eine neue runde eine neue reviewfahrt

tex_review/chapters/experiments.tex

@@ -30,7 +30,7 @@ Care was taken to have at least two beacons in each room and a third beacon visi
 Due to the difficult architecture and the extremely thick walls of the museum, we decided on this procedure, which explains the rather large 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 signal coverage 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. 
-To compensate that, battery powered beacons could be used but we consider this approach less practicable, so we did not take this option. 
+%To compensate that, battery powered beacons could be used but we consider this approach less practicable, so we did not take this option.
 The power sockets are located at different heights ranging from \SI{0.2}{\meter} to \SI{2.5}{\meter}. 
 Consequently, there were no prior requirements on how a single beacon should be placed exactly and its position is dictated by the socket's position. 
 Considering all the above, the beacons were placed more or less freely and to the best of our knowledge.} 
@@ -40,7 +40,7 @@ The positions of the fingerprints are set within our 3D map editor (see fig. \re
 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 necessarily accurate.
 As the optimization scheme does not require equally spaced reference points, doing so would result in superfluous effort.
 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 achieved with appropriate hardware (e.g. laser-scanner), but again, this requires more time and care, which in our opinion does not justify a presumably increased accuracy of some decimeters.}
+Of course, this could be achieved with appropriate hardware (e.g. laser-scanner), but again, this requires more time and care, which in our opinion does not justify a presumably increased accuracy of some decimeters.} \addy{Therefore, we accept the resulting inaccuracy between the (reference) position stored on the map and the actual position where the measurement took place, due to the enormous time saving.}
 
 \add{Summing up the above, the following initial steps are required to utilize our localization system in a building: 
 \begin{enumerate}
@@ -59,9 +59,10 @@ Creating the floor plan including walls and stairs took us approximately \SI{40}
 Adding knowledge like semantic information such as room numbers would of course take additional time.
 All remaining steps were performed on-site using our smartphone app for localization, which can be seen in fig. \ref{fig:yasmin}. 
 As the museum did not provide any Wi-Fi infrastructure, we installed \SI{42}{} beacons as explained above. 
-With the help 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 a Motorola Nexus 6 at the \SI{2.4}{GHz} Wi-Fi band. 
-This took \SI{85}{\minute}, as all measurements were conducted using the same smartphone.
+With the help 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.}
+\addy{After that, \SI{30}{} Wi-Fi scans were conducted and recorded for each of the \SI{133}{} reference points using a Motorola Nexus 6 at the \SI{2.4}{GHz} Wi-Fi band. This took approximately \SI{25}{\second} per point, as the Android OS restricts the scan rate.}
+%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 the \SI{2.4}{GHz} Wi-Fi band. 
+\add{In total, 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 negligible amount of time 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.
@@ -235,7 +236,7 @@ However, as the overall error suggests, this is not always an advantage, which w
 %warum ist die optimierung tdz. ganz gut?
 As mentioned above, some areas are heavily attenuated by big walls, what simply does not fit the used signal strength prediction model. 
 As discussed in section \ref{sec:relatedWork} and \ref{sec:wifi}, we only consider ceilings within the model to avoid computational expensive wall intersection-tests. 
-A far higher number of reference measurements in bad areas can therefore only increase the accuracy to a limited extent. 
+A far higher number of reference measurements in bad areas can therefore only increase the accuracy to a limited extent, \addy{whereas increasing the number of reference points could compensate for this, however requires additional setup time, what is then contrary to a fast deploy time.} 
 Nevertheless, by optimizing all parameters (\mPosAPVec{}, \mTXP{}, \mPLE{} and \mWAF{}) the system provides far better localization results compared to using the \docAPshort{}'s real positions with empirical values or even optimized values only for \mTXP{}, \mPLE{} and \mWAF{}. 
 The reason for this is obvious.
 The optimized parameters fit the (unrealistic) signal strength prediction model much better than the real ones and thus provide for a smaller error between measured RSSI and predicted RSSI. 
@@ -273,7 +274,7 @@ The 4 chosen walking paths can be seen in fig. \ref{fig:floorplan}.
 Walk 0 is \SI{152}{\meter} long and took about \SI{2.30}{\minute} to walk.
 Walk 1 has a length of \SI{223}{\meter} and Walk 2 a length of \SI{231}{\meter}, both required about \SI{6}{\minute} to walk. 
 Finally, walk 3 is \SI{310}{\meter} long and takes \SI{10}{\minute} to walk.
-All walks were carried out by 4 different male testers using either a Samsung Note 2, Google Pixel One or Motorola Nexus 6 for recording the measurements. 
+\addy{Each of the single walks was} carried out by 4 different male testers using either a Samsung Note 2, Google Pixel One or Motorola Nexus 6 for recording the measurements. 
 All in all, we recorded \SI{28}{} distinct measurement series, \SI{7}{} for each walk.
 The picked walks intentionally contain erroneous situations, in which many of the above treated problems occur. 
 \del{This allows us to discuss everything in detail.}