The Internet of Things comes to the aid of Tatarstan's cows

How new technologies help in dairy farming on the example of a farm in Khabarovsk

The trend of introduction of modern technologies, is reaching the agro-industrial sector, which opens the Internet of Things for livestock breeding complex. Now farmers of the republic have the opportunity track the health and condition of cows with the help of sensors, information from which is sent online to the computers of the dairy complex. About how to optimise work in the field of agriculture on the example of a farm in Khabarovsk — read in the material of Realnoe Vremya.

IT for agricultural sector

International experience shows that the use of new technologies increases the efficiency of farms by 15-25%. In Russia, the introduction of innovations in the agricultural industry is only gaining momentum today. According to PwC, the share of domestic enterprises using modern technologies is no more than 10%. But in the future 3-5 years, their number may multiply. According to the ministry of agriculture of Russia, the Russian market of digital technologies in the agro-industrial sector is 360 billion rubles, and in 6 years it is going to increase fivefold. The Internet of Things can be useful in almost all areas of agriculture, and it inevitably comes there.

One of the companies that are already practicing the use of new technologies is a farm in Khabarovsk. Oleg Borisov, the chairman of Blagodatnoye agricultural production cooperative in Khabarovsk, notes that the decision to use state-of-the-art equipment for effective work was made at the stage of creating the microenterprise, which has operated since February 2019. Then a video surveillance from MTS was installed in the farm in the cowshed, and another development of the company has recently been introduced — smart sensors that control the dairy farm. The mechanics are simple — a cow swallows a bolus connected to a cloud service. It tracks the needs of each individual animal and its condition, promptly sending information to the operator.

MTS Smart Farming sensors stay there for the rest of the animal's life after they get into its stomach. The system assumes a complex solution of issues. In real-time mode, 24 by 7, they can use them to monitor the health of the cow, getting information about possible diseases even before the stage of their manifestation, control heat and water stress, automatically detect estrus and calving. For employees, the system automatically generates work tasks and records them. The owner and manager of the dairy farm have access to cloud storage, where all information is received.

“Our cooperation began with the installation of video surveillance in the cowshed. We were satisfied with the results, so we decided to take advantage of the company's new offer to monitor the health of animals and the work of employees. The use of new technologies eliminates the human factor in production management and gives the opportunity to control all processes remotely, literally in real time. We decided to implement the development because we care about the health of our animals and pursue the goal of using all resources economically and efficiently," said the source of the publication.

Complex work

To implement the technology, the customer only needs to set detailed tasks, and the developer team does everything else.

“We have selected the animals that will be brought into the system, selected a suitable room for examination, to understand how to place the equipment. We needed to have a computer with the Internet — and that's all: MTS did everything else — the installation of the system, training of personnel on a turnkey basis," says Oleg Borisov, the chairman of Blagodatnoye.

To be more precise, the company does all the calculations itself, deploys networks, installs boluses, and configures software. Moreover, it leads its clients for at least six months after that, helping to debug all processes, optimise approaches to work, and even find weak points in the farm's functionality to work through them together.

Blagodatnoye is currently testing the new technology, the economic effects of which can be assessed closer to the end of the year. There are also plans to expand the number of livestock with “smart” sensors.

Reducing costs and increasing production volumes

As test studies have shown, the technology can detect a cow disease five days before symptoms appear, and the nearest calving — 15 hours. Thanks to diagnostics, treatment can be started earlier, using by 15% less medication. A more efficient reproduction planning leads to higher yields. The service period can be shortened from the average Russian 150 days to 90 days. As a result, milk production increases by very significant indicators, which in the case of large enterprises are estimated in the hundreds of thousands of tonnes of milk a year.

In Tatarstan, the new solution was presented on Field Day.

“I am sure that in the region, which is the leader in dairy production, technologies in the agro-industrial complex can provide significant support in the development of this direction. According to the estimates of the Analytical Centre of the ministry of agriculture of Russia, the use of big data technologies, “agrotechnical” Internet of Things, artificial intelligence and machine learning can double the efficiency of the Russian agro-industrial complex and reduce the cost of production and storage of agricultural products by 15%," comments Marat Shakirov, the director of the MTS branch in the Republic of Tatarstan.

The use of such technologies is particularly relevant in connection with the spread of the new coronavirus. The measures introduced in this regard — the regime of self-isolation, social distance — have led to an increase in the risks of stoppages in production processes. The material prepared in conjunction with MTS, on the specific example, reveals how it systems come to the aid of enterprises in organising the work of personnel and remote monitoring of the condition of animals, adjusting the microclimate in the premises for keeping the herd.

By Maria Gorozhaninova

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