Issue №: 2(113)
The journal deals with the problems of vibration technologies and machines, mathematical methods of vibration process studies, information on design and technological development, presents teaching and methodological aspects of teaching in the Higher School of Applied Sciences, where vibration machines and technologies are studied.
PREDICTION AND MONITORING OF ANIMAL HEALTH USING ARTIFICIAL INTELLIGENCE
Olena Solona – Candidate of Technical Sciences, Associate Professor of the Department of Labor Protection and Biotechnical Systems in Animal Production of Vinnytsia National Agrarian University (St. Soniachna, 3, Vinnytsia, Ukraine, 21008, e-mail: solona_o_v@ukr.net, https://orcid.org/ 0000-0002-4596-0449).
Dmytro Lisovyi is a technologist at "Myasny Master" LLC (Vashchuka St., 17, Vinnytsia, Ukraine, 21001, e-mail: lisovoj.dmitry@gmail.com).
Farm animals, which number more than 70 billion worldwide, are increasingly kept on large, intensive farms. Currently, there are no scientifically based “benchmarks” for quantifying transient physiological (affective) states in farm animals, and there are no established indicators, only indicators of poor condition, such as injury, pain, and fear. Traditional approaches to monitoring animal health are time-consuming, interrupt agricultural processes, and involve subjective judgment. Biometric sensor data supported by artificial intelligence is a smart new solution for covert animal monitoring, but its potential for quantifying physiological states and innovative solutions in its application have not yet been realized. This review presents innovative methods for collecting large amounts of data on the condition of farm animals that can be used to train artificial intelligence models to classify, quantify, and predict the physiological states of farm animals. By extending this to the group level, artificial intelligence can be applied to model emotional dynamics and contagion among animals. Digital twin models open up new data-driven approaches to modelling animal behaviour and physiological state. By displaying the information and predictions of the digital twin in an intuitive way on an interactive dashboard, caregivers will be better informed about their animals, enabling them to respond quickly and effectively to reduce pain and ensure animal welfare. Further research in this area can be aimed at developing and improving data analysis algorithms and expanding the range of measured parameters.
1. Solona, O.V., Skoromna, O.I., Ohorodnichuk, H.M. (2023). Zastosuvannia tsyfrovykh tekhnolohii u haluzi tvarynnytstva [Application of digital technologies in the livestock industry]. Tekhnika, enerhetyka, transport APK – Technology, energy, agriculture transport AIC, 4 (123), 43-50 [in Ukrainian].
2. Solona, O.V. (2020). Zastosuvannia suchasnykh mekhatronnykh system ta robotyzovanykh kompleksiv u APK Ukrainy [Application of modern mechatronic systems and robotic complexes in the agricultural sector of Ukraine]. Tekhnika, enerhetyka, transport APK – Technology, energy, agriculture transport AIC, 3 (110), 71-76 [in English].
3. Neethirajan, S., Reimert, I., Kemp, B. (2021). Measuring Farm Animal Emotions Sensor-Based Approaches. Sensors, 21, 553 [in English].
4. Camerlink, I., Coulange, E., Farish, M., Baxter, E.M., Turner, S.P. (2018). Facial expression as a potential measure of both intent and emotion. Sci. Rep, 8, 17602 [in English].
5. Viscardi, A.V., Hunniford, M., Lawlis, P., Leach, M., Turner, P.V. (2017). Development of a Piglet Grimace Scale to Evaluate Piglet Pain Using Facial Expressions Following Castration and Tail Docking: A Pilot Study. Front. Vet. Sci, 4, 51 [in English].
6. Ekici, S., Jawzal, H. (2020). Breast cancer diagnosis using thermography and convolutional neural networks. Med. Hypotheses, 137, 109542 [in English].
7. Cho, Y., Bianchi-Berthouze, N., Julier, S.J. (2017). DeepBreath: Deep learning of breathing patterns for automatic stress recognition using low-cost thermal imaging in unconstrained settings. Proceedings of the 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII). (pp. 23-26), San Antonio, USA. Available online: https://ieeexplore.ieee.org/abstract/document/8273639 [in English].
8. Du, X., Lao, F., Teng, G. (2018). A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry. Sensors, 18, 2906 [in English].
9. Brouwer, A.M., van Dam, E., van Erp, J.B.F., Spangler, D.P., Brooks, J.R. (2018). Improving Real-Life Estimates of Emotion Based on Heart Rate: A Perspective on Taking Metabolic Heart Rate into Account. Front. Hum. Neurosci, 12, 284 [in English].
10. Riaboff, L., Poggi, S., Madouasse, A., Couvreur, S., Aubin, S., Bédère, N. et al. (2020). Development of a methodological framework for a robust prediction of the main behaviours of dairy cows using a combination of machine learning algorithms on accelerometer data. Comput. Electron. Agric, 169, 105179 [in English].
11. Valderas, M.T., Bolea, J., Laguna, P., Bailón, R., Vallverdú, M., Ieee, F. (2019). Mutual information between heart rate variability and respiration for emotion characterization. Physiol. Meas, 40, 084001 [in English].
12. Bovine Expert Tracking and Surveillance. URL:https://www.onecup.ai/betsy [in English].
13. Herd Management. URL:https://store.onecup.ai/ [in English].
14. Farm management platform DeLaval DelPro™. URL:https://www.delaval.com/uk/nashi-rishennya/upravlinnya-fermoyu/ [in English].
15. Vplyv novitnikh tekhnolohii na tvarynnytstvo: zbir danykh z dopomohoiu shtuchnoho intelektu [Impact of new technologies on animal husbandry: data collection using artificial intelligence]. URL: https://zvk.org.ua/blog/vplyv-novitnikh-tekhnolohiy-na-tvarynnytstvo-zbir-danykh-z-dopomohoiu-shtuchnoho-intelektu/ [in Ukrainian].
16. Kamera i shtuchnyi intelekt dopomozhut u vyznachenni i likuvanni kulhavosti VRKh [Camera and artificial intelligence to help identify and treat lameness in cattle]. URL: http://milkua.info/uk/post/kamera-i-stucnij-intelekt-dopomozut-u-viznacenni-i-likuvanni-kulgavosti-vrh [in Ukrainian].
17. Aliiev, E.B., Havrylchenko, O.S. (2018). Sposib otsinky stanu oporno-rukhovoho aparatu velykoi rohatoi khudoby [Method for assessing the state of the musculoskeletal system of cattle]. Naukovi horyzonty – Scientific horizons, 12 (73), 3-7 [in Ukrainian].
18. Tekhnolohiia shtuchnoho intelektu spryiaie ekonomii koshtiv na likuvannia antybiotykamy molochnykh koriv [Artificial intelligence technology helps to save money on antibiotic treatment of dairy cows.] URL: https://www.vetfactor.com/ua/news/tekhnologiya-shtuchnogo-intelektu-spriya-ekonomii-koshtiv-na-likuvannya-antibiotikami-molochnikh-koriv/ [in Ukrainian].
19. Schwartz, S.M., Wildenhaus, K., Bucher, A., Byrd, B. (2020). Digital Twins and the Emerging Science of Self: Implications for Digital Health Experience Design and «Small» Data. Front. Comput. Sci, 2, 31 [in English].
20. Neethirajan, S., Kemp, B. (2021). Digital Twins in Livestock Farming. Animals, 11, 1008 [in English].
21. Brown-Brandl, T.M. (2019). Using RFID in Animal Management and More. J. Anim. Sci, 97, 1-2 [in English].
About journal
The journal "Vibrations in engineering and technology" presents materials on the following issues
• Theory of processes and machines
• Mechanical Engineering and materialprocessing
• Processing and food production
The journal "Vibrations in Engineering and Technologies" is included in the list of technical scientific publications of Ukraine
(Category "B", Order of the Ministry of Education and Science of Ukraine dated July 2, 2020 No. 886)
Old version of the site: http://vibrojournal.vsau.edu.ua/
The journal "Vibrations in Engineering and Technology" is indexed by the following databases and catalogs:
The certificateof massmedia State registration:kv no 16643-5115 from 30.04.2010 .
Founder of the journal: Vinnytsia National Agrarian University
Kind of publication: journal
Type of publication : Scientific
Publication status: Domestic
Year of founding:
Periodicity: 4 times a year
Extent: 18.75 nominal printed pages
ISSN: 2306-8744 (printed version), (online)
Language of edition : (mixed languages) Ukrainian, English
The scope of the distribution and the category of readers: national, foreign, teaching staff, scientists, businessmen.
Periodical is included in the list of scientific professional editions of Ukraine approved by the Order of Ministry of Education and Sciences of Ukraine from 21.12.2015 No. 1328.
The journal "Vibrations in engineering and technology" is included in the "Catalogue of periodicals of Ukraine".
Journal subscription can be executed in each post office department.
Subscription Index is 99720.
Old version of site: http://vibrojournal.vsau.edu.ua/
In June 1994 the 2nd International Scientific and Technical Conference "Application of vibrations for technological purposes" was organized on the basis of Vinnytsia State Agricultural Institute. Leading experts in this field, noting the significant contribution to the school of Vibration Engineering under the leadership of P. S. Bernyk, proposed to create a professional all-Ukrainian scientific and technical journal "Vibration in engineering and technology..The journal was foundedat Vinnytsia State Agricultural Institute and P.S. Bernyk was elected to be the chief editor .
For all these years (since 1994) theJournal "vibration in engineering and technology" published 94 issues wherestudy of vibration effects, the creation of progressive energy saving technologies and equipment for their implementation were highlighted.
Currently Kaletnik H.M PhD , professor, academician NAAS is the chief editor of the "Vibrations in engineering and Technology"
The journal "Vibration in Engineering and technology", which has no analogues on the territory of Ukraine, is well known abroad.
