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Title: RECOGNISING DAIRY COWS' BEHAVIOUR WITH LSTM MODEL TO IMPROVE FARM MANAGEMENT PRACTICES
RECOGNISING DAIRY COWS' BEHAVIOUR WITH LSTM MODEL TO IMPROVE FARM MANAGEMENT PRACTICES

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Kristina Dineva; Tatiana Atanasova
10.5593/sgem2023V/6.2/s25.43
10.5593/sgem2023v/6.2
1314-2704
978-619-7603-66-8
English
23
6.2
•    Prof. DSc. Oleksandr Trofymchuk, UKRAINE 
•    Prof. Dr. hab. oec. Baiba Rivza, LATVIA
Advances in Biotechnology
This paper focuses on recognizing the activity of dairy cows using a non-invasive approach that monitors four key behaviors: licking, feeding, standing, and lying. The study used IoT devices with accelerometers and gyroscopes attached to the cow's neck to continuously monitor its movements. The data collection process aimed to capture the dynamic and static nature of dairy cow behaviors, providing a valuable data set for subsequent analysis. To efficiently process the raw data, we analyzed it and then used long short-term memory (LSTM) neural networks, a type of recurrent neural network (RNN) suitable for sequential data processing. The LSTM model was trained on the collected sensor data to recognize and classify the four target activities. The model achieved an accuracy of 96%, indicating its robust ability to accurately identify dairy cow activity. Furthermore, the model consistently maintained a low loss value hovering around 0.25, demonstrating its generalization and predictive performance. This research has important implications for dairy production and animal welfare. Accurate real-time recognition of dairy cow activities can help improve farm management practices, enabling timely interventions when needed.
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The research leading to these results received funding from the Ministry of Educationand Science of the Republic Bulgaria under the National Science ProgramINTELLIGENT ANIMAL HUSBANDRY, grant agreement No. Д01-62/18.03.2021/.
conference
https://doi.org/10.5593/sgem2023V/6.2/s25.43
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Proceedings of 23rd International Multidisciplinary Scientific GeoConference SGEM 2023
23rd International Multidisciplinary Scientific GeoConference SGEM 2023, 28-30 November, 2023
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference-SGEM
SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci and Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts and Letters; Acad Fine Arts Zagreb Croatia; Croatian Acad Sci and Arts; Acad Sci Moldova; Montenegrin Acad Sci and Arts; Georgian Acad Sci; Acad Fine Arts and Design Bratislava; Russian Acad Arts; Turkish Acad Sci.
353-360
28-30 November, 2023
website
9618
farm management, IoT (Internet of things), cow’s behavior recognition, LSTM (long short-term memory) neural networks, accelerometer and gyroscope data