Wireless Internet. 9th International Conference, WICON 2016, Haikou, China, December 19-20, 2016, Proceedings

Research Article

Horizontal Slicing Clustering Based Movement Detection Method for IoTs

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  • @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
Xiaoyu Li1, Xiaoling Wu,*, Daoping Huang1, Lei Shu2
  • 1: South China University of Technology
  • 2: Guangdong University of Petrochemical Technology
*Contact email: xl.wu@giat.ac.cn

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.