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27188 Ambient Sound-Based Collaborative Localization of Indeterministic Devices
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Kamminga, J.W. and Le, Viet Duc and Havinga, P.J.M. (2016) Ambient Sound-Based Collaborative Localization of Indeterministic Devices. Sensors (Switserland), 16 (9). 1478. ISSN 1424-8220 *** ISI Impact 2,033 ***

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Localization is essential in wireless sensor networks. To our knowledge, no prior work has utilized low-cost devices for collaborative localization based on only ambient sound, without the support of local infrastructure. The reason may be the fact that most low-cost devices are indeterministic and suffer from uncertain input latencies. This uncertainty makes accurate localization challenging. Therefore, we present a collaborative localization algorithm (Cooperative Localization on Android with ambient Sound Sources (CLASS)) that simultaneously localizes the position of indeterministic devices and ambient sound sources without local infrastructure. The CLASS algorithm deals with the uncertainty by splitting the devices into subsets so that outliers can be removed from the time difference of arrival values and localization results. Since Android is indeterministic, we select Android devices to evaluate our approach. The algorithm is evaluated with an outdoor experiment and achieves a mean Root Mean Square Error (RMSE) of 2.18 m with a standard deviation of 0.22 m. Estimated directions towards the sound sources have a mean RMSE of 17.5 ° and a standard deviation of 2.3 °. These results show that it is feasible to simultaneously achieve a relative positioning of both devices and sound sources with sufficient accuracy, even when using non-deterministic devices and platforms, such as Android.

Item Type:Article
Research Group:EWI-PS: Pervasive Systems
Research Program:CTIT-General
Research Project:COMMIT/SENSA: Sensor Networks for Public Safety
Uncontrolled Keywords:sound localization; collaborative localization; opportunistic localization; wireless sensor networks; smartphones; Android; input latency
ID Code:27188
Deposited On:31 October 2016
ISI Impact Factor:2,033
More Information:statistics

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