Update .gitea/workflows/build.yaml

.drone.yml

@@ -1,29 +0,0 @@
----
-kind: pipeline
-type: docker
-name: default
-
-steps:
-  - name: buildlatex
-    image: nareshkumarrao/texliveonfly
-    commands:
-      - texliveonfly Main.tex 
-      - biber main
-      - texliveonfly Main.tex
-      - biber main
-      - texliveonfly Main.tex
-  - name: gitea_release
-    image: plugins/gitea-release
-    settings:
-      base_url: https://git.nareshkumarrao.com
-      api_key:
-        from_secret: gitea_token
-      files: Main.pdf
-    when:
-      event: tag
-
-trigger:
-  event:
-    - push
-    - tag
-

.gitea/workflows/build.yaml

@@ -0,0 +1,26 @@
+name: Build and Release
+
+on:
+  push:
+    tags:
+      - 'v*'
+  schedule:
+    - cron: '@monthly'
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    container:
+      image: alpine:latest
+      options: --user root
+    steps:
+      - run: apk add --no-cache nodejs nix
+      - name: Checkout code
+        uses: actions/checkout@v4
+      - run: nix-channel --add https://nixos.org/channels/nixos-24.11 nixpkgs && nix-channel --update
+      - run: nix-shell -p biber tectonic --run "tectonic Main.tex"
+
+      - name: Create Release
+        uses: https://github.com/softprops/action-gh-release@v2
+        with:
+          files: Main.pdf

.gitlab-ci.yml

@@ -1,8 +0,0 @@
-build-job:
-        image: texlive/texlive:latest
-        stage: build
-        script:
-                - make
-        tags:
-                - docker
-

.textidote

@@ -1,3 +1,3 @@
 --output html
---dict dico.txt
+--dict dict.txt
 --check en Main.tex

0-Cover/Cover.tex

@@ -3,7 +3,7 @@
 		\vspace*{1cm}
 		\begin{Huge}
 		\textbf{Measuring Bulk Material Flow using Commercially-Available LIDAR Sensors}\par
-		\textbf{---First Draft---}\par
+%		\textbf{---Final Draft---}\par
 		\end{Huge}
 		\vfill
 		\large
@@ -20,8 +20,8 @@
 		\vfill
 		\normalsize
 		\begin{align*}
-		&\text{1. Examiner: Prof. Dr.-Ing M. Protogerakis}\\
-		&\text{2. Examiner: Prof. Dr.-Ing R. Beck}
+		&\text{1. Examiner: Prof. Dr.-Ing. M. Protogerakis}\\
+		&\text{2. Examiner: Prof. Dr.-Ing. R. Beck}
 		\end{align*}
 		\vfill
 		Düsseldorf\\

1-Introduction/Introduction.tex

@@ -1,61 +1,64 @@
 \chapter{Introduction}\label{chap:intro}
 
+This chapter lays out an overview of this project and thesis. The reasoning and motivation for exploring the topic will be elaborated, followed by the parameters of the project. Finally, the chapter closes with an overview of the various stages of development of this project, from conception to completion.
+
 \section{Motivation}
 
 \subsection{Transportation of Bulk Material}
 
-It is necessary in several industries, including those of mining and manufacturing, to transport bulk material from one location to another. In mining, it may be sand or gravel. In manufacturing, it may be powdered chemicals\cite{protogerakisInterview2022}.
+It is necessary in several industries \cite{protogerakisInterview2022}, including those of mining and manufacturing, to transport bulk material from one location to another. In mining, it may be sand or gravel. In manufacturing, it may be powdered chemicals. 
 
 The transportation of this bulk material typically involves the use of a conveyor belt. These conveyors are specifically designed for the efficient transport of bulk material.
 
 \subsection{Measuring Bulk Material Flow}
 
-\begin{wrapfigure}[12]{R}{0.5\textwidth}
-	\centering
-    \includegraphics[width=0.45\textwidth]{photographs/beltscale}
-    \caption{A conventional electronic belt scale.}
-\end{wrapfigure}
-
 This transportation of bulk material flow introduces the need to accurately measure the rate at which the material is flowing. This is essential for various tasks such as keeping track of inventory or for control systems. Knowing when a belt is overloaded, running empty or broken is also an important safety concern. This work deals with the specific challenge of measuring bulk material flow on a conveyor.
 
 \subsection{Conventional Belt Scales}
 
-The conventional method of measuring bulk material flow in use in the industry today is the electronic belt scale. These scales use load cells to translate compression and tension into electrical signals. These signals representing weight may then be converted into measurements of volume.
+The conventional method of measuring bulk material flow in use in the industry today is the electronic belt scale---as shown in \autoref{fig:beltscale}. These scales use load cells to translate compression and tension into electrical signals. These signals representing weight may then be converted into measurements of volume.
 
 These electronic belt scales are robust and proven in the field. However, there are also downsides with this approach.
 
 \begin{enumerate}
 \item High unit costs as well as higher retrofitting costs
 \item Humidity and moisture content of the material may introduce significant errors which may not be easily compensated
-\item Vibration from transport and loading introduces noise into the measurements\cite{tomobe2006}
+\item Vibration from transport and loading introduces noise into the measurements \cite{tomobe2006}
 \end{enumerate}
 
-\section{Aims of this Work}
+\begin{figure}[h]
+	\centering
+    \includegraphics[width=0.75\textwidth]{photographs/beltscale}
+    \caption{A conventional electronic belt scale.}
+    \label{fig:beltscale}
+\end{figure}
+
+\section{Aims of this Work}\label{sec:aims}
 
 %\subsection{Research Question}
 The central \textbf{research question} that is investigated in this work is:
 
-\textit{How can a cheaper and easier to install measurement system for bulk material flow on a conveyor belt be designed?}
+\textit{How can a cheaper and easier-to-install measurement system for bulk material flow on a conveyor belt be designed?}
 
 \subsection{Use of Commercially-Available Products}\label{sec:useOfCommerciallyAvailableProducts}
 
-As given by the research question above, one of the central parameters is the question of cost. Since the cost of industrial equipment can be many multiples of the cost of commercially available products, studying alternatives becomes attractive.
+As given by the research question above, one of the central parameters is the question of cost. Since the cost of industrial equipment can be far greater than the cost of commercially available products, studying alternatives becomes attractive.
  
-As an example, the cost price of the Intel RealSense L515 used in this project was €380\footnote{Due to Intel announcing that they are discontinuing their LIDAR sensor series, the price of this particular product has risen up to €570 as of January 2022.}, whereas the SICK LM400 used by Fojtik\cite{fojtik2014} can cost upwards of €4000\footnote{This price is an aggregate estimate based on multiple online merchants as of January 2022}.
+As an example, the cost price of the Intel RealSense L515 used in this project was \euro{380}\footnote{Due to Intel announcing that they are discontinuing their LIDAR sensor series, the price of this particular product has risen up to \euro{570} as of January 2022.}, whereas the SICK LM400 used by Fojtik \cite{fojtik2014} can cost upwards of \euro{4000}\footnote{This price is an aggregate estimate based on multiple online merchants as of January 2022}.
 
 \subsection{Use of the LIDAR Sensor}
 
 The usage of the LIDAR sensor was implemented in order to fulfill the second requirement of the research question, namely that the solution must be easier to install than other conventional solutions.
 
-As is discussed in the following section on design, the LIDAR sensor was selected primarily because it is a contactless sensor. This means that installation can be carried out with little to no adjustments to the existing conveyor belt system. The LIDAR sensor must simply be suitably positioned in order to gather and deliver data.
+As will be discussed in the following section on design, the LIDAR sensor was selected primarily because it is a contactless sensor. This means that installation can be carried out with little to no adjustments to the existing conveyor belt system. The LIDAR sensor must simply be suitably positioned in order to gather and deliver data.
 
 \subsection{Requirements \& Restrictions}
 
-Besides fulfilling the research question, the design solution should fulfill the following restrictions and requirements as well.
+Besides fulfilling the research question, the design solution should meet the following criteria as well.
 
 \begin{itemize}
-\item \textbf{Industrial Robustness} - The final product should be able to withstand the harsh environments that it would likely be installed in, i.e. in a gravel quarry. This means the product must be adequately housed and protected from the environment, against vibrations and shocks.
-\item \textbf{Industrial Connectivity} - The product should be able to interface with existing industrial networks, i.e. using Industrial Ethernet.
+\item \textbf{Industrial Robustness} - The final product should be able to withstand the harsh environments that it would likely be installed in, i.e.\ in a gravel quarry. This means the product must be adequately housed and protected from the environment, against vibrations and shocks.
+\item \textbf{Industrial Connectivity} - The product should be able to interface with existing industrial networks, i.e.\ using Industrial Ethernet.
 \item \textbf{Real-Time Ability} - The product should ideally deliver values in Real-Time through the required interface. This means not only a high enough data resolution but also high determinism.
 \item \textbf{Remote Control} - The product should be able to be configured and diagnosed remotely, in order to prioritize simplicity of installation and maintenance.
 \end{itemize}
@@ -90,9 +93,9 @@ After being able to successfully interface with the sensor, a proof-of-concept s
 \end{itemize}
 
 \subsection{Laboratory Prototype}
-Once the proof-of-concept software was stable, the setup was moved into a laboratory environment in order to further develop the main functionalities of the prototype. Among the functionalities that were developed:
+Once the proof-of-concept software was stable, the setup was moved into a laboratory environment in order to further develop the main functionalities of the prototype. Among the functionalities that were developed were:
 \begin{itemize}
-\item Remotely acquire the raw sensor data over the network
+\item Remote acquisition the raw sensor data over the network
 \item Image preparation (offset, rotation, skew)
 \item Cross-correlation methods to determine belt velocity
 \item Profinet interface to deliver processed data

2-StateOfTheArt/StateOfTheArt.tex

@@ -1,16 +1,22 @@
 \chapter{State of the Art}
 
-The interest in the implementation of optical methods for the purposes of measuring bulk material is not novel. The reasoning is clear: conventional methods are intrusive and costly. Being a non-contact, non-intrusive approach, makes any sort of optical solution to the measurement problem very desirable.
+The conventional methods of measuring the mass or volume flow of bulk materials \cite{protogerakisInterview2022} are using so-called \textit{belt scales} or \textit{belt weighers}. These typically either employ the gravimetric method or nuclear method in order to determine the mass or volume flow of bulk materials.
 
-As early as 1997, Green et al.\ were already experimenting with non-contact methods to calculate mass flow rates. In that time, they resorted to using electrodynamic sensors. Although a far cry from the resolution afforded by contemporary sensors, Green et al.\ and their electrodynamic sensors demonstrated the potential of non-contact sensing for bulk materials\cite{green1997}.
+As already detailed in \autoref{chap:intro}, gravimetric belt scales use load cells to transform the compression due to the weight of the belt, into electrical signals.
 
-In 2014, Fojtik released his paper on using laser scanning to measure the volume of bulk material on a conveyor belt. Fojtik focused on the measurement of wood chips, which required special consideration to the volume fluctuations due to humidity\cite{fojtik2014}. 
+Nuclear belt scales \cite{elias1980} function principally by measuring gamma ray attenuation through the bulk material. While these type of scales have their advantages over the gravimetric conventional method, such as ease-of-installation and calibration, there are also other severe disadvantages. Most importantly, the handling of radioactive products must be carried out by certified personnel. Secondly, the chemical composition of the bulk material must also be homogeneous. 
 
-Independently, Zeng et al.\ too released their paper on the use of laser scanning for measuring the volume flow of bulk material.\cite{zeng2015} The focus of their paper was using these technologies to increase energy efficiency.
+The interest in the implementation of \textbf{optical methods} for the purposes of measuring bulk material is not novel. The reasoning is clear: conventional methods are intrusive and costly. A non-contact, non-intrusive approach makes any sort of optical solution to the measurement problem very desirable.
 
-Although they differed slightly in their precise approaches, both Fojtik and Zeng et al.\ used the same fundamental principle to determining volume flow, namely the derivation of the cross-sectional area of material based on the difference between an empty and laden belt. Both of them also are similar in their use of SICK LMS industrial laser scanners.
+As early as 1997, Green et al.\ \cite{green1997} were already experimenting with non-contact methods to calculate mass flow rates. In that time, they resorted to using electrodynamic sensors. These electrodynamic sensors were used to estimate both velocity and concentration, which in turn were used to derive mass flow rates. They also used a cross-correlation method to determine material velocity. Although a far cry from the resolution afforded by contemporary sensors, Green et al.\ and their electrodynamic sensors demonstrated the potential of non-contact sensing for bulk materials.
 
-Both Min et al.\ in 2020\cite{min2020}, and Qiao et al.\ in 2021\cite{qiao2022} too have published their analyses and results on solving this problem. They both take novel approaches, however, using not only laser scanning but a hybrid solution involving regular optical imaging to supplement the analysis of the material surface. They both also attempt to implement more advanced mathematical models, using 3D reconstruction and neural networks.
+In 2014, Fojtik \cite{fojtik2014} released his paper on using laser scanning to measure the volume of bulk material on a conveyor belt. Fojtik focused on the measurement of wood chips, which required special consideration to the volume fluctuations due to humidity.
+
+Independently, Zeng et al.\ \cite{zeng2015} too released their paper on the use of laser scanning for measuring the volume flow of bulk material. The focus of their paper was using these technologies to increase energy efficiency. In that paper, they claim that non-contact methods of measuring the volume flow of bulk materials increased energy efficiency by up to \SI{30}{\percent} and reduced maintenance costs by up to \SI{20}{\percent}.
+
+Although they differed slightly in their precise approaches, both Fojtik and Zeng et al.\ used the same fundamental principle to determine volume flow, namely the derivation of the cross-sectional area of material based on the difference between an empty and laden belt. Both of them also are similar in their use of SICK LMS industrial laser scanners.
+
+Both Min et al.\ in 2020 \cite{min2020}, and Qiao et al.\ in 2021 \cite{qiao2022} too have published their analyses and results on solving this problem. They both take novel approaches, however, using not only laser scanning but a hybrid solution involving regular optical imaging to supplement the analysis of the material surface. They both also attempt to implement more advanced mathematical models, using 3D reconstruction and neural networks.
 
 As shown by the papers above, this work is not novel in its use of optical methods to solve the problem of measuring bulk material volume flow. This project does set itself apart, however, by
 \begin{enumerate*}[label=\alph*)]

3-Design/Design.tex

@@ -9,6 +9,18 @@ The analysis of volume flow can be broken down into two fundamental operations t
 \end{itemize}
 
 \subsection{Cross-Sectional Area}
+
+The methodology used in order to analyze the cross-sectional area of the material flow is \textbf{geometric analysis}. Simply put, the geometry of a laden belt is compared with that of an empty belt. The resulting difference in area is that of the material itself.
+
+As shown in \autoref{fig:conveyor_top}, the LIDAR sensor returns a 2-dimensional image with the value of each pixel representing depth data. This 2-dimensional image can then be separated into slices. A slice represents the depth data of a single dimension, in this case, the crosswise dimension of the belt.
+
+\begin{figure}[h]
+\centering
+\includegraphics[width=0.75\textwidth]{design/conveyor_top}
+\caption{Graphical depiction of the LIDAR sensor image. The slice is a one-dimensional extract of the sensor image crosswise over the belt.}
+\label{fig:conveyor_top}
+\end{figure}
+
 \begin{figure}[h]
 	\centering
     \includegraphics[width=0.6\textwidth]{design/cross_analysis_new}
@@ -16,35 +28,28 @@ The analysis of volume flow can be broken down into two fundamental operations t
     \label{fig:cross_analysis}
 \end{figure}
 
-The methodology used in order to analyze the cross-sectional area of the material flow is \textbf{geometric analysis}. Simply put, the geometry of a laden belt is compared with that of an empty belt. The resulting difference in area is that of the material itself.
-
-In order to accomplish this analysis, a horizontal slice of the sensor data is used. The slice represents the depth data of a single dimension, in this case, the crosswise dimension of the belt.
-
 During calibration, the empty belt is used to fit the polynomial belt curve $f(x)$. The fitting of this nth-degree polynomial is done with the least-squares method.
 
+After calibration, the current slice curve $g(x)$ can be used to obtain the Cross-Sectional Area $A_C$ as shown in \autoref{eq:cross_area} and \autoref{fig:cross_analysis}. 
+
 \begin{equation} 
   A_C = \int^{x_b}_{x_a}\left[ g(x) - f(x) \right] dx \label{eq:cross_area}
 \end{equation}
 
-
-After calibration, the current slice curve $g(x)$ can be used to obtain the Cross-Sectional Area as shown in \autoref{eq:cross_area}.
-
 \subsubsection{Further Considerations}
 The accuracy of the computed cross-sectional area depends primarily on the accuracy of the depth data as well the frame rate of the sensor.
 
+\begin{minipage}{\textwidth}
 However, further operations may be implemented in order to increase accuracy, such as:
 \begin{itemize}
 \item Computing the cross-sectional area from multiple slices of each frame and averaging these
 \item Computing the average cross-sectional area between frames, in order to create a smoother---and possibly more accurate---estimation of the volume flow
 \end{itemize}
+\end{minipage}
 
 It is important to note though, that the implementation of further operations may exhaust the processing capabilities of the platform. Therefore, a crucial balance must be struck between performance and accuracy.
 
-\begin{figure}[h]
-\centering
-\includegraphics[width=0.75\textwidth]{design/conveyor_top}
-\caption{Graphical depiction of the LIDAR sensor image. The slice is a one-dimensional extract of the sensor image crosswise over the belt.}
-\end{figure}
+Furthermore, this method of estimating the cross-sectional area does not take into account the warping of the belt when it is laden with material. This algorithm operates under the assumption that the error introduced by warping is negligible. This error can further be reduced by placing the sensor strategically over sections of the belt which are supported by struts. The ability to re-calibrate the belt curve $f(x)$ regularly will also help reducing this error.
 
 \subsection{Belt Velocity}
 Conventional belt scales use some form of a rotary encoder in order to measure the belt velocity. This is---however accurate---only an approximation of the velocity of the material flow itself, since material velocity may deviate from belt velocity depending on environmental or material conditions.
@@ -55,15 +60,27 @@ The fundamental operation being used in the following methods in order to determ
 
 In the case of this project, given the known interval between two consecutive signals---i.e.\ the frame rate---it is possible to express this delay in the form of a physical displacement, in meters.
 
-The different analytic methods used in this project differ only by which data is selected to represent the signal during cross-correlation. The algorithm of calculating the cross-correlation itself remains the same.
+The various analytic methods used in this project differ only by which data is selected to represent the signal during cross-correlation. The algorithm of calculating the cross-correlation itself remains the same.
+
+Equation \ref{eq:cross_corr} shows how the cross-correlation $r$ between two signals $A$ and $B$ of lengths $n$ may be calculated by multiplying each element $i$ together. This is done for each possible delay $d$ value. The maximum value of the correlation $r$ corresponds to the most likely value of $d$.
 
 \begin{equation}
 r(d) = \sum_{i=1}^{n} A_i \cdot B_{i+d} \label{eq:cross_corr}
 \end{equation}
 
-Equation \ref{eq:cross_corr} shows how the cross-correlation $r$ between two signals $A$ and $B$ of lengths $n$ may be calculated by multiplying each element $i$ together. This is done for each possible delay $d$ value. The maximum value of the correlation $r$ corresponds to the most likely value of $d$.
-
 \subsubsection{Chosen Method - Statistical Method}
+This method was developed as an aggregate of the previously attempted methods, improving on and solving issues earlier iterations had. It is therefore simply the most successful iteration.
+
+The statistical method carries out the following operations:
+\begin{enumerate}
+\item A user-provided area of interest is cropped out of the entire sensor frame. This is done to isolate only the most relevant and data-dense regions, as well as to eliminate error from static elements as much as possible.
+\item This subset of the frame is then divided into one-dimensional vertical strips.
+\item For each of the strips, the cross-correlation displacement is calculated.
+\item With the of displacement values for each strip, statistical outlier values are removed and a mean displacement is calculated.
+\item This mean displacement in pixels, together with camera frame geometry, is used to calculate the physical displacement in meters.
+\end{enumerate}
+
+The use of this statistical approach using multiple vertical strips---see \autoref{fig:conveyor_xcorr}---is very similar to directly using 2-dimensional correlation, however it attempts to solve a significant problem with the 2-dimensional cross-correlation method.
 
 \begin{figure}[h]
 \centering
@@ -72,19 +89,6 @@ Equation \ref{eq:cross_corr} shows how the cross-correlation $r$ between two sig
 \label{fig:conveyor_xcorr}
 \end{figure}
 
-This method was developed as an aggregate of the previously attempted methods, improving on and solving issues earlier iterations had. It is therefore simply the most successful iteration.
-
-The statistical method carries out the following operations:
-\begin{enumerate}
-\item A user-provided area of interest is cropped out of the entire sensor frame. This is done to isolate only the most relevant and data-dense regions, as well as to eliminate error from static elements as much as possible.
-\item This subset of the frame is then divided into one-dimensional vertical strips
-\item For each of the strips, the cross-correlation displacement is calculated.
-\item With the of displacement values for each strip, statistical outlier values are removed and a mean displacement is calculated
-\item This mean displacement in pixels, together with camera frame geometry, is used to calculate the physical displacement in meters.
-\end{enumerate}
-
-The use of this statistical approach using multiple vertical strips---see \autoref{fig:conveyor_xcorr}---is very similar to directly using 2-dimensional correlation, however it attempts to solve a significant problem with the 2-dimensional cross-correlation method.
-
 Since a 2-dimension cross-correlation would simultaneously consider the entire area of interest, any static elements in the frame would highly influence the results of the correlation, causing it to always be close to zero. This introduces a high error and variability in the result.
 
 This statistical approach allows us to discard outlier values---such as values close to zero---and retain only those slices which do not contain any static elements.
@@ -95,7 +99,7 @@ Before arriving at the statistical method described above, multiple iterations o
 
 Firstly, as already mentioned above, the \textbf{2-dimensional cross-correlation}. This method produces robust values and is less computationally complex than the statistical approach, however it is significantly more sensitive to static elements. This introduces many challenges since static elements may not be entirely avoided, either on the belt, or on the sensor itself.
 
-The other alternative method called the \textbf{topographical method} is much less computationally expensive, since it only runs one cycle of the cross-correlation algorithm per frame.
+The other alternative method, called the \textbf{topographical method}, is much less computationally expensive, since it only runs one cycle of the cross-correlation algorithm per frame.
 
 The topographical approach works in the following manner. The values within each \textbf{crosswise} slice are summed. This reduces the 2-dimensional sensor data into a 1-dimensional representation which is called the \textit{topography}. This topography can be used as the signal for cross-correlation.
 
@@ -114,8 +118,22 @@ The volume of material that has passed the sensor per frame $V_F$, can be calcul
   % \frac{1}{f} \label{eq:volavg}
 \end{equation}
 
+\subsection{Accuracy}
 
-\section{Phases of Development}
+The accuracy of the system is limited primarily by the framerate of the sensor.
+
+Figure \ref{eq:accuracyupperlimit} shows the theoretical maximum accuracy for a simple single line-scanner method of determining volume. Thus, for the targeted framerate of 30 FPS, the theoretical maximum accuracy of this method is limited to \SI{3.3}{\percent}.
+
+\begin{equation}\label{eq:accuracyupperlimit}
+\text{Accuracy Upper Limit} = \frac{1}{f} \cdot \SI{100}{\percent}
+\end{equation}
+
+Introducing multiple line-scans per frame would proportionally reduce this upper limit, at the cost of increased computational complexity.
+
+The various manufacturers of conventional belt scales have claims of accuracy between \SI{0.5}{\percent} and \SI{2}{\percent}.
+
+
+\section{Phases of Development}\label{sec:developmentphases}
 The following phases of development are not grouped chronologically over the span of the project schedule, rather into conceptual groups.
 
 \subsection{Preparing Development and Build Environment}
@@ -124,10 +142,10 @@ Setting up the development environment for this project was a non-trivial task,
 The Raspberry Pi 4 Model B used in this project was delivered with a Quad Core Cortex-A72 64-bit SOC. However, a 32-bit kernel OS was used in this project, due to the netHAT drivers being delivered as 32-bit compiled binaries.
 
 \subsubsection{Intel RealSense SDK}
-The Intel RealSense SDK, or librealsense, is a cross-platform library provided by Intel for use with their RealSense devices. Pre-compiled binaries for 32-bit ARM were not provided, and therefore must be compiled\cite{realsense_git}.
+The Intel RealSense SDK, or librealsense, is a cross-platform library provided by Intel for use with their RealSense devices. Pre-compiled binaries for 32-bit ARM were not provided, and therefore must be compiled \cite{realsense_git}.
 
 \subsubsection{ZeroMQ}
-ZeroMQ is a lightweight asynchronous messaging library that extends the traditional socket interfaces\cite{zeromq_git}. In this project, ZeroMQ was used in order to:
+ZeroMQ is a lightweight asynchronous messaging library that extends the traditional socket interfaces \cite{zeromq_git}. In this project, ZeroMQ was used in order to:
 \begin{itemize}
 \item Broadcast raw sensor data to remote controllers using a publish/subscribe model
 \item Exchange configuration parameters between the remote controller and the local processor using a request/reply model
@@ -145,15 +163,15 @@ ZeroMQ was chosen to provide the aforementioned functionalities for the followin
 \subsubsection{Real-Time Kernel Patch}
 Traditionally, the Linux kernel only allows one process to preempt another process in specific circumstances. This means, that even a high-priority thread may not preempt kernel code until the kernel explicitly yields control.
 
-This is particularly disadvantageous for any operations requiring real-time performance. In order to circumvent this, the \verb|CONFIG_PREEMPT_RT| Kernel Patch is used in order to allow kernel code to be preempted\cite{rtwiki}.
+This is particularly disadvantageous for any operations requiring real-time performance. In order to circumvent this, the \verb|CONFIG_PREEMPT_RT| Kernel Patch is used in order to allow kernel code to be preempted \cite{rtwiki}.
 
 In the case of this project, this means that the local processor can process and deliver data in a more deterministic fashion.
 
 \subsubsection{GUI with Qt}
-The Qt GUI framework was used in order to create a GUI for the remote controller. This allowed for the sensor data to be more easily calibrated and aligned, as well as providing a consistent interface for end-user configuration. Qt was chosen for its ease of use, as well as its ability to be compiled cross-platform\cite{qtWebsite}.
+The Qt GUI framework \cite{qtWebsite} was used in order to create a GUI for the remote controller. This allowed for the sensor data to be more easily calibrated and aligned, as well as providing a consistent interface for end-user configuration. Qt was chosen for its ease of use, as well as its ability to be compiled cross-platform.
 
 \subsection{Development of Main Functionality}
-At this stage of the design process, the functionality that is fundamental to the principle operation described earlier are developed. These functions include:
+At this stage of the design process, the functionality that is fundamental to the principle operation described earlier was developed. These functions include:
 \begin{itemize}
 \item Transmission of raw sensor data
 \item Calibration of sensor data
@@ -186,7 +204,16 @@ See \autoref{chap:validation} for elaboration and results of each of the testing
 
 \section{Components}\label{sec:componenets}
 
+As already touched upon in \autoref{sec:aims}, the components used in this project were chosen mainly for their commercial availability and low cost. This section will elaborate more on the decision to select these specific components.
+
+The cost for each of these components are listed at the end of this section in \autoref{table:cost}.
+
 \textbf{Raspberry Pi 4 Model B}\nopagebreak
+
+The Raspberry Pi was chosen as the computation platform primarily for its widespread use in IoT and IIoT, low cost and commercial availability. It also supports the Linux kernel and operating system which greatly eases the software development and deployment process. 
+
+As shown in \autoref{tab:rpi}, the Quad-Core ARM processor as well as 2 GB memory capacity provide ample performance for the intended computation. The wireless networking capability of the Raspberry Pi makes it an ideal candidate for an IoT product.
+
 \begin{table}[H]
 \centering
 \begin{tabularx}{0.75\textwidth}{| c | >{\centering\arraybackslash}X |}
@@ -208,11 +235,17 @@ Storage & Micro-SD card slot \\
 Operational Temperature & \SI{0}{\celsius} to \SI{50}{\celsius} \\
 \hline
 \end{tabularx}
-\caption{The relevant technical specifications of the Raspberry Pi 4 Model B used in this project\cite{rpiSpecs}.}
+\caption{The relevant technical specifications of the Raspberry Pi 4 Model B used in this project \cite{rpiSpecs}.}
+\label{tab:rpi}
 \end{table}
 
 
 \textbf{Intel RealSense L515}\nopagebreak
+
+The Intel Realsense L515 was also chosen primarily for its low cost. However, the open-source and Linux-friendly nature of Intel's RealSense SDK also make it an ideal choice to pair with the Raspberry Pi. The small form-factor of the sensor would also allow a final product size that would be compact and easy to install.
+
+\autoref{table:l515} provides an overview of the specifications of the RealSense L515 sensor. 
+
 \begin{table}[H]
 \centering
 \begin{tabularx}{0.75\textwidth}{ >{\centering\arraybackslash}X  | >{\centering\arraybackslash}X | >{\centering\arraybackslash}X |}
@@ -241,10 +274,18 @@ Operational Temperature & \SI{0}{\celsius} to \SI{50}{\celsius} \\
 \multicolumn{1}{|c|}{} & \multicolumn{2}{c|}{2x M3 Mounting Point}\\
 \hline
 \end{tabularx}
-\caption{The relevant technical specifications of the Intel RealSense L515 used in this project\cite{realsenseDatasheet}.}
+\caption{The relevant technical specifications of the Intel RealSense L515 used in this project \cite{realsenseDatasheet}.}
+\label{table:l515}
 \end{table}
 
 \textbf{netHAT}\nopagebreak
+
+The netHAT by Hilscher provides a simple-to-use Industrial Ethernet interface for the Raspberry Pi. Through the Raspberry Pi HAT standard, the netHAT is easily installed on the GPIO pins of the Raspberry Pi.
+
+The drivers---called CIFX---and API library provided--called libCIFX---provide a simple way to interface with Industrial Ethernet networks from software. Section \ref{sec:softarch} shows how CIFX was integrated into the rest of the software architecture.
+
+\autoref{table:nethat} gives an overview of the capabilities and specifications of the netHAT.
+
 \begin{table}[H]
 \centering
 \begin{tabularx}{0.75\textwidth}{ | c | >{\centering\arraybackslash}X | } \hline
@@ -253,31 +294,28 @@ Memory & 4MB Quad SPI Flash \\ \hline
 Interface & SPI up to 125MHz \\ \hline
 Network & 2x Ethernet 100 BASE-TX \\ \hline
 \end{tabularx}
-\caption{The relevant technical specifications of the Hilscher netHat\cite{nethatHilscher}.}
+\caption{The relevant technical specifications of the Hilscher netHat \cite{nethatHilscher}.}
+\label{table:nethat}
 \end{table}
 
-\subsection{Cost Breakdown}
+\textbf{Cost Breakdown}\nopagebreak
+
+\autoref{table:cost} lists the individual costs of each of the components, and their total. This total is not reflective of the final cost of the completed product as it does not yet include costing for the housing, wiring and other installation costs.
+
 \begin{table}[H]
 \centering
 \begin{tabular}{| c | c |}
 \hline
-Intel RealSense L515 & €380\tablefootnote{The cost has since increased to €570 as of January 2022.}\\ \hline
-Raspberry Pi Model 4 B & €84 \\ \hline
-netHAT & €69 \\ \hline
-\textbf{Total} & \textbf{€553\tablefootnote{Due to a malfunctioning unit, a new sensor was purchased, bringing the total cost of development to around €1120.}} \\ \hline
+Intel RealSense L515 & \euro{380}\tablefootnote{The cost has since increased to \euro{570} as of January 2022.}\\ \hline
+Raspberry Pi Model 4 B & \euro{84} \\ \hline
+netHAT & \euro{69} \\ \hline
+\textbf{Total} & \textbf{\euro{553}\tablefootnote{Due to a malfunctioning unit, a new sensor was purchased, bringing the total cost of development to around \euro{1120}.}} \\ \hline
 \end{tabular}
 \caption{Breakdown of the costs used in the development of this project.}
 \label{table:cost}
 \end{table}
 
 \section{Process Overview}
-\begin{figure}[h]
-	\centering
-	\includegraphics[width=0.8\textwidth]{./design/ProcessOverview}
-	\caption{Overview of the communication and processing process between the remote controller and the local processor.}
-	\label{fig:processoverview}
-\end{figure}
-
 With the objective of creating a marketable commercial product in mind, the process flow was designed for ease-of-use and ease-of-configuration for the end-user. This is the justification for implementing a remote controller that allows the setup to be remotely configured once installed.
 
 While \autoref{fig:processoverview} gives a brief overview of the interrelationship of the remote and local sides in the complete process, it is here further elaborated:
@@ -298,33 +336,35 @@ While \autoref{fig:processoverview} gives a brief overview of the interrelations
 
 \end{enumerate}
 
-\section{Software Architecture}\label{sec:softarch}
-\begin{figure}[h]
+\begin{figure}[H]
 	\centering
-	\includegraphics[width=0.7\textwidth]{./design/SoftwareArchitecture}
-	\caption{Overview of the interactions between the various software components and their communication.}
+	\includegraphics[width=0.8\textwidth]{./design/ProcessOverview}
+	\caption{Overview of the communication and processing process between the remote controller and the local processor.}
+	\label{fig:processoverview}
 \end{figure}
 
-The software developed in this project consists of two separate but tightly interconnected parts, namely:
+\section{Software Architecture}\label{sec:softarch}
+
+The software architecture developed in this project---see \autoref{fig:SoftwareArchitecture}---consists of two separate but tightly interconnected parts, namely:
 \begin{itemize}
 \item \textbf{FlowPi:} The local processing software that runs on the Raspberry Pi, and
 \item \textbf{FlowRemote: } The remote control software that is meant to run on an external PC for configuration purposes
 \end{itemize}
 
-\subsection{Development Language Choice}
-The software is written in \cpp\ for compatibility and performance reasons. All the device drivers provide libraries in either \clang\ or \cpp, while some drivers such as the CIFX library for the netHAT are only provided in \clang. 
-
-The topic of performance between languages and systems is one of much-heated debate, however \cpp\ was chosen for this project due to the ability to program comfortably in a higher-level language, while having the ability to \textit{\enquote{drop down}} into \clang. The \clang\ Programming Language is often the benchmark for higher-level programming languages when programming for Real-Time Systems due to its predictability and the ability to run operations with few layers of abstraction on memory directly\cite{pizlo2010}. 
-
-Furthermore, since the scale of the processing unit of the program is relatively small, the benefits that come from using a higher-level programming language---such as increased productivity, organization, and re-usability\cite{pizlo2010}---are not strictly necessary.
-
 \begin{figure}[h]
 	\centering
-    \includegraphics[width=0.8\textwidth]{./design/ProcessingLibrary}
-    \caption{Representation of the how the processing unit is called by different components of the program.}
-    \label{fig:processinglib}
+	\includegraphics[width=0.7\textwidth]{./design/SoftwareArchitecture}
+	\caption{Overview of the interactions between the various software components and their communication.}
+	\label{fig:SoftwareArchitecture}
 \end{figure}
 
+\subsection{Development Language Choice}
+The software is written in \cpp\ for compatibility and performance reasons. All the device drivers provide libraries in either \clang\ or \cpp, while some drivers such as the library for the netHAT---called CIFX---are only provided in \clang. 
+
+The topic of performance between languages and systems is one of heated debate, however \cpp\ was chosen for this project due to the ability to program comfortably in a higher-level language, while having the ability to \textit{\enquote{drop down}} into \clang. The \clang\ Programming Language is often the benchmark for higher-level programming languages when programming for Real-Time Systems due to its predictability and the ability to run operations with few layers of abstraction on memory directly \cite{pizlo2010}. 
+
+Furthermore, since the scale of the processing unit of the program is relatively small, the benefits that come from using a higher-level programming language---such as increased productivity, organization, and re-usability \cite{pizlo2010}---are not strictly necessary.
+
 As shown in \autoref{fig:processinglib}, the main functionality of the processing unit includes:
 
 \begin{itemize}
@@ -333,10 +373,21 @@ As shown in \autoref{fig:processinglib}, the main functionality of the processin
 \item Cross-Correlation
 \end{itemize}
 
+\begin{figure}[h]
+	\centering
+    \includegraphics[width=0.8\textwidth]{./design/ProcessingLibrary}
+    \caption{Representation of the how the processing unit is called by different components of the program.}
+    \label{fig:processinglib}
+\end{figure}
+
 These are implemented in \clang\ as much as possible. This is then encapsulated by a \cpp\ wrapper. This provides ease-of-use on the remote side, where processing is not real-time critical, while still allowing the local side to directly call the \clang\ processing functions.
 
 \subsection{FlowRemote -- Remote Control GUI}
 
+FlowRemote is designed in order to allow for easier configuration and calibration of the setup, as well as enabling the engineer to do so remotely. The idea being that---once the Raspberry Pi and LIDAR sensor have been installed over a conveyor system and a network connection---the engineer no longer requires a direct physical connection to the Raspberry Pi in order to configure and calibrate the system. \autoref{fig:flowremotegui} shows the design of the GUI.
+
+As described in \autoref{fig:flowremote}, FlowRemote allows the engineer to remotely preview the raw sensor data, run pre-processing on it, configure the processing parameters and deliver those back to the local processor running on the Raspberry Pi. 
+
 \begin{figure}[h]
 	\centering
 	\includegraphics[width=0.9\textwidth]{./design/FlowRemote}
@@ -344,31 +395,22 @@ These are implemented in \clang\ as much as possible. This is then encapsulated
 	\label{fig:flowremote}
 \end{figure}
 
-\begin{figure}[h]
+\begin{figure}[H]
 	\centering
 	\includegraphics[width=\textwidth]{./flowremote}
 	\caption{Design of the FlowRemote GUI.}
 	\label{fig:flowremotegui}
 \end{figure}
 
-FlowRemote is designed in order to allow easier configuration and calibration of the setup, as well as enabling the engineer to do so remotely. The idea being that---once the Raspberry Pi and LIDAR sensor have been installed over a conveyor system and a network connection---the engineer no longer requires a direct physical connection to the Raspberry Pi in order to configure and calibrate the system.
-
-As described in \autoref{fig:flowremote}, FlowRemote allows the engineer to remotely preview the raw sensor data, run pre-processing on it, configure the processing parameters and deliver those back to the local processor running on the Raspberry Pi.
-
-
-%\section{Data Processing and Outputs}\label{sec:dataproc}
-%rotation algorithm, skew algorithm, curve fitting library, cross-correlation algorithm...
-%
-%transmission to Profinet, output formats (float)\todo{complete section}
-
-
 \section{Housing}
-\begin{figure}[H]
+For the purposes of field-testing the project, a rudimentary housing was designed in CAD---see \autoref{fig:housing}---and 3D printed. The housing provided a small amount of protection from the environment for the otherwise bare Raspberry Pi.
+
+\begin{figure}[h]
 \centering
 \includegraphics[width=\textwidth]{housing}
 \caption{Isometric view of the underside (left) and topside (right) of the prototype housing.}
+\label{fig:housing}
 \end{figure}
-For the purposes of field-testing the project, a rudimentary housing was designed in CAD and 3D printed. The housing provided a small amount of protection from the environment for the otherwise bare Raspberry Pi.
 
 The housing was constructed around the standard Raspberry Pi 4 Model B with the netHAT modules attached, allowing for the extra ports to be accessible through the housing as well.
 

4-Validation/Validation.tex

@@ -1,22 +1,28 @@
 \chapter{Validation}\label{chap:validation}
+
+As was briefly touched upon in \autoref{sec:developmentphases}, the development of this project was carried out in iterative phases. After each iteration, the developed features were validated for their functionality and suitability. This chapter will go over these stages---sandbox, laboratory and field-testing---in depth.
+
 \section{Sandbox Stage}
-\begin{figure}[h]
-\centering
-\includegraphics[width=0.75\textwidth]{prototype/mug}
-\caption{Visual representation of the sensor data plotted as a color-graph.}
-\end{figure}
+
 The fundamental objective of the sandbox stage of development was to investigate the suitability of the Intel RealSense L515 LIDAR sensor.
 
 In this stage, the testing was mainly to determine
 \begin{enumerate}
 \item if a connection to the sensor can be established
-\item if the data received can be visually represented and manipulated
+\item if the data received can be visually represented and manipulated---see \autoref{fig:mug}
 \item if the accuracy of the data was within a tolerable range
 \end{enumerate}
 
+\begin{figure}[h]
+\centering
+\includegraphics[width=0.75\textwidth]{prototype/mug}
+\caption{Visual representation of the sensor data plotted as a color-graph.}
+\label{fig:mug}
+\end{figure}
+
 In order to accomplish this, a precursor to the FlowDAR software was developed that was connected to the sensor directly over USB. The aim of the software was to process the raw sensor data in order to determine the cross-sectional area of an object upon a flat plane. In this case, a small cardboard box was placed against a wall.
 
-As represented in \autoref{fig:prototype_program}, the software firstly calibrates itself to the flat plane---the wall---using linear regression to generate a straight-line. Then upon placing the object on the plane, using the techniques discussed in \autoref{chap:design}, the cross-sectional area of the object could be measured.
+As represented in \autoref{fig:prototype_program}, the software first calibrates itself to the flat plane---the wall---using linear regression to generate a straight-line. Then upon placing the object on the plane, using the techniques discussed in \autoref{chap:design}, the cross-sectional area of the object could be measured.
 
 An object with the cross-sectional area of \SI{3150}{\milli\meter\squared} was used in this validation. The software measured \SI{3288}{\milli\meter\squared}, yielding an error of \SI{4}{\percent}.
 
@@ -56,9 +62,9 @@ An object with the cross-sectional area of \SI{3150}{\milli\meter\squared} was u
 \end{figure}
 
 \section{Laboratory Stage}
-The development of the fundamental features of this project was done in an iterative process of rapid prototyping and testing. In order to accomplish this, a controlled environment that can be easily accessed and modified must be established. This setup was realized in the Telelaboratory\footnote{Laborator for the development of remote systems at the Faculty of Electrical Engineering, University of Applied Sciences Düsseldorf}.
+The development of the fundamental features of this project was done in an iterative process of rapid prototyping and testing. In order to accomplish this, a controlled environment that can be easily accessed and modified must be established. This setup was realized in the Telelaboratory\footnote{Laboratory for the development of remote systems at the Faculty of Electrical Engineering, University of Applied Sciences Düsseldorf}.
 
-The setup consisted of miniature looped conveyor belt system. The looped nature of this conveyor system was advantageous, as it could be loaded with material that would continuously circulate. This allowed development to be carry on uninterrupted and even remotely if necessary. The objects used to simulate material on the belt were miniature cars that were chosen simply for their availability and simple geometry.
+The setup consisted of a miniature looped conveyor belt system. The looped nature of this conveyor system was advantageous, as it could be loaded with material that would continuously circulate. This allowed development to be carry on uninterrupted and even remotely if necessary. The objects used to simulate material on the belt were miniature cars that were chosen simply for their availability and simple geometry.
 
 The LIDAR sensor was mounted using its ISO 1222 tripod mounting point on a regular camera tripod and positioned over the conveyor belt. The Raspberry Pi was connected to the laboratory network which allowed for configuration and testing to be done over the network. Using a VPN tunnel, further configuration and testing could also be done remotely from outside the laboratory network.
 
@@ -73,7 +79,7 @@ Object Cross-Sectional Area & Uncertainty \\ \hline
 \SI{20}{\milli\meter\squared} & \SI{10}{\percent} \\ 
 \SI{120}{\milli\meter\squared} & \SI{4}{\percent} \\ \hline
 \end{tabular}
-\caption{Uncertainty of Cross-Sectional Area measurement for different sized objects}\label{table:cross_uncertainty}
+\caption{Uncertainty of Cross-Sectional Area measurement for different sized objects.}\label{table:cross_uncertainty}
 \end{table}
 
 As shown in \autoref{table:cross_uncertainty}, measurements of the miniature cars---with cross-sectional areas of \SI{20}{\milli\meter\squared}---had a relatively high uncertainty of around \SI{10}{\percent}. The uncertainty was reduced to \SI{4}{\percent} when using a cardboard box of a larger size. This however, is to be expected according to the specified uncertainty of the LIDAR sensor at \SI{1}{\meter}.
@@ -97,7 +103,7 @@ The values sent to the controller by the FlowPi over the Profinet interface were
 
 A simple PLC program was written to activate an output---in this case, turning on an LED---whenever the Cross-Sectional Area was over a certain threshold value.
 
-The FlowPi software as well as the Profinet interface were shown to be functioning as the LEDs lit up in a robust manner whenever a miniature car passed under the scanning area of the LIDAR sensor. A rigorous measurement of the latency was not carried out, however the latency was deemed to be under a second.
+The FlowPi software as well as the Profinet interface were shown to be functioning as the LEDs lit up in a robust manner whenever a miniature car passed under the scanning area of the LIDAR sensor. A rigorous measurement of the latency was not carried out, however the latency was deemed to be under one second.
 
 \subsection{Linux RT-Patch}
 In order to test the effect of the Linux RT-Patch, a simple test comparing the jitter values of Profinet-IO communications was conducted.
@@ -107,7 +113,7 @@ The system was connected over Profinet to a Virtual PLC running on Codesys, and
 The results show that the RT-Patched kernel had a maximum jitter of \SI{2166}{\micro\second}, which was \SI{26}{\percent} lower than the normal kernel. This lower jitter may be indicative of higher-determinism of the system.
 
 \section{Field-Testing Stage}
-The field-testing stage was carried out at the Siep Gravel Quarry\footnote{Siep Kieswerk GmbH \& Co. KG in Jülich. See \nameref{chap:ack}.}. There, a bucket loader was being used to excavate gravel into a hopper. The hopper first filtered out larger rocks and boulders through a set of evenly spaced rods. Acting as a buffer, the hopper would continuously load a conveyor belt with gravel.
+The field-testing stage was carried out at the Siep Gravel Quarry\footnote{Siep Kieswerk GmbH \& Co. KG in Jülich. See \nameref{chap:ack}.}---see \autoref{fig:photo_overview}. There, a bucket loader was being used to excavate gravel into a hopper. The hopper first filtered out larger rocks and boulders through a set of evenly spaced rods. Acting as a buffer, the hopper would continuously load a conveyor belt with gravel.
 
 The quarry currently uses a conventional belt scale system that was placed under the conveyor belt. This simultaneously measured both belt velocity and the material mass flow---in tonnes per hour---delivering the values to a PLC in a nearby control box. 
 
@@ -115,16 +121,19 @@ The quarry currently uses a conventional belt scale system that was placed under
 \centering
 \includegraphics[width=0.75\textwidth]{photographs/overview}
 \caption{Siep Kieswerk GmbH \& Co. KG in Jülich where the field testing was carried out.}
+\label{fig:photo_overview}
 \end{figure}
+
+\subsection{Setup and Testing}
+The LIDAR sensor was attached to a walkway that went over the conveyor belt---see \autoref{fig:beltview}. The sensor must be placed at a minimum distance of \SI{0.5}{\meter} from the belt, in addition to clearance accounting for the height of the gravel on the belt as well. In this case, the sensor was placed at a height of \SI{1}{\meter} from the belt. The housed Raspberry Pi and various connections were also attached to the walkway.
+
 \begin{figure}[h]
 \centering
 \includegraphics[width=0.75\textwidth]{photographs/beltview}
 \caption{The view of the conveyor belt and material as seen by the sensor.}
+\label{fig:beltview}
 \end{figure}
 
-\subsection{Setup and Testing}
-The LIDAR sensor was attached to a walkway that went over the conveyor belt. The sensor must be placed at a minimum distance of \SI{0.5}{\meter} from the belt, in addition to clearance accounting for the height of the gravel on the belt as well. In this case, the sensor was placed at a height of \SI{1}{\meter} from the belt. The housed Raspberry Pi and various connections were also attached to the walkway.
-
 A standard home-grade wireless access point was used to provide a local network, through which the configuration of the system could take place.
 
 Once all the devices were connected and turned on, the pre-configured Raspberry Pi connected itself to the wireless access point that was reachable by the engineering laptop. A connection between the FlowRemote configuration software and the FlowPi processing software could be established and configuration could begin.

5-Conclusion/Conclusion.tex

@@ -5,11 +5,13 @@ The state of this project upon completion can be analyzed by recalling the resea
 A breakdown of the various factors that determine the suitability of the implementation presented in this project:
 \begin{description}
 
-\item[Sensor Suitability] \hfill \\ The wavelength of the infrared laser used in this project of \SI{860}{\nano\meter} was shown to be unsuitable for use with the conveyor belt during the on-site testing. This is most likely due to the absorption spectrum of the belt material that had very flow reflectivity at this infrared wavelength. The similarly black colored belt used in laboratory testing however was visible to the LIDAR sensor. A further study of belt materials commonly deployed in the field is necessary.
+\item[Sensor Suitability] \hfill \\ The wavelength of the infrared laser used in this project of \SI{860}{\nano\meter} was shown to be unsuitable for use with the conveyor belt during the on-site testing. This is most likely due to the absorption spectrum of the belt material that had very low reflectivity at this infrared wavelength. The similarly black colored belt used in laboratory testing however was visible to the LIDAR sensor. A further study of belt materials commonly deployed in the field is necessary.
+
+The Intel RealSense L515 Sensor was designed for indoor use and therefore has no vibration certification or waterproofing certification. Either a housing must be designed to adequately protect sensor, or another sensor with appropriate ratings must be used instead.
 
 \item[Temperature Suitability] \hfill \\ On the higher end of the temperature range, the LIDAR sensor used in this project is the limiting factor. The maximum temperature of \SI{30}{\celsius} is easily exceeded in particularly hot weather or even in direct sunlight. Design of the housing must account for adequate cooling, as well as reflectivity, should the system be deployed in view of direct sunlight.
 
-\item[Hardware Suitability] \hfill \\ The Raspberry Pi provided sufficient processing power in order to develop, test and deploy the prototype software. The flexibility of the Linux platform also grants sufficient flexibility in order to easily add further functionality---i.e. a web server or other interface---or modify existing functionality.
+\item[Hardware Suitability] \hfill \\ The Raspberry Pi provided sufficient processing power in order to develop, test and deploy the prototype software. The flexibility of the Linux platform also grants sufficient flexibility in order to easily add further functionality---i.e.\ a web server or other interface---or modify existing functionality.
 
 The netHAT was also shown to be performant and stable during testing. Combined with the Raspberry Pi, it provides a low cost platform to bring IoT to Industrial Networking.
 
@@ -17,9 +19,11 @@ The netHAT was also shown to be performant and stable during testing. Combined w
 
 \item[Software Suitability] \hfill \\ The software architecture as laid-out in \autoref{chap:design} was shown to fulfill the requirements of the process. The individual software elements and libraries such as ZeroMQ and Qt were shown to be robust enough to carry out the configuration process. The software was shown to successfully combine the separate process elements into a single workflow which simplified the configuration process.
 
-\item[Cost Suitability] \hfill \\ At a development cost of just under €600---even at a profit margin of \SI{500}{\percent}---the system is still able to remain competitive with conventional systems in use in the industry today\footnote{See \autoref{table:cost}}.
+\item[Cost Suitability] \hfill \\ At a development cost of just under \euro{600}---even at a profit margin of \SI{500}{\percent}---the system is still able to remain competitive with conventional systems in use in the industry today\footnote{See \autoref{table:cost}}.
+
+\item[Housing Suitability] \hfill \\ The housing designed for the field-testing stage of this project is only suitable as a prototype. A more robust housing must be developed out of more durable materials, and account for weather and vibration. 
+
 
-\item[Housing Suitability] \hfill \\ The housing designed for the field-testing stage of this project is only suitable as a prototype. A more robust housing must be developed out of more durable materials, and account for weather and vibration.
 \end{description}
 
 \section{Project Status and Feasibility}
@@ -36,6 +40,6 @@ One or two more iterations of development are required in order to fully realize
 
 The issues at this stage are only that of signal acquisition and signal pre-processing. The field-testing has shown that the expectation of the signal was slightly different from reality due to the optical properties of the conveyor belt. New methods and operations need to be developed to circumvent these issues.
 
-Once these signal issues have been overcome, all that remains is testing the system for accuracy, stability and robustness. Future work must deal with the questions of environment-proofing and housing.
+Once these signal issues have been overcome, all that remains is testing the system for accuracy, stability and robustness. For example, stability of the measurements may be impacted by vibration. Therefore, suitable software additions must be made to filter out such vibrations, should they introduce significant error. Future work must deal with these questions of environment-proofing and housing. 
 
 In order to study the commercial viability of this product to its end, future work must also investigate the potential sourcing and supply chains of the hardware used. As mentioned earlier in this work, the RealSense L515 has been discontinued, and other suitable hardware must be sourced and integrated.

I-Abstract/Abstract.tex

@@ -1,2 +1,6 @@
 \chapter{Abstract}
-The availability of powerful commercial hardware in recent years has enabled not only the potential to reduce costs, but also allow the integration of conventional software development methods of Industrial IoT. In order to test the viability of these products and methods, this project concerns itself with developing a cheaper and easier-to-install alternative to the conventional belt scales used for measuring the volume of bulk material on industrial conveyor belts. Previous research has shown that optical and laser-based methods for measuring bulk material are indeed possible, however only through to use of research-grade or industrial equipment. This work demonstrates---through the development of a prototype with the accompanying software---that a system using the Intel RealSense L515 and a Raspberry Pi has the required performance to run the required analysis, and deliver those results over Industrial Ethernet to conventional industrial PLCs. Although a fully-functional product was not able to be realized due to the unsuitable optical properties of the tested conveyor belt, the system is capable enough to deliver results in a laboratory setting. More work is required to further fine-tune the signal pre-processing issues in the field.
+The availability of powerful commercial hardware in recent years has enabled not only the potential to reduce costs, but also allowed for the integration of the conventional software development methods of Industrial IoT. To test the viability of these products and methods, this project concerns itself with developing a cheaper and easier-to-install alternative to the conventional belt scales used for measuring the volume of bulk material on industrial conveyor belts.
+
+Previous research has shown that optical and laser-based methods for measuring the volume of bulk material are indeed possible, but only through the use of research-grade or industrial-grade equipment. This work demonstrates---through the development of a prototype with the accompanying software---that a system using the Intel RealSense L515 and a Raspberry Pi has the required performance to run the required analysis, and deliver those results over Industrial Ethernet to conventional industrial PLCs.
+
+Although a fully-functional product was not realized due to the unsuitable optical properties of the tested conveyor belt, the system is capable enough to deliver results in a laboratory setting. More work is required to further fine-tune the signal pre-processing issues in the field.

II-Thanks/Thanks.tex

@@ -1,6 +1,6 @@
 \chapter{Acknowledgments}\label{chap:ack}
 
-I would like to give special thanks to Prof. Dr.-Ing. Michael Protogerakis for his attentive supervision of my Master Project and this thesis.
+I would like to give special thanks to Prof. Dr.-Ing. Michael Protogerakis for his attentive supervision of my Master's Project and this thesis.
 
 N. Stuhrmann and M. Meilchen too have my gratitude for their tireless assistance in the laboratory.
 

III-Eides/Eides.tex

@@ -8,8 +8,8 @@ Düsseldorf, February 2022
 Nareshkumar Rao
 
 This thesis was supervised by:\\
-1. Examiner: Prof. Dr.-Ing M. Protogerakis\\
-2. Examiner: Prof. Dr.-Ing R. Beck
+1. Examiner: Prof. Dr.-Ing. M. Protogerakis\\
+2. Examiner: Prof. Dr.-Ing. R. Beck
 
 \vspace{2em}
 \hrule
@@ -24,5 +24,5 @@ Düsseldorf, Februar 2022
 Nareshkumar Rao
 
 Diese Arbeit wurde betreut von:\\
-1. Prüfer: Prof. Dr.-Ing M. Protogerakis\\
-2. Prüfer: Prof. Dr.-Ing R. Beck
+1. Prüfer: Prof. Dr.-Ing. M. Protogerakis\\
+2. Prüfer: Prof. Dr.-Ing. R. Beck

Main.tex

@@ -61,6 +61,7 @@
 \newcommand{\todoi}[1]{\todo[inline]{#1}}
 \newcommand{\cpp}{\texttt{C++}}
 \newcommand{\clang}{\texttt{C}}
+\newcommand{\euro}[1]{€\,#1}
 \newcommand{\fullWidthImage}[3]{
 \begin{figure}[h]
 	\includegraphics[width=0.9\textwidth]{#1}
@@ -95,7 +96,7 @@ pdfkeywords={LIDAR, conveyor belt}
 \include{./III-Eides/Eides}
 %\include{./II-Glossary/Glossary}
 
-\setcounter{secnumdepth}{2}
+\setcounter{secnumdepth}{1}
 \setcounter{tocdepth}{1}
 \tableofcontents 
 

dict.txt

@@ -7,4 +7,5 @@ FlowPi
 CIFX
 PhoenixContact
 PLCNext
-
+Nareshkumar
+Rao

literatur.bib

@@ -1,4 +1,20 @@
 
+@article{elias1980,
+  title = {Accuracy and Performance Analysis of a Nuclear Belt Weigher},
+  author = {Elias, E. and Pieters, W. and Yom-tov, Z.},
+  date = {1980-12-01},
+  journaltitle = {Nuclear Instruments and Methods},
+  shortjournal = {Nuclear Instruments and Methods},
+  volume = {178},
+  number = {1},
+  pages = {109--115},
+  issn = {0029-554X},
+  doi = {10.1016/0029-554X(80)90863-0},
+  abstract = {Nuclear belt weighers have a broad range of applications in the solid particle industry. This work analyzes the accuracy and sensitivity of nuclear weighers for a wide range of operational conditions and design parameters. The problem of the effect of material profile and bulk density variations on the scale performance is quantitatively addressed. A new methodology is developed to calculate the minimum detectable load accounting for both accuracy and sensitivity. Accuracies of less than 1\% can be achieved in some ideal situations by proper design of the source length and geometrical configuration.},
+  langid = {english},
+  file = {/home/naresh/Zotero/storage/5MYVCG6T/Elias et al. - 1980 - Accuracy and performance analysis of a nuclear bel.pdf;/home/naresh/Zotero/storage/9HHFBGPZ/0029554X80908630.html}
+}
+
 @inproceedings{fojtik2014,
   title = {Measurement of the Volume of Material on the {{Conveyor Belt}} Measuring of the Volume of Wood Chips during Transport on the {{Conveyor Belt}} Using a Laser Scanning},
   booktitle = {Proceedings of the 2014 15th {{International Carpathian Control Conference}} ({{ICCC}})},