Авторы

  • Kh.I. Toliev
    Tashkent University of Information Technologies named after Muhammad al-Khwarizmi

DOI:

https://doi.org/10.71337/inlibrary.uz.arims.86982

Аннотация

The application of innovative technological solutions and the automation of various processes in the national economy are of crucial importance in addressing the shortage of natural resources and emerging global challenges associated with the world's growing population. In light of this, the emergence of the concept of the fourth industrial revolution (Industry 4.0) aims to support efficient and sustainable production by integrating advanced digital technologies, tools, and resources. The rapid development of Industry 4.0 represents a true solution to these pressing issues.


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ACADEMIC RESEARCH IN MODERN SCIENCE

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DAIRY 4.0 AND ITS DEVELOPMENT PROSPECTS

Toliev Kh.I.

Tashkent University of Information Technologies

named after Muhammad al-Khwarizmi

https://doi.org/10.5281/zenodo.15387522

The application of innovative technological solutions and the automation of

various processes in the national economy are of crucial importance in addressing
the shortage of natural resources and emerging global challenges associated with
the world's growing population. In light of this, the emergence of the concept of
the fourth industrial revolution (Industry 4.0) aims to support efficient and
sustainable production by integrating advanced digital technologies, tools, and
resources. The rapid development of Industry 4.0 represents a true solution to
these pressing issues.

Industry 4.0 enables real-time internet connectivity for various layers of

data sources and allows for fast and efficient processing of large volumes of data.
This ensures rapid production of high-quality products that meet demand in
manufacturing and facilitates integration between different systems. Industry 4.0,
which incorporates numerous advanced sensor technologies, can improve the
technological structure of the dairy sector, an important link in the food industry.

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In line with the development of industrial generations, new principles such

as PLF (Precision Livestock Farming), PDF (Precision Dairy Farming), SFM (Smart
Farming Management), and Dairy 4.0 with modern technological support are
emerging in the livestock sector over the next decade. These principles offer
significant opportunities, including automatic manure cleaning in farm buildings,
microclimate control, remote identification and inventory of cattle through
electronic chips, collection of information about objects via non-invasive and
invasive sensors and IoT devices, robotic control, optimal feeding tailored to
individual animals, monitoring milk parameters during the milking process, early
detection of cattle diseases, application of artificial intelligence tools based on big
data, effective breeding and decision-making, and most importantly, reducing
human intervention and managing resource efficiency through online
management.

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,3].

In particular, the

adoption of these innovative technologies in line with Industry 4.0 has led to the
establishment of new dairy farms known as "Dairy 4.0."

The developmental stages of the dairy industry are distinguished from one

another by several characteristics, including the technologies employed, methods
of implementing feed and breeding practices, data analysis techniques, and the


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farm's environmental impact. Below, we will explore the distinctive features of
the periods from Dairy 1.0 to Dairy 4.0, as well as the key components of Dairy
4.0.

Figure 1.

Dairy 1.0 (Traditional)

dairy farming employs a conventional approach

with minimal automation, relying primarily on manual labor. Animal feeding,
milking, health monitoring, and breeding processes are conducted based on
human observation and intervention. Furthermore, there is minimal attention to
environmental impact, limited veterinary services, and the collection and
management of records are predominantly carried out manually using paper-
based systems.

Dairy 2.0 (Mechanized)

represents the modernization era of the dairy

industry. It primarily involves implementing key mechanization methods to
reduce human labor on farms. Practices such as ration-based feeding of farm
animals, controlled breeding, and improved healthcare protocols have been
introduced. While records are still maintained on paper, the requirements for
data management and collection have evolved, incorporating the results of
scientific research.

Dairy 3.0 (Automated)

is characterized by this period of dairy farming and

the introduction of milking machines and specialized mechanisms. This phase
involves implementing improved feeding practices, artificial insemination and
effective breeding management, ensuring optimal microclimate conditions,
reducing the farm's environmental impact, disease detection and management, as
well as, most crucially, maintaining electronic records and conducting data
analysis.

Dairy 4.0 (Smart Farm)

represents the most advanced stage of the dairy

industry, integrating modern technologies to optimize all processes, manage the
farm territory technologically, ensure sustainability, and minimize negative


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environmental impacts. The essential components that constitute the 4th
generation of the dairy industry are shown in Figure 2, and their important
aspects will now be examined.

2-rasm.

Dairy 4.0 ni tashkil qiluvchi komponentlar

Robotics

is one of the latest developing technologies in the dairy industry,

which includes robotic automatic milking systems, waste removal systems, and
individual cattle feeding systems. In particular, automatic milking systems allow
for a significant increase in milking frequency and productivity by reducing labor
costs

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while manure removal systems

help prevent risks to cow health and reduce ammonia gas emissions. Sensors
installed in robotic systems enable the collection of accurate real-time data

[4],

which can be used to analyze daily milk yield and parameters, as well as predict
important values (Figure 3).


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Dairy Robotics systems

Automated Milking

systems

On-floor

cleaning

Benefits of robotics

Increased milking

frequency

Increased

productivity

Accurate and real-time

collection of data

Figure 3.

The role of robotic systems in the dairy industry

3D printing

is a production system that allows for controlling the shape

and structural ingredients of food products, as well as meeting individual
nutritional requirements

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Currently,

this is being used in the production of meat and meat analogues, egg whites, and
protein products

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The scope of 3D

printing in dairy products is primarily characterized by the following five key
concepts: innovative, futuristic, healthy, efficient, and sustainable.

Big Data

methods bring significant benefits to dairy farms (Figure 4),

including improving dairy farm management, predicting milk productivity,
enhancing quality and quantity, and facilitating both operational and strategic
decision-making

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BigData helps

identify and predict milk productivity and diseases at both individual cow and
herd levels, assists in herd formation, and contributes to improving farm
profitability. BigData is formed as a result of collecting and integrating various
property data of real-time objects into a central database. Currently, important
studies in farm practices are achieving successful results, such as forming
nutritional groups, assessing animal health, predicting early clinical mastitis and
lameness, and obtaining maximum profit with minimal costs.


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Figure 4.

Benefits of Big Data for the dairy industry

IoT (Internet of Things)

is a standalone operational tool that enables the

collection of various real-time data about objects, performs initial processing, and
transmits this information to computing nodes in a communication environment.
For instance, IoT devices that monitor cows' temperature, heart rate, and
movement patterns provide information about their health, location, and activity
levels

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IoT applications vary

depending on the issue being addressed, but their operating mechanisms are
almost identical. They typically consist of a complex including sensors, connection
to a communication network, memory, control and processing board, power
source, motor drive, and information input and output components. Data
obtained from the sensors are recorded in memory, initially processed, compared
with standards, and, if necessary, messages are transmitted to other nodes. In
animal husbandry, IoT tools are used for animal monitoring, health control, and
automation of farming operations.

Artificial intelligence (AI)

is primarily used to assess the health and well-

being of dairy animals for milk productivity

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In this case, AI simplifies the decision-making processes by utilizing a

range of data sources about an individual, from highly important to seemingly
unnecessary information gathered from rarely used source. AI determines the
requirements for effective cow management based on physiological and
environmental factors, which helps ensure high-quality milk production. Dairy
4.0 utilizes AI to improve product quality, meet customer demands, and enhance
dairy farm practices.

Blockchain

is a new technology that is rapidly penetrating various fields.

This technology enables customers to track the production and quality of their
products. Blockchain technology is being applied in the development of smart
ecosystems for milk supply chains to help provide sustainable and safe food for


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the growing global population. In her research study, Mangla investigated how
blockchain technology can be utilized to enhance the social sustainability of milk
supply chains in Turkey

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].

They have

identified several advantages of this technology, including preventing food fraud,
developing rural areas, protecting animal welfare and health, and ensuring food
security.

In conclusion, the Dairy 4.0 concept represents a crucial step towards

digitalization and automation in the dairy industry. Its implementation not only
enhances production efficiency but also strengthens food security, protects the
environment, and enables more effective utilization of human resources. In the
future, as a result of integrating technologies such as artificial intelligence and
blockchain in this direction, "smart farms" are expected to develop further,
leading to the emergence of sustainable and cost-effective systems that meet the
demands of the global dairy market.

References:

1.

Malik, M., Gahlawat, V.K., Mor, R.S. and Hosseinian-Far, A. (2024). Towards

white revolution 2.0: Challenges and opportunities for the industry 4.0
technologies in Indian dairy industry. Operations Management Research. pp.1-22.
2.

Hogenboom, J.A., Pellegrino, L., Sandrucci, A., Rosi, V. and D’Incecco, P.

(2019). Invited review: Hygienic quality, composition and technological
performance of raw milk obtained by robotic milking of cows. Journal of Dairy
Science. 102: 7640-7654.
3.

Babajanov B. S. Aproblems and solutions of organizing smart livestock

farms //Central Asian Journal of Education and Computer Sciences. – 2022. – Т. 1.
– №. 4. – С. 6-19.
4.

Bhoj, S., Tarafdar, A., Singh, M. and Gaur, G.K. (2022). Smart and Automatic

Milking Systems: Benefits and Prospects. In: [Gaur, G.K. (Ed.)], Smart and
Sustainable Food Technologies. Springer Nature Singapore Pte Ltd. pp 87-121.
5.

Toliev, K. (2024). Architecture and priority issues of intelligent milking

system on the farm. DTAI–2024, 1(DTAI).
6.

Sun, J., Peng, Z., Yan, L., Fuh, J.Y. and Hong, G.S. (2015). 3D food printing-An

innovative way of mass customization in food fabrication. International Journal of
Bioprinting. 1(1): 27-38.
7.

Lee, J. (2021). A 3D food printing process for the new normal era: A review.

Processes. 9: 1495. https://doi.org/10.3390/ pr9091495.
8.

Cabrera, V.E., Barrientos-Blanco, J.A., Delgado, H. and FadulPacheco, L.

(2020). Symposium review: Real-time continuous decision making using big data
on dairy farms. Journal of Dairy Science. 103: 3856-3866.


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9.

Chaudhry, A.A., Mumtaz, R., Zaidi, S.M.H., Tahir, M.A. and School, S.H.M.

(2020). Internet of Things (IoT) and machine learning (ML) enabled livestock
monitoring. In 2020 IEEE 17th International Conference on Smart Communities:
Improving Quality of Life Using ICT, IoT and AI (HONET). Pp 151-155.
10.

Cheng, C., Fu, J., Su, H. and Ren, L. (2023). Recent advancements in

agriculture

robots:

Benefits

and

challenges.

Machines.

11:

48.

https://doi.org/10.3390/machines11010048.
11.

Zhang, L., Guo, W., Lv, C., Guo, M., Yang, M., Fu, Q. and Liu, X. (2024).

Advancements in artificial intelligence technology for improving animal welfare:
Current applications and research progress. Animal Research and One Health.
2(1): 93-109.
12.

Mangla, S., Kazancoglu, Y., Ekinci, E., Liu, M., Özbiltekin, M., Sezer, M. (2021).

Using system dynamics to analyze the societal impacts of blockchain technology
in milk supply chains. Transportation Research Part E: Logistics and
Transportation Review. 149: 102289. https://doi.org/10.1016/j.tre.2021.
102289.

Библиографические ссылки

Malik, M., Gahlawat, V.K., Mor, R.S. and Hosseinian-Far, A. (2024). Towards white revolution 2.0: Challenges and opportunities for the industry 4.0 technologies in Indian dairy industry. Operations Management Research. pp.1-22.

Hogenboom, J.A., Pellegrino, L., Sandrucci, A., Rosi, V. and D’Incecco, P. (2019). Invited review: Hygienic quality, composition and technological performance of raw milk obtained by robotic milking of cows. Journal of Dairy Science. 102: 7640-7654.

Babajanov B. S. Aproblems and solutions of organizing smart livestock farms //Central Asian Journal of Education and Computer Sciences. – 2022. – Т. 1. – №. 4. – С. 6-19.

Bhoj, S., Tarafdar, A., Singh, M. and Gaur, G.K. (2022). Smart and Automatic Milking Systems: Benefits and Prospects. In: [Gaur, G.K. (Ed.)], Smart and Sustainable Food Technologies. Springer Nature Singapore Pte Ltd. pp 87-121.

Toliev, K. (2024). Architecture and priority issues of intelligent milking system on the farm. DTAI–2024, 1(DTAI).

Sun, J., Peng, Z., Yan, L., Fuh, J.Y. and Hong, G.S. (2015). 3D food printing-An innovative way of mass customization in food fabrication. International Journal of Bioprinting. 1(1): 27-38.

Lee, J. (2021). A 3D food printing process for the new normal era: A review. Processes. 9: 1495. https://doi.org/10.3390/ pr9091495.

Cabrera, V.E., Barrientos-Blanco, J.A., Delgado, H. and FadulPacheco, L. (2020). Symposium review: Real-time continuous decision making using big data on dairy farms. Journal of Dairy Science. 103: 3856-3866.

Chaudhry, A.A., Mumtaz, R., Zaidi, S.M.H., Tahir, M.A. and School, S.H.M. (2020). Internet of Things (IoT) and machine learning (ML) enabled livestock monitoring. In 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET). Pp 151-155.

Cheng, C., Fu, J., Su, H. and Ren, L. (2023). Recent advancements in agriculture robots: Benefits and challenges. Machines. 11: 48. https://doi.org/10.3390/machines11010048.

Zhang, L., Guo, W., Lv, C., Guo, M., Yang, M., Fu, Q. and Liu, X. (2024). Advancements in artificial intelligence technology for improving animal welfare: Current applications and research progress. Animal Research and One Health. 2(1): 93-109.

Mangla, S., Kazancoglu, Y., Ekinci, E., Liu, M., Özbiltekin, M., Sezer, M. (2021). Using system dynamics to analyze the societal impacts of blockchain technology in milk supply chains. Transportation Research Part E: Logistics and Transportation Review. 149: 102289. https://doi.org/10.1016/j.tre.2021. 102289.

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