In this book a Received Signal Strength (RSS) based indoor
localization system, dubbed LEMON, based on low-cost low-power
wireless devices is proposed, which offers better accuracy than the
state-of-the-art. A simple RSS scaling trick is then used to
further improve the accuracy of LEMON. Furthermore, we study the
effect of the node orientation, the number and the arrangement of
the infrastructure nodes and the profiled samples, leading us to
further insights about what can be effective node placement and
profiling. We also consider alternate formulations of the
localization problem, as a Bayesian network model as well as
formulated in a combinatorial fashion. Then performance of
different localization methods is compared and again LEMON ensures
better accuracy. An effective room localization algorithm is
developed, and both single and multiple channels are used to test
its performance. Furthermore, a set of two-step localization
algorithms is designed to make the LEMON robust in the presence of
noisy RSS and faulty device behavior.
Lap Lambert Academic Publishing
|Country of origin:
Israat Tanzeena Haque
||229 x 152 x 7mm (L x W x T)
||Paperback - Trade
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