Proceedings of the Korean Society of Computer Information Conference (한국컴퓨터정보학회:학술대회논문집)
- 2019.07a
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- Pages.263-266
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- 2019
Analyzing Dog Health Status through Its Own Behavioral Activities
- Karimov, Botirjon (Department of Computer Engineering, Konkuk University) ;
- Muminov, Azamjon (Department of Computer Engineering, Konkuk University) ;
- Buriboev, Abror (Department of Computer Engineering, Konkuk University) ;
- Lee, Cheol-Won (Department of Computer Engineering, Konkuk University) ;
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Jeon, Heung Seok
(Department of Computer Engineering, Konkuk University)
- Published : 2019.07.10
Abstract
In this paper, we suggest an activity and health monitoring system to observe the status of the dogs in real time. We also propose a k-days algorithm which helps monitoring pet health status using classified activity data from a machine learning approach. One of the best machine learning algorithm is used for the classification activity of dogs. Dog health status is acquired by comparing current activity calculation with passed k-days activities average. It is considered as a good, warning and bad health status for differences between current and k-days summarized moving average (SMA) > 30, SMA between 30 and 50, and SMA < 50, respectively.