A System for Monitoring Animals Based on Behavioral Information and Internal State Information
Managing the risk of injury or illness is an important consideration when keeping pets. This risk can be minimized if pets are monitored on a regular basis, but this can be difficult and time-consuming. However, because only the external behavior of the animal can be observed and the internal condit...
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Format: | Article |
Language: | English |
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MDPI AG
2024-01-01
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Series: | Animals |
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Online Access: | https://www.mdpi.com/2076-2615/14/2/281 |
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author | Taro Shibanoki Yuugo Yamazaki Hideyuki Tonooka |
author_facet | Taro Shibanoki Yuugo Yamazaki Hideyuki Tonooka |
author_sort | Taro Shibanoki |
collection | DOAJ |
description | Managing the risk of injury or illness is an important consideration when keeping pets. This risk can be minimized if pets are monitored on a regular basis, but this can be difficult and time-consuming. However, because only the external behavior of the animal can be observed and the internal condition cannot be assessed, the animal’s state can easily be misjudged. Additionally, although some systems use heartbeat measurement to determine a state of tension, or use rest to assess the internal state, because an increase in heart rate can also occur as a result of exercise, it is desirable to use this measurement in combination with behavioral information. In the current study, we proposed a monitoring system for animals using video image analysis. The proposed system first extracts features related to behavioral information and the animal’s internal state via mask R-CNN using video images taken from the top of the cage. These features are used to detect typical daily activities and anomalous activities. This method produces an alert when the hamster behaves in an unusual way. In our experiment, the daily behavior of a hamster was measured and analyzed using the proposed system. The results showed that the features of the hamster’s behavior were successfully detected. When loud sounds were presented from outside the cage, the system was able to discriminate between the behavioral and internal changes of the hamster. In future research, we plan to improve the accuracy of the measurement of small movements and develop a more accurate system. |
first_indexed | 2024-03-08T11:07:56Z |
format | Article |
id | doaj.art-e6f0710cfbf345548580f1dbbdb72358 |
institution | Directory Open Access Journal |
issn | 2076-2615 |
language | English |
last_indexed | 2024-03-08T11:07:56Z |
publishDate | 2024-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Animals |
spelling | doaj.art-e6f0710cfbf345548580f1dbbdb723582024-01-26T14:32:45ZengMDPI AGAnimals2076-26152024-01-0114228110.3390/ani14020281A System for Monitoring Animals Based on Behavioral Information and Internal State InformationTaro Shibanoki0Yuugo Yamazaki1Hideyuki Tonooka2Department of Intelligent Mechanical Systems, Faculty of Environmental, Life, Natural Science and Technology, Okayama University, Okayama 700-8530, JapanMajor in Computer and Information Sciences, Graduate School of Science and Engineering, Ibaraki University, Hitachi 316-8511, JapanMajor in Computer and Information Sciences, Graduate School of Science and Engineering, Ibaraki University, Hitachi 316-8511, JapanManaging the risk of injury or illness is an important consideration when keeping pets. This risk can be minimized if pets are monitored on a regular basis, but this can be difficult and time-consuming. However, because only the external behavior of the animal can be observed and the internal condition cannot be assessed, the animal’s state can easily be misjudged. Additionally, although some systems use heartbeat measurement to determine a state of tension, or use rest to assess the internal state, because an increase in heart rate can also occur as a result of exercise, it is desirable to use this measurement in combination with behavioral information. In the current study, we proposed a monitoring system for animals using video image analysis. The proposed system first extracts features related to behavioral information and the animal’s internal state via mask R-CNN using video images taken from the top of the cage. These features are used to detect typical daily activities and anomalous activities. This method produces an alert when the hamster behaves in an unusual way. In our experiment, the daily behavior of a hamster was measured and analyzed using the proposed system. The results showed that the features of the hamster’s behavior were successfully detected. When loud sounds were presented from outside the cage, the system was able to discriminate between the behavioral and internal changes of the hamster. In future research, we plan to improve the accuracy of the measurement of small movements and develop a more accurate system.https://www.mdpi.com/2076-2615/14/2/281monitoring systemimage processingmask R-CNNanomaly detectionone-class SVMrodents |
spellingShingle | Taro Shibanoki Yuugo Yamazaki Hideyuki Tonooka A System for Monitoring Animals Based on Behavioral Information and Internal State Information Animals monitoring system image processing mask R-CNN anomaly detection one-class SVM rodents |
title | A System for Monitoring Animals Based on Behavioral Information and Internal State Information |
title_full | A System for Monitoring Animals Based on Behavioral Information and Internal State Information |
title_fullStr | A System for Monitoring Animals Based on Behavioral Information and Internal State Information |
title_full_unstemmed | A System for Monitoring Animals Based on Behavioral Information and Internal State Information |
title_short | A System for Monitoring Animals Based on Behavioral Information and Internal State Information |
title_sort | system for monitoring animals based on behavioral information and internal state information |
topic | monitoring system image processing mask R-CNN anomaly detection one-class SVM rodents |
url | https://www.mdpi.com/2076-2615/14/2/281 |
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