This paper proposes the concept of the Internet of dogs, and uses its perceptual tracking to track the behavioral trajectory of various dogs around the world, constructs a framework for analyzing the spatial and temporal trajectory of dogs, and answers our more unsolved mysteries. For noise data, this paper adopts the sliding filter algorithm. Which makes the behavior data significantly enhance the smoothness, and constructs a new police dog motion attitude fusion method. Compared with the Kalman filter method, it has higher real-time performance under the premise of ensuring accuracy. A new multi-sensor police dog data vest is designed and implemented according to the biological movement characteristics of the police dog. Based on multiple small and low power consumption sensors, a new police dog motion attitude fusion method is constructed, which can capture different posture data of the police dog, including standing, sitting, lying, etc.


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    Title :

    From State Estimation for Dogs to the Internet of Dogs


    Contributors:
    Wang, Youwen (author) / Huang, Qian (author) / Chen, Sisi (author) / Zhu, Chaozheng (author)


    Publication date :

    2019-07-01


    Size :

    3694020 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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