Abstract
In the era of fourth industrial revolution or Industry 4.0 together with the second information and communication technology era, the way we human beings live, act and do are always challenging by the waves of new technologies such as Internet of Things, Artificial Intelligence, Cloud Computing so on and so forth. These new technologies also drive life science, academic, business and production industries for better sides. Among them, one of challenging and innovative technology in life science industry is precision dairy farming which has been pushed into frontline topic among the academia and industry farm managers. Generally speaking, the precision dairy farming can be defined as the use of technologies advanced or simple to analyze the physical and mental behaviors of an individual cows for specifying health and profitability indicators so that overall management and farm performance are to be improved. In other words, the precision dairy farming will focus on welfare and health care for making the farm returns optimal through the use of technologies. Here, technologies may range from daily milk recording to automatic body conditions scoring for individual cows and an accurate prediction of calving time and reporting unusual occurrences during the delivery times.
In order to realize the objectives of precision dairy farming as a fundamental step, a hybrid visual stochastic approach which is a fusion of image technology and statistical method to dairy cow monitoring system is introduced in this paper. The proposed system will investigate four key areas for the precision dairy farming namely: cow identification, body condition scoring, detection of estrus behavior, prediction of time for the occurrence calving event. In doing so, the combination of image technology, statistical methods and stochastic models will be utilized. Specifically, image processing methods will be performed to detect cow activities such as standing, lying and walking in association with time, space and frequencies. Then collected data are to be transformed into a stochastic model of special type of Markov Chain for decision making process. Then some experimental results will be shown by using both image and statistical data collected from the real life environments and some available datasets.
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Acknowledgment
This work was supported in part by SCOPE: Strategic Information and Communications R&D Promotion Program (Grant No. 172310006) and JSPS KAKENHI Grant Number 17K08066.
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Zin, T.T., Tin, P., Kobayashi, I., Hama, H. (2020). A Hybrid Visual Stochastic Approach to Dairy Cow Monitoring System. In: Ao, SI., Kim, H., Castillo, O., Chan, As., Katagiri, H. (eds) Transactions on Engineering Technologies. IMECS 2018. Springer, Singapore. https://doi.org/10.1007/978-981-32-9808-8_10
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DOI: https://doi.org/10.1007/978-981-32-9808-8_10
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