensor measurements are recorded using a simple mobile application that implements the standard Android SensorManager. %Sensor measurements are recorded using a simple mobile application that implements the standard Android SensorManager.
The experiments are separated into four sections: The experiments are separated into five sections:
At first, we discuss the performance of the novel transition model and compare it to a grid-based approach. At first, we discuss the performance of the novel transition model and compare it to a grid-based approach.
In section \ref{sec:exp:opti} we have a look at \docWIFI{} optimization and how the real \docAPshort{} positions differ from it. In section \ref{sec:exp:opti} we have a look at \docWIFI{} optimization and how the real \docAPshort{} positions differ from it.
Following, we conducted several test walks throughout the building to examine the estimation accuracy (in \SI{}{\meter}) of the localization system and discuss the here presented solutions for sample impoverishment. Following, we conducted several test walks throughout the building to examine the estimation accuracy (in \SI{}{\meter}) of the localization system and discuss the here presented solutions for sample impoverishment.
\add{In section \ref{sec:eval:act} the threshold-based activity recognition is evaluated, providing a detection rate for the test walks utilized before.}
Finally, the respective estimation methods are discussed in section \ref{sec:eval:est}. Finally, the respective estimation methods are discussed in section \ref{sec:eval:est}.
\commentByToni{Activity Recognition Experimente. Wie gut ist es?}
\subsection{Transition} \subsection{Transition}
\begin{figure}[t] \begin{figure}[t]
@@ -212,9 +217,8 @@ A more realistic model would not only mean an overall improvement of the results
Further evaluations and discussions regarding the here used optimization can be found in \cite{Ebner-17}. Further evaluations and discussions regarding the here used optimization can be found in \cite{Ebner-17}.
\subsection{Localization Error} \subsection{Localization Error}
\label{sec:exp:loc}
\begin{figure}[t] \begin{figure}[t]
\centering \centering
@@ -370,6 +374,14 @@ In contrast, a real sample impoverishment scenario, as seen in walk 0 (cf. fig.
Nevertheless, such an slightly increased diversity of \SI{8.4}{\meter} is enough to influence the estimation error of the $D_\text{KL}$ in a negative way (cf. walk 1 in table \ref{table:overall}). Nevertheless, such an slightly increased diversity of \SI{8.4}{\meter} is enough to influence the estimation error of the $D_\text{KL}$ in a negative way (cf. walk 1 in table \ref{table:overall}).
Ironically, this is again some type of sample impoverishment, caused by the aforementioned environmental restrictions not allowing particles inside walls or other out of reach areas. Ironically, this is again some type of sample impoverishment, caused by the aforementioned environmental restrictions not allowing particles inside walls or other out of reach areas.
%%activity
\subsection{Activity Recognition}
\label{sec:eval:act}
Wie gut ist die Activity...
%%estimation %%estimation
\subsection{Estimation} \subsection{Estimation}
\label{sec:eval:est} \label{sec:eval:est}