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Agricultural Big Data Due to the Agricultural Internet of Things —— 【Xinxin IoT】

来自: 成都鑫芯电子科技有限公司 浏览次数:2045 2017-03-15From : Chengdu Xinxin Electronic Technology Co., Ltd.Browse Times: 2045

For agricultural big data , each of us has a different understanding, but for the current technical level of the agricultural Internet of Things , we still need a correct and deep understanding and understanding of agricultural big data .

Our agricultural experts believe that China's agricultural production has reached a very critical time. Nowadays, agricultural resources are not able to grow the land, but the population is still growing rapidly. And the rural labor force is very old. Who will grow the land and raise pigs in another 20 years? This is a key issue. So what should we do in this case? There is only one way out to make farming and cultivation intelligent. How can we achieve intelligent farming and cultivation? Then we need to be precise. Only by realizing the precision of data collection and control can we achieve high-efficiency, high-yield land without pollution and harm to the environment. To be precise, the core technology is agricultural big data.

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Agricultural big data. First, it is necessary to rely on big data of biological information to achieve excellent varieties and disease-free. The key to solving this problem is genetic technology. Which gene is good? Kilograms of tomatoes. Big data, one is the production of agriculture, and the other is the change in the shape and disease of animals and plants. The second is precision production. How can it be matched well? Large amounts of macro and micro data need to be combined. Agricultural big data is the largest data in the world, because agriculture involves both humans, animals, water, soil, air, and so on. The country realizes how we can achieve precise production, and the market will not have such a big twist. Just because there is no data.

Chinese agricultural experts believe that the current agricultural big data mainly comes from four aspects: the Internet of Things technology ; biological information data; resources and environmental data; agricultural statistics.

The key technology of agricultural big data: data collection. The automated collection of data makes the Internet a key core role. Where is the data stored? How to store efficiently? This is cloud computing technology, available on demand. Various data processing methods, such as stream processing and batch processing. Data analysis and mining, how to get from the piglet to the kill, what formula, how much water, protein, water, fat is given to it in the process, so that it grows fast, so the linked data comes first, including visual data, Tabular data, analysis and processing of these data.

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There are five main applications of agricultural big data:

1. Basic research. The core of basic research, whether it is pigs, cattle, sheep, fish, rice grains, how can the excellent shape be associated with its output? How to correlate phenotypic analysis data with genetic analysis research data, and screen out the corresponding genes to make it high yield and good quality? This requires the support of agricultural big data.

2. Intelligent agricultural production. Intelligent aquaculture production is typical of agricultural production. On the one hand, it is prediction and early warning; on the other hand, it is optimized and controlled. For example, why can two people raise 150,000 chickens and put 140,000 eggs a day? This depends on when the chicken is fed, how many times it is fed, how the feces are handled, how the eggs are picked, and how the eggs are packed. This piece is the only way to solve the future of Chinese agriculture , and the key to it is big data.

3. Market forecast and logistics. Link data from all over the country to predict market conditions and logistics information for the coming year.

4. Agricultural product quality and safety . Use big data to explain the safety of agricultural products, establish a traceability system for agricultural products, and establish a database of various consumer behaviors of producers, citizens, and producers.

5. Resources integration and sharing and services. China should share big data systems in various places in order to more accurately analyze data resources in various places and make corresponding countermeasures.

Problems facing China's agricultural big data:

1. Lack of agricultural big data.

2. Big data models lack long-term accumulation.

3. The lack of agricultural big data integration with industry.

4. Agricultural big data lacks necessary specifications.


March 15, 2017

Chengdu Xinxin Electronic Technology Co., Ltd. Editorial Department

Editor: Little Devil in Gourd

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