Human SLAM: Simultaneous Localisation and Configuration (SLAC) of Indoor Wireless Sensor Networks and theri Users
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Issue Date
2015-08-24
Language
en
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Abstract
The indoor localisation problem, in smart spaces, is more than just finding the whereabouts
of users. Finding positions of users relative to the devices of a smart space is even
more important. Unfortunately, configuring such systems manually is a tedious process,
requires expert knowledge and is not resilient to changes in the environment.
We propose a new system, called Simultaneous Localisation and Configuration (SLAC),
to address these two challenges, locating the user and the devices, and combine them
into a single estimation problem. The SLAC algorithm, which is based on FastSLAM, is
able to locate devices using the received signal strength indicator (RSSI) of devices and
motion data from users.
Simulations have been used to show two main effects on the localisation performance:
the amount of RSSI updates and the location of devices in the space. Live tests, in nontrivial
environments, showed that we can achieve room level accuracy and that the
localisation can be performed in real time. This is all done locally, i.e. running on a
user's device, with respect for privacy and without using any prior information of the
environment or device locations.
More work is required to increase accuracy in larger environments and to make the
algorithm more robust for environment noise caused by walls and other objects. Existing
techniques, such as map fusing, could alleviate these problems.
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Faculteit der Sociale Wetenschappen