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Method for Identifying Cow Identity Based on Template Matching of Cow Activity Data

Published: 22 October 2018 Publication History

Abstract

The1 method of identifying cows based on the template matching of cow activity data is a method to realize the remote and intelligent identification of dairy cows' identity information and facilitate the management of pasture. The cow activity data refers to comprehensive information including but not limited to cow head movement data, swallowing amount data, general exercise data, and more. Through the daily accumulation and observation of data, different dairy cows have obvious differences in daily activities such as activity time, peak activity, etc. The identification method is based on the different behaviors of the corresponding cows in daily life resulting in fluctuations of different activity data to identify different cows. Through the research and improvement of experiment, we reduced the length of identification data before which needs more than 700 hours to only 120 hours of data, making the method practical.

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  1. Method for Identifying Cow Identity Based on Template Matching of Cow Activity Data

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    CSAE '18: Proceedings of the 2nd International Conference on Computer Science and Application Engineering
    October 2018
    1083 pages
    ISBN:9781450365123
    DOI:10.1145/3207677
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 22 October 2018

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    Author Tags

    1. Cow activity data
    2. cow illness warning
    3. data analysis
    4. identify cow identity
    5. template matching

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    CSAE '18 Paper Acceptance Rate 189 of 383 submissions, 49%;
    Overall Acceptance Rate 368 of 770 submissions, 48%

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