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added heading and step detection to transition

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toni
2018-09-20 10:24:23 +02:00
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7 changed files with 44 additions and 25 deletions
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tex/chapters/introduction.tex
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@@ -21,7 +21,7 @@ Within this work we present a simple yet efficient method that enables a particl
We also use a novel approach for finding an exact estimation of the pedestrian's current position by using a rapid computation scheme of the kernel density estimation \cite{Bullmann-18}.
Many historical buildings, especially bigger ones like castles, monasteries or churches, are built of massive stone walls and have annexes from different historical periods out of different construction materials.
This leads to problems for methods using received signal strengths (RSS) from \docWIFI{} or Bluetooth, due to a high signal attenuation between different rooms.
This leads to problems for methods using received signal strengths indications (RSSI) from \docWIFI{} or Bluetooth, due to a high signal attenuation between different rooms.
Many unknown quantities, like the walls definitive material or thickness, make it expensive to determine important parameters, \eg{} the signal's depletion over distance.
Additionally, most wireless approaches are based on a line-of-sight assumption.
Thus, the performance will be even more limited due to the irregularly shaped spatial structure of such buildings.
@@ -35,10 +35,10 @@ Clearly, this is contrary to most costumers expectations of a fast to deploy and
In addition, this is not only a question of costs incurred, but also for buildings under monumental protection, not allowing for larger construction measures.
To sum up, this work presents a smartphone-based localization system using a particle filter to incorporate different probabilistic models.
We omit time-consuming approaches like classic fingerprinting or measuring the exact positions of access-points.
We 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 pedestrian's movement is modeled realistically using a navigation mesh, based on the building's floorplan.
A barometer based activity recognition enables going into the third dimension and problems occurring from multimodalities and impoverishment are taken into account.
A barometer and accelerometer based activity recognition enables going into the third dimension and problems occurring from multimodalities and impoverishment are taken into account.
The goal of this work is to propose a fast to deploy and low-cost localization solution, that provides reasonable results in a high variety of situations.
Consequently, we believe that by utilizing our localization approach to such a challenging scenario, it is possible to prove those characteristics.