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.
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Acknowledgment
The authors gratefully thank the referees for the constructive and insightful comments. This work was supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant No. 16KJB510014, the Natural Science Foundation of Jiangsu Province under Grant No. BK20171023, and the National Natural Science Foundation of China under Grant No. 61701223.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Sun, Y., Wang, X., Zhang, X., Zhang, X. (2018). ZigBee-Based Device-Free Wireless Localization in Internet of Things. In: Meng, L., Zhang, Y. (eds) Machine Learning and Intelligent Communications. MLICOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-00557-3_57
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DOI: https://doi.org/10.1007/978-3-030-00557-3_57
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