Abstract
Movement detection in Internet of Things (IoTs) has been widely used in many fields, such as valuables monitoring, safety protection and empty-nesters care. Monitoring by videos, GPS and ultrasonic is the most common method to address the movement detection in IoTs. However, these efforts are circumscribed because they need the support of the special equipment, such as cameras, infrared equipment and ultrasonic facilities. It is significant to detect the movement in IoTs systems without additional equipment and ensure its high detection precision. Therefore, in this paper we derive an innovative method called Horizontal Slicing Clustering (HSC) to detect the movement in the IoTs. Received Signal Strength Indicator (RSSI) data are the network parameters which are utilized in this method. The simulation results show their effectiveness in movement detection.
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Acknowledgments
This work is supported by the 2014 Natural Science Foundation of Guangdong Province under Grant 2014A030313685, the 2014 Pearl River Science and Technology Nova Program of Guangzhou under Grant 2014J2200023, Guangdong High-Tech Development Fund No. 2013B010401035, 2013 top Level Talents Project in “Sailing Plan” of Guangdong Province, National Natural Science Foundation of China (Grant No. 61401107), and 2014 Guangdong Province Outstanding Young Professor Project (No. Yq014116).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Li, X., Wu, X., Huang, D., Shu, L. (2018). Horizontal Slicing Clustering Based Movement Detection Method for IoTs. In: Huang, M., Zhang, Y., Jing, W., Mehmood, A. (eds) Wireless Internet. WICON 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 214. Springer, Cham. https://doi.org/10.1007/978-3-319-72998-5_29
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DOI: https://doi.org/10.1007/978-3-319-72998-5_29
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