Research Article
Horizontal Slicing Clustering Based Movement Detection Method for IoTs
@INPROCEEDINGS{10.1007/978-3-319-72998-5_29, author={Xiaoyu Li and Xiaoling Wu and Daoping Huang and Lei Shu}, title={Horizontal Slicing Clustering Based Movement Detection Method for IoTs}, proceedings={Wireless Internet. 9th International Conference, WICON 2016, Haikou, China, December 19-20, 2016, Proceedings}, proceedings_a={WICON}, year={2018}, month={1}, keywords={Internet of things (IoTs) Movement detection Horizontal slicing clustering (HSC) Received signal strength indicator (RSSI)}, doi={10.1007/978-3-319-72998-5_29} }- Xiaoyu Li
Xiaoling Wu
Daoping Huang
Lei Shu
Year: 2018
Horizontal Slicing Clustering Based Movement Detection Method for IoTs
WICON
Springer
DOI: 10.1007/978-3-319-72998-5_29
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.