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Agriculture plays a pivotal role in the development of world civilization, especially for Chinese civilization.
For example, the evolution of production tools in various dynasties, the construction of water irrigation projects, the advancement of farming and management technologies, and the expansion of regions. We can learn “emphasis on agriculture and restrain business” from history textbooks very early, and appreciate the importance that the rulers of the dynasty paid to agriculture.
But today, with the increase of social productivity and the increase of grain output, the variety of commodities is becoming more and more abundant. For agriculture, the seller's market has gradually transformed into a buyer's market. The situation of unsalable agricultural products has occurred from time to time, and agricultural innovation has developed Facing a huge test.
Food demand growth: As the global population increases and quality needs increase, food demand also rises. Decrease in the number of experts: The profitability and attractiveness of the industry are very low, resulting in a continuous decrease in the number of experts that the industry can rely on. Low efficiency: The cultivation of traditional cereals, vegetables and fruits, as well as the cultivation of animal husbandry , face the problems of low efficiency, market illiquidity, and insufficient information openness. High-yield risks: sowing and harvesting, birth and slaughter, time periods like this, and increasing climate change are all bringing great uncertainty to the future profit of agricultural products.
Farmers are no longer a status symbol, but an equal profession. And this very ancient industry in the history of civilization is being combined with technology to explode more vitality.
准农业是物联网在农业著名的应用之一，适用于大面积作物种植。 Fine . Quasi-agriculture is one of the well-known applications of the Internet of Things in agriculture, suitable for large-scale crop cultivation. Today we will use it to understand the application of the Internet of Things in agriculture .
准农业的概念可以归纳为三个层面：数据的采集、分析与应用。 Abandoning some of the concepts of the mouth pass, in essence, the concept of precision and quasi-agriculture can be summarized into three levels: data collection, analysis and application. This is true for all IoT applications .
准农业很受欢迎的三项技术。 The United States "National Geographic" magazine has published an analysis of three popular technologies that are very popular in quasi-agriculture.
Soil and yield mapping
Variable-rate technology-Variable-rate tech
“土壤与产量制图”与“农业数据的采集” 1. "Soil and Yield Mapping" and "Agricultural Data Collection"
Commonly, farmers grid the farmland according to the shape and size, collect soil samples of each grid, and analyze the chemical properties of soil structure and nitrogen content to draw a map. You can know which grid needs more watering from the map. Which one needs more fertilizer.
Collecting data with sensors is another way we can easily think of. A large number of sensors are deployed in the farmland, allowing them to obtain environmental parameters automatically and in real time. However, there are many types of parameters that need to be detected in crop planting. The single-point data obtained by the sensors is difficult to present the overall appearance of the farmland.
So you can also talk about drones. Drones collect multispectral, thermal, and visual images during flight. These image information are processed and can show results such as crop monitoring, field analysis, land imaging, and mapping.
The same goes for yield mapping. Intelligent mechanical equipment for harvesting crops, equipped with GPS system and yield monitor, collect geographic location information while harvesting crops, and use data to reveal yield changes in each area of farmland.
By combining these new and old methods, farmers can obtain the current parameters of farmland, analyze the data and take corresponding measures.
“指导系统”与“3S技术” 2. "Guiding System" and "3S Technology"
3S refers to RS, GPS, GIS.
RS is remote sensing. It does not touch the object itself. It collects the electromagnetic wave information of the target with a sensor, and identifies the target after processing and analysis. The role is to provide basic image information. GPS is a global positioning system that determines image location information. GIS is a geographic information system. The processed image is entered into GIS and can be used for subsequent data management and application analysis.
At present, 3S has become a widely used technology in modern surveying and mapping.
In the agricultural scenario, a GIS system is introduced into intelligent agricultural machinery. During operation, the GPS system will map the real-time operation status of the machine to the GIS information. This can greatly improve efficiency, achieve more efficient operation paths, and be more accurate. Sowing irrigation. This is also a technology that is used very frequently in agriculture.
可变速率技术--VRT技术 3. Variable rate technology-VRT technology
Variable rate technology (VRT) allows farmers to optimize the input of each part of the field, plant different types and quantities of seeds where needed and at the time, and place the right amount of fertilizers and pesticides.
This technology needs to be deployed in machinery and equipment, and coordinated with GIS when applied. But at present, the cost of VRT is high and the adoption rate is relatively reduced.
What we talked about above is suitable for large-scale crop cultivation, and the system is relatively complicated, and the cost of a system is relatively high. However, the subsequent benefits will outweigh the input costs. The larger the planted area, the faster the cost can be recovered.
Other applications of the Internet of Things in agriculture
For example, the breeding of poultry and livestock can be divided into three levels.
Monitor animal vital signs through sensors to ensure no disease; In some cases of wide-area grazing, use position sensors or GPS to track the position of animals such as cows and sheep to reduce loss and improve management efficiency; more accurate through sensor data monitoring Predict and schedule milking times and slaughter dates to maximize yields.
Another wave of magical operations is that last year, the University of Wageningen, a well-known Dutch institution of higher learning, launched an international artificial intelligence greenhouse planting contest-cucumber cultivation for the global artificial intelligence team.
Wageningen University provides cucumber growth data. The participating teams use the original data to create models. On the one hand, they collect real-time data through tools such as sensors and cameras. On the other hand, artificial intelligence algorithms make decisions based on the data and control the "operation parameters" in the greenhouse. Such as light, temperature and humidity , ventilation, watering irrigation, etc., completely reduce human intervention.
Then we saw the results map of Tencent AI cucumber.
Enterprises join the " Agricultural Internet of Things "
Which companies participate in the above-mentioned "AI + Agriculture" competitions? Microsoft, Tencent, Intel, etc ...
It can be said that there are more than "a few" enterprises that pay attention to agriculture.
In 2018, Ali launched an artificial pig raising project, 200 kilometers of pigs, emphasizing the meat texture of pork. Hu Xiaoming, who was also the president of Aliyun at the time, said that the kilometer of pig movement will become a new standard for judging the quality of pork.
In this project, the camera image recognition technology can automatically collect the pig's body shape data and record the distance, time and frequency of each pig's movement; the acoustic characteristics and infrared temperature measurement technology can identify the pig's body temperature, call, and determine whether it is sick Early warning of the epidemic situation; the collected data will be collected on the cloud platform to form a data file for each pig for data analysis and measures.
JD.com also launched the “running chicken” project earlier, emphasizing the full-term safety chicken that runs one million steps.
In this project, the key equipment is a foot ring tied to each chicken (this foot ring must ensure that the recorded steps are accurate, the steps are visible in real time, and there will be no physical damage during breeding). The sensor is implanted inside the foot ring, and the bionic step counting algorithm conforming to the biological characteristics of birds is applied; and the LoRa / NB-IoT low-power IoT communication technology is used for signal transmission to ensure that the foot ring does not lose power midway; then the data passes The gateway reaches the cloud platform and analyzes and processes various data on the platform.
Huawei has also launched a NB-IoT-based cattle networking project with partners, which mainly solves the problem of too low efficiency of dairy cows' estrus monitoring and affecting the milk production of dairy farms. What is done is to achieve timely breeding of cows and accurately monitor the estrus of cows.
Future development of the agricultural Internet of Things
The key to development is efficiency.
Back to the key issue of efficiency, we can look at it in two ways.
1. Improve agricultural production efficiency and diversify production, distinguish agricultural products from low-margin commodities;
2. If necessary, you can also add modern development thinking such as "branding, premium enhancement, refined operation, and Internet service".
Using science and technology to improve efficiency and channels to build markets, agriculture, as an important industry, will continue to develop.