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kazu
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tex/chapters/conclusion.tex
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\section{Conclusion}
Within this work a novel approach for utilizing the forward-backward smoother and backward simulation to problems of indoor localisation was presented.
Within this work a novel approach for utilizing \commentByFrank{utiliSing?} the forward-backward smoother and backward simulation to problems of indoor localisation was presented.
Both were implemented as fixed-lag and fixed-interval smoother.
It was shown that smoothing methods are able to decrease the estimation error and improving the overall localisation.
Especially fixed-lag smoothing is a great tool for runtime support by reducing timely errors and improving the overall estimation with affordable costs.
It was shown that smoothing methods are able to decrease the estimation error and improving \commentByFrank{are able to decrease ... and improve. ING weg?} the overall localisation.
Especially fixed-lag smoothing is a great tool for runtime support by reducing timely \commentByFrank{wieder} errors and improving the overall estimation with affordable costs.
However, a fixed-lag smoother is not able to change the lag dynamically, as its name suggests.
Therefore, a dynamic-lag smoother could be able to further improve the estimation by considering higher lags in critical areas.