Research Article
ZigBee-Based Device-Free Wireless Localization in Internet of Things
@INPROCEEDINGS{10.1007/978-3-030-00557-3_57, author={Yongliang Sun and Xiaocheng Wang and Xuzhao Zhang and Xinggan Zhang}, title={ZigBee-Based Device-Free Wireless Localization in Internet of Things}, proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings}, proceedings_a={MLICOM}, year={2018}, month={10}, keywords={Device-free wireless localization Internet of Things Artificial neural networks ZigBee}, doi={10.1007/978-3-030-00557-3_57} }- Yongliang Sun
Xiaocheng Wang
Xuzhao Zhang
Xinggan Zhang
Year: 2018
ZigBee-Based Device-Free Wireless Localization in Internet of Things
MLICOM
Springer
DOI: 10.1007/978-3-030-00557-3_57
Abstract
In recent years, localization has been one of the research hot-spots in Internet of Things (IoT). Device-Free Wireless Localization (DFWL) that extends the application range of wireless localization has been considered as a promising technology. In this paper, we propose a ZigBee-based DFWL system using Artificial Neural Networks (ANNs) in IoT. The proposed system utilizes Received Signal Strength (RSS) variations, which is caused by the obstructing of the Line of Sight (LoS) links, to estimate the location of a target using an ANN model. A nonlinear function is approximated between RSS difference information and location coordinates using the ANN model. With the ANN model, the location of the target can be estimated. The experimental results show that the proposed DFWL system is able to locate the target without any terminal device and offer a valuable reference for DFWL in IoT.