What is smart agriculture?

With the rapid integration of a new generation of information technology into traditional industries, agricultural digitalization, networking and intelligence have gradually become the cornerstone of agricultural modernization. Relying on cloud computing, 5G, Internet of Things and other technologies, various sensor nodes and communication networks deployed in agricultural production sites can realize intelligent perception, intelligent early warning, intelligent decision-making and intelligent analysis of agricultural production environment. Combined with the current rural revitalization strategy and large-scale rural land transfer, it provides accurate guarantee, high-quality operation level and intelligent decision support for agricultural production.

Agriculture 4.0 is a highly intensive, highly intelligent, highly collaborative, highly accurate and highly ecological modern agricultural form supported by technologies such as big data, Internet of Things and AI. The smart farm visualization solution supports multi-link business covering farm planning, production and circulation, promotes the efficiency, perception and controllability of the whole application process of agricultural drones and automation equipment, improves the refined management level of farms, the quality and efficiency of agricultural machinery operations, and creates intelligence. Unmanned and efficient.

Using zero code to build a 3D lightweight smart farm, the regional panorama, the collective distribution of farms and villages and the corresponding environment are diversified and visualized around four dimensions: plot overview, sowing analysis, cattle management and equipment inquiry, and supported by data, which can also provide practical reference information for sowing and management. Turning "number" into "thing", through integrating the data of agricultural projects and business systems, the goals of rational utilization of agricultural resources, reducing production costs, improving ecological environment and improving crop products and quality have been realized.

The data analysis page of the agricultural management visualization analysis chart shows the farmland statistical information, quarterly sowing ratio, agricultural machinery and project number of each farm in detail. With clear and detailed data, it reflects the agricultural situation of each farm and provides more accurate basis for farm management and decision-making.

The smart agriculture solution takes each block as the monitoring unit, based on the HT for Web visual graphic engine independently developed, and relies on the spatial and regional distribution characteristics and laws of cultivated land fertility to build a plot interface control scene.

In the map scene, the land types of 10 farms are displayed, which are divided into cultivated land, woodland, grassland, building land, industrial land, commercial land, residential land, public facilities land, water area and park. Different land types are displayed in different colors. For example, after clicking the farmland button on the left side of the page, only the farmland situation of all farms will be displayed in the scene. Users can view it more directly and see the distribution position of all farmland at a glance.

On the 2D data analysis interface, the statistical data of agriculture, forestry and grassland of 10 farm, the land area of management right, the ranking of commercial land proportion, land certificate and the statistical data of each area are dynamically displayed in real time. Based on this, users can compare each farm and understand the management and development potential of each farm. Rich chart components simplify the data, save users a lot of search time, and realize the precise command of "one map".

Satellite data observations of various plots and cultivated crops can be superimposed and displayed in a 3D scene. Users can clearly see which crops are planted on this cultivated land by observing the colors and icons of the plot. Or roll the mouse pulley to enlarge, and you can clearly see the plot code of the planting plot. After the observation of satellite data, the plot layers are classified by color superposition;

■ Ground temperature state: Visually monitor the ground temperature threshold, overlay the soil temperature remote sensing layer in the 3D scene, and select different colors for different temperature stages, so as to see the abnormal ground temperature area at a glance. Combined with the monitoring and early warning function of the system, it helps users to find possible problems and risks in time and take corresponding measures to prevent and solve them.

■ Microbial activity: clearly distinguish the changes of microbial activity values in different blocks through different color blocks. As a key index, the change of microbial activity reflects the health status of soil and the vitality and activity of microorganisms in soil. Visual monitoring can better evaluate soil quality and ecosystem health.

■ Crop development prediction: predict the future development state of crops or possible changes in the growth process through visualization. It is beneficial for users to sow crops in different rows and provide scientific basis for agricultural production quality monitoring.

■ Crop distribution and yield forecast: display local block names and future output value forecast to help users understand the yield forecast of vertical farms more intuitively.

The use of satellite data observation technology is completely changing plant science research. By providing plant-based phenotypic data, various analyses can be applied to digital twin scenes, and the characteristics of crops in the whole planting season can be measured with centimeter-level accuracy. Help users to monitor crops and soil in real time from macro to micro, so as to get the maturity speed and periodic change of plants more accurately.

For the monitoring details of each plot, please click on the relevant plot to view the planting details, including the information list of crops, nutrient elements of each farm land, crop yield estimation information and other indicators. Help farmers and herdsmen to strengthen their understanding of crop behavior in a specific environment.

The map scene of animal husbandry and cattle management shows the three-dimensional model of Tes cattle farm, Ira cattle house and Boer cattle farm. Accurately locate each pasture through HT for Web GIS, and click the corresponding pasture name in the 3D panel to switch to the corresponding location.

Double-click the corresponding pasture to jump to the analysis interface of the pasture, and the displayed data information includes: cow data, breeding quantity ranking information, cow pairing times and cow reproduction record map. The dynamic diagram and 2.5D configuration diagram were used to summarize and analyze the cattle breeding data. Through data cloud and mobile office, the requirements of remote visualization, transparent production and scientific management of pasture are realized, and the production efficiency and performance of pasture are effectively improved.

Agricultural machinery and equipment inquiry is deeply integrated with agricultural machinery and equipment through Beidou navigation and positioning system, 5G communication system, machine condition monitoring and sensing technology, so as to realize real-time display of real-time positions of various agricultural machinery and equipment (such as harvesters, tractors, sprayers, lawn mowers, transport vehicles, forklifts, etc.). ) Combining GIS with latitude and longitude coordinates in the map scene. It not only obtains job data in real time and simulates it, but also provides intelligent decision-making for intelligent scheduling, job planning and shift adjustment.

Visualization of Irrigation/Fertilization/Spraying According to the different growth patterns of rice, corn, pumpkin, tomato and other crops in farmland, automatic sprinkler irrigation or drone irrigation can be selected, and the time length and irrigation amount can be intelligently set for specific crops or dryland crops.

Drone irrigation can provide managers with a lot of information about the temporal and spatial changes in the field, and fly autonomously in the whole process. Any terrain can provide an accurate operation path for farmland irrigation, fertilization and drug distribution. According to the detected soil moisture, growth stage and vegetation index, the planting area, crop growth and output value can be predicted independently, and at the same time, the numerical preset suggestions on the dosage of chemical fertilizers and pesticides can be output. Combined with the water and fertilizer integration technology, the utilization rate of fertilizers can be improved, the precision sowing of variable fertilization can be realized, and the growth speed and quality of crops can be improved. Realize various intelligent management modes such as time planning, model driving and environment driving.

Construct a map of agricultural resources management to help farmers and herdsmen better understand the farm environment and crop conditions. Effectively solve the problems of manual statistical data, such as time-consuming, labor-consuming, untimely and inaccurate, and improve work efficiency and sowing quality. Through this management mode, it can be expected that it will have a far-reaching impact on the transformation of agricultural production mode and promote the development of agriculture in a more efficient, environmentally friendly and sustainable direction.