Agricultural products are the material foundation essential for human survival and development, and concern a country’s economy and people's livelihood. China feeds nearly 21 percent of the world’s population while having less than 9 percent of the world’s arable land and 6 percent of freshwater resources. China, as an agricultural power, has a tight supply of food due to dwindling per capita arable land. As a result, developing smart agriculture, improving food production quality, and ensuring efficient and reasonable use of arable land will be critical for China’s agricultural development.

This project based on 5G+MEC (Mobile Edge Computing) technology and an intelligent AI-based analysis tool, achieves real-time digital planting of rice and vegetables. The smart agriculture management platform, which incorporates data collecting, transmission, interpretation, simulation, and decision-making, is established by intelligently interpreting data, and conducting modeling and decision-making. It achieves targeted, scientific and efficient management of agricultural production, fulfils the objective of improving efficiency, high yield and high quality, provides reference and ideas for the application of 5G and AI in modern agriculture, and also promotes the development of smart agriculture. The platform can automatically store, extract and interpret the massive images，videos and other data collected by front terminals. Independently developed deep learning toolbox (DeepField) is embedded on the platform. Standardized database is connected to all models on the platform, allowing for functions like intelligent counting, crop growth diagnosis, assessment of nutritional level, intelligent identification of plant diseases and insect pests, and intelligent yield monitoring. After implementation, this project has cut operating costs, achieved targeted, scientific and efficient management of agricultural production, and improved quality and efficiency while reducing carbon emissions.

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• Local-Shanghai, China

• Youth
• Older persons
• Women
• Indigenous and nomadic peoples
• People with disabilities
• The unemployed
• The poor
• Migrants
• Refugees and internally displaced people
• Remote and rural communities

Based on 5G+MEC smart agricultural system, this mature project can be directly promoted for application. Once the system is developed, it can be used infinitely. During the promotion process, the system can directly provide platform and data support services for users. In the future, it can be equipped with a corresponding number of data acquisition equipment and matching network for application based on different areas of usage. It can be repeated for simple and convenient use. At present, we have applied 5g + AI smart agriculture in many project, such as smart cabbage and smart tangerine peel planting in Guangdong, smart pig and smart sheep raising in Zhejiang, etc. The AI analysis model of this project has the replicability of a variety of crops, and can quickly adjust the analysis model suitable for crops according to the growth attributes of different crops, which can be replicated and popularized all over the world.

Take Shanghai for example, which has a population of over 24 million. The population density increases the demand for agricultural products, but agriculture only accounts for 0.39 percent of Shanghai’s GDP. Agriculture workers in China are mostly over 50 years old, and have a poor level of literacy. The labor force is a major stumbling block to agriculture’s future development. Solving the food problem has become an urgent task for the development of a sustainable society. The application of 5G smart agriculture reduces the input for agricultural products at the source. Targeted water and fertilizer management based on big data analysis and intelligent identification guarantees more efficient fertilizer use, increases crop quality, decreases the price of agricultural products, and maintains agricultural operations traceability for high-quality and safe agricultural products.

At the same time, through the establishment of an innovative development model of "industry university research", the project provides a complete solution to the field of agricultural production and multi planting scenarios in the field. Compared with other projects that collect crop growth data through sensing equipment, this project mainly collects and analyzes the images and videos of crop growth, and realizes analysis, research and judgment in combination with meteorological, remote sensing and other data, so as to further reduce the project cost. Through the accumulation of materials, the ability of AI image recognition will be more perfect in the continuous training process, and the operation cost will be gradually reduced in the subsequent development.

The project scientifically and effectively guides crop planting through artificial intelligence analysis. Compared with the previous empirical planting method, it is conducive to improve crop quality and yield. After the construction platform of the project is applied in Qingmei rice planting base, it is expected to increase production by 5% - 20%. To achieve the goal of end hunger, achieve food security and improved nutrition and promote sustainable agriculture (Goal 2) and goal of ensure healthy lives and promote well-being for all (Goal 3). The relevant research of the world food and Agriculture Organization (FAO) shows that 75% of carbon dioxide (CO2) in traditional intensive agriculture comes from chemical fertilizer, and the application of chemical fertilizer has a great impact on agricultural carbon emission. This project through scientific guidance on the use of water and fertilizer, it is expected to save 10% - 35% water and reduce the application of nitrogen fertilizer by 10% - 30%, effectively reduce agricultural carbon emissions and promote the goal of take urgent action to combat climate change and its impacts （Goal 13）. With intelligent machinery instead of labor, agricultural practitioners can remotely operate and control intelligent equipment, significantly improve labor efficiency, and realize the situation of agricultural efficiency, increasing farmers' income and rural prosperity. In addition, a number of technicians who understand both information technology and agricultural production will be trained to expand the scope of agricultural employment. All of this will achieve the goal of Promote inclusive and sustainable economic growth, employment and decent work for all (Goal 8).