fixed commentsbyMarkus

tex_review/chapters/introduction.tex

@@ -55,19 +55,18 @@ During the here presented update, the following novel contributions will be pres
 \begin{itemize}
 	\item The pedestrian's movement is modelled in a more realistic way using a navigation mesh, generated from the building's floor plan. This only allows movements that are actually feasible, e.g. no walking through walls. Compared to the gridded-graph structure we used before \cite{Ebner-16}, the mesh allows continuous transitions and reduces the required storage space drastically.
 	\item To enabled more smooth floor changes, a threshold-based activity recognition using barometer and accelerometer readings is added to the state evaluation process of the particle filter. The method is able to distinguish between standing, walking, walking up and walking down. 
-	\item To address the problem of sample impoverishment in a wider scope, we present a simplification of our previous method \cite{Fetzer-17}. This reduces the overhead of adapting an existing system to the proposed method and allows to incorporate it as an independent component of the state transition of any approach using a general particle filter methodology. \commentByMarkus{Satzbau}
+	\item To address the problem of sample impoverishment in a wider scope, we present a simplification of our previous method \cite{Fetzer-17}. This reduces the overhead of adapting an existing system to the proposed method and allows to incorporate it directly to the state transition of any approach, using a general particle filter methodology.
 \end{itemize} 
 }
 %We then further omit time-consuming approaches like classic fingerprinting or measuring the exact positions of access points.
 %Instead we use a simple optimization scheme based on reference measurements to estimate a corresponding \docWIFI{} model.
 
 The goal of this work is to propose a fast to deploy \del{and low-cost} localization solution, that provides reasonable results in a high variety of situations.
-\add{However, many state-of-the-art solutions tend to be evaluated within office or faculty buildings, offering a modern environment and well described infrastructure.} \commentByMarkus{Brauchen wir hier Quellen um das zu belegen?}
+\add{However, many state-of-the-art solutions tend to be evaluated within office or faculty buildings, offering a modern environment and well described infrastructure.} 
 Consequently, we believe that by utilizing our localization approach to such a challenging scenario, it is possible to prove those characteristics. 
-\commentByMarkus{Statt challenging "a more realistic scenario"?!}
 \add{To initially set up the system we only require a blueprint to create the floor plan, some Wi-Fi infrastructure, without any further information about access point positions or parameters, and a smartphone carried by the pedestrian to be localized. 
 The existing Wi-Fi infrastructure can consist of the aforementioned Wi-Fi beacons and/or already existing access points. 
-The combination of both technologies is feasible, depending on the scenario and building.  \commentByMarkus{depending on was genau? Würde den Nebensatz einfach weg lassen}
+The combination of both technologies is feasible.
 Nevertheless, the museum considered in this work has no Wi-Fi infrastructure at all, not even a single access point. 
 Thus, we distributed a set of \SI{42}{beacons} throughout the complete building by simply plugging them into available power outlets. 
 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.}