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dc.contributor.authorHu, Jwu-Shengen_US
dc.contributor.authorHuang, Yu-Lunen_US
dc.contributor.authorTseng, Chin-Yuanen_US
dc.date.accessioned2014-12-08T15:36:37Z-
dc.date.available2014-12-08T15:36:37Z-
dc.date.issued2014en_US
dc.identifier.issn1550-1329en_US
dc.identifier.urihttp://hdl.handle.net/11536/24958-
dc.identifier.urihttp://dx.doi.org/10.1155/2014/654063en_US
dc.description.abstractLocalization in a wireless sensor network (WSN) becomes important for many modern applications, like landslide detection, precision agriculture, health care, and so forth. The more precise the position of an anchor node is, the more accurate the localization of a sensor node can be measured. Since the Global Positioning System (GPS) device cannot work properly indoor, some existing localization methods configure anchor nodes in a manual fashion. However, neither applying GPS modules nor manually configuring anchor nodes is suitable for a WSN and especially artificial errors ofmanual configuration may be propagated and affect the results of localization. In this paper, we propose an alternative method to estimate anchor node locations in an indoor environment. We collect the Received Signal Strength Indicator (RSSI) data from the anchor node when human is walking around them. Meanwhile, we use a wearable IMU-camera device to assist the moving trajectory estimation. We implement a monocular Visual Odometry with a human walking model to estimate moving trajectories. An Unscented Kalman Filter (UKF) is used to estimate the anchor node location by fusing the RSSI data and moving trajectory. The experiment results show that the proposed method has lower estimation error when locating anchors.en_US
dc.language.isoen_USen_US
dc.titleLocating Anchors in WSN Using a Wearable IMU-Cameraen_US
dc.typeArticleen_US
dc.identifier.doi10.1155/2014/654063en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKSen_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000339757500001-
dc.citation.woscount0-
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