Topological Mapping through Distributed, Passive Sensors
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 2147-2151.
Abstract
In this paper we address the problem of inferring the topology, or inter-node navigability, of a sensor network given non-discriminating observations of activity in the environment. By exploiting motion present in the environment, our approach is able to recover a probabilistic model of the sensor network connectivity graph and the underlying traffic trends. We employ a reasoning system made up of a stochastic Expectation Maximization algorithm and a higher level search strategy employing the principle of Occam's Razor to look for the simplest solution explaining the data. The technique is assessed through numerical simulations and experiments conducted on a real sensor network.
@inproceedings{ijcai2007p346,
title = {Topological Mapping through Distributed, Passive Sensors},
author = {Marinakis, Dimitri and Dudek, Gregory},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {2147--2151},
year = {2007},
url = {https://ijcai.org/proceedings/2007/346},
}
TY - CPAPER TI - Topological Mapping through Distributed, Passive Sensors AU - Marinakis, Dimitri AU - Dudek, Gregory T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 2147 EP - 2151 UR - https://ijcai.org/proceedings/2007/346 ER -Copied
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