\section{Conclusion}

map information into smoothing. better way and faster then just dijkstra. compensate big jumps caused by wifi. better method for estimation and drawing of particles in backward simulation. more advanced smoothing transition. not used evaluating using the observations, but using the given information for more advanced approaches. 

fixed-lag gap dynamic interval dependend upon estimation error variance

\begin{figure}
	\input{gfx/activity/activity_over_time}
	\caption{activity recognition}
	\label{fig:activityRecognition}
\end{figure}

\begin{figure}
	\input{gfx/particles/particles}
	\caption{particles. green = avg50, black = avg. gnuplot zickt bei der legende}
	\label{fig:activityRecognition}
\end{figure}