erklaerung in den experimenten wie der aufbau ist

tex_review/chapters/abstract.tex

@@ -20,7 +20,7 @@ To stress our system, we have chosen a very challenging test scenario.
 All experiments were conducted within a 13th century historic building, formerly a convent and today a museum. 
 The system is evaluated using 28 distinct measurement series on four different test walks, up to \SI{310}{\meter} length and \SI{10}{\minute} duration.
 It can be shown, that the here presented localization solution is able to provide a small positioning error, even under difficult conditions and faulty measurements. 
-\del{Our advanced} \add{The introduced} filtering methods allow for a real fail-safe system, while the optimization scheme enables a setup-time of under \SI{120}{\minute} for the \del{complete building}  \add{building's \SI{2500}{\square\meter} walkable area}. 
+\del{Our advanced} \add{The introduced} filtering methods allow for a real fail-safe system, while the optimization scheme enables an \add{on-site} setup-time of \add{less then} \SI{120}{\minute} for the \del{complete building}  \add{building's \SI{2500}{\square\meter} walkable area}. 
 %We are able to resolve sample impoverishment whenever it occurs and thus provide a real fail-safe system. 
 %finally compare the standard weighted-average estimator with our kernel density approach. 
 }

tex_review/chapters/experiments.tex

@@ -4,15 +4,65 @@ As explained at the very beginning of this work, we wanted to explore the limits
 By utilizing \del{it to} \add{the proposed technology in} a 13th century historic building, we created a challenging scenario not only because of the various architectural factors, but also because of its function as a museum.
 During all experiments, the museum was open to the public and had a varying number of \SI{10}{} to \SI{50}{} visitors while recording.
 
-The \SI{2500}{\square\meter} building consists of \SI{6}{} different levels, which are grouped into 3 floors (see fig. \ref{fig:apfingerprint}). 
+The \del{\SI{2500}{\square\meter}} building consists of \SI{6}{} different levels, which are grouped into 3 floors (see fig. \ref{fig:apfingerprint}). 
 Thus, the ceiling height is not constant over one floor and varies between \SI{2.6}{\meter} to \SI{3.6}{\meter}.
-In the middle of the building is an outdoor area, which is only accessible from one side. 
 While most of the exterior and ground level walls are made of massive stones, the floors above are half-timbered constructions.
-Due to different objects like exhibits, cabinets or signs not all positions within the building were walkable. 
+In the middle of the building is an outdoor area, which is only accessible from one side. 
+\add{The complete walkable indoor area for a visitor is \SI{2500}{\square\meter} in size. 
+Due to objects like exhibits, cabinets or signs not all positions within the building were freely accessible.}
 For the sake of simplicity we did not incorporate such knowledge into the floorplan. 
 Thus, the floorplan consists only of walls, ceilings, doors, windows and stairs.
 It was created using our 3D map editor software based on architectural drawings from the 1980s. 
+\add{The mesh is then created automatically, which only takes a few seconds to compute.}
 
+%wie haben wir die ap aufgehängt 
+\add{As described in section \ref{sec:wifi} we used \SI{42}{} WEMOS D1 mini to provide a \docWIFI{} infrastructure throughout the building.
+The distribution of the beacons on ground floor can be seen in fig. \ref{fig:apfingerprint} (black dots) as well as the references (fingerprints) for optimization. 
+The position of the beacons were chosen depending on available power sources. 
+We have tried to have at least two beacons in one room and a third beacon visible in an approximate radius of 10 meters.
+Due to the difficult architecture and the extremely thick walls of the museum, we decided on this procedure, which explains the rather unusual number of \SI{42}{} transmitters compared to modern buildings. 
+Another reason for the high number of beacons is that we did not want to analyze the quality of the Wi-Fi infrastructure for further improvements, as this can be a very time-consuming task. 
+In many areas of the building an improvement would not even be possible due to the lack of power sockets. 
+As an alternative, the beacons could also be operated using a battery, but we consider this approach less practicable, so we did not take this option. 
+The power sockets had different heights ranging from \SI{0.2}{\meter} to \SI{2.5}{\meter}. 
+So there were no prior requirements how to place a single beacon exactly and their position is thus similar to the sockets position. 
+Considering all the above, the beacons were placed more or less freely and to the best of our knowledge.} 
+
+\add{A very similar approach was chosen for placing the fingerprints. 
+The positions of the fingerprints are set within our 3D map editor software by simply dragging the fingerprinting icon on the desired position or by entering the position manually. 
+The reference points were placed every \SI{3}{\meter} to \SI{7}{\meter} from each other, however as can be seen in fig. \ref{fig:apfingerprint} not very accurately. 
+A perfect distance between the single points is not a crucial factor for the optimization and thus we consider such an accurate approach to be pointless.
+Furthermore, it is not easy to adopt the exact position to take the reference measurements in the building later on. 
+Of course, this could be done with appropriate hardware (e.g. laser-scanner), but again this costs a lot of time, which in our opinion does not justify a presumably increased accuracy of some decimeters.}
+
+\add{Summing up the above, the following initial steps are required to utilize our localization system to a building: 
+\begin{enumerate}
+	\item Acquiring a blueprint or architectural drawing of the building including at minimum the walls and stairs of the respective floors. 
+	\item Based on this 2D drawing, the floorplan is created using our 3D map editor (cf. fig. \ref{fig:museumMap}). This requires manual effort, comparable to software like Inkscape or FreeCAD. 
+	\item If necessary, creating or improving the Wi-Fi infrastructure by plugging in beacons to available power sockets and write all MAC-addresses into a whitelist.
+	%\item Store floorplan and whitelist of MAC-addresses onto the smartphone. 
+	\item Record the reference measurements based on the reference positions given in the floorplan. 
+	\item The Wi-Fi model is optimized using the previously obtained reference measurements.
+	\item The navigation mesh is created automatically based on the before created floorplan as can be seen in fig. \ref{fig:museumMapMesh}. 
+\end{enumerate}
+For the building considered within this work, we were able to perform this steps in less then \SI{160}{\minute} by a person, which is familiar with the system, and the janitor of the museum. 
+Step 1 and 2 were conducted off-site. 
+The blueprint was initially provided by the director of the museum as digital photography. 
+Creating the floorplan including walls and stairs took us approximately \SI{40}{\minute} and is then stored onto the smartphone after creation. 
+Adding knowledge like semantic information such as room numbers would of course take additional time.
+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. 
+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}. 
+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. 
+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.
+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...
+}
+
+%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.
 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. 
@@ -107,7 +157,7 @@ This is more difficult using the mesh and requires the handling of baricentric c
 %\commentByToni{Work in Progress... Irgendwie passt die Grafik nicht so wirklich. Im Gegensatz zum 2017 Paper würde ich gerne ein wenig über die geschätzten Positionen reden. Die Unterschiede zwischen Local und Global dabei. Warum machne Schätzungen gar so weit weg von der Realität sind und das es oft auch gar nicht so schlimm ist, falls das passiert. Tipps sind Willkommen. Vielleicht b) weglassen und in a einfach noch die fingerprint positionen mit rein. damit man ein gefühlt dafür bekommt wie viel wir in Vorleistung gehen müssen. An sich erkannt man ja dann das von "oben" das die optimierung manchmal gut und manchmal schlecht ist.}
 
 %wie viele ap sind es insgesamt?
-As described in section \ref{sec:wifi} we used \SI{42}{} WEMOS D1 mini to provide a \docWIFI{} infrastructure throughout the building.
+%As described in section \ref{sec:wifi} we used \SI{42}{} WEMOS D1 mini to provide a \docWIFI{} infrastructure throughout the building.
 Within all Wi-Fi observations, we only consider the beacons, which are identified by their well-known MAC address. 
 Other transmitters like smart TVs or smartphone hotspots are ignored as they might cause estimation errors.
 The references (fingerprints) we used to optimize the Wi-Fi models as well as the real position of the \docAPshort{}s (black dot) can be seen in fig. \ref{fig:apfingerprint} for ground level.
@@ -126,7 +176,7 @@ This allows a comparison with the optimized \docAPshort{} positions, what can al
 \end{figure}
 %Positionsfehler und wo?
 It illustrates the results of the global (blue) and the per-floor (orange) method for all \docAPshort{}'s installed to ground level. 
-The respective optimized positions $\mPosAPVec$ are connected by a grey line with the corresponding ground truth, providing the position error on the $xz$-plane.
+The respective optimized positions $\mPosAPVec$ are connected by a grey line with the corresponding ground truth, providing the position error on the \add{$xy$-plane}.
 The average distance error (3D) between the \docAPshort{}'s real position and the optimized ones is \SI{5.4}{\meter} ($\mu =$ \SI{5.1}{}) for the per-floor and \SI{4.8}{\meter} ($\mu =$ \SI{5.6}{}) for global strategy.
 However, it is easy to see that the results are better in some areas (green) than in others (red and purple).
 While the green \add{rectangle} encloses an area that has a high number of \docAPshort{}s with line-of-sight conditions, the \docAPshort{}s in red and purple are shielded by very thick stone walls and have a lower number of reference points with direct visual contact (cf. fig. \ref{fig:apfingerprint}).

tex_review/review/01_review.txt

@@ -4,6 +4,7 @@ The paper presents a smartphone-based localization system using a particle filte
 
 1. The authors mention that "a setup-time of under 120 min for the complete building" in abstract. But I don't find any context about the setup-time in the whole paper. How does the "under 120 min" calculate? How long does the navigation mesh for the whole buliding take? How long does the 42 WiFi beacon installation take? How does the measuremnet of the reference points take? etc. The authors should give the details.
 -> 120 museum has enough power outlets, requires it for the vitrinen... (am anfang von den experimenten was dazu schreiben)
+-> 120 was misleading. the 120 min war bezogen auf onside setup.. however, we have now addded how the system is setup and what step took what time. 
 
 2. The authors mention that the historical buildings "environments that are not built with localization in mind or do not provide any wireless infrastructure". But the WiFi beacons still need to be plugged into the power outlets. That means the whole building need 42 available power outlets. Does the WiFi beacon install in special position? I think the historical buildings don't have enough power outlets or the power outlets don't be available in a suitable position, maybe there is no power outlets at all in the whole corridor for example.