Petrong Shares Develop Agricultural Artificial Intelligence Countermeasures and Suggestions

Shanghai Herong Agricultural Science and Technology Development Co., Ltd. is obviously increasingly driving the development of an agricultural and intelligent technology development, accelerating operational efficiency and resource utilization. Developing agricultural artificial intelligence, making it a challenge and opportunity for my country, it is necessary to live, catch up with advanced technology, develop work should take the absorption, lending, innovation, and beyond the way to improve the research as soon as possible. Innovation? Application system to meet the requirements of agricultural development on agricultural monitoring, agricultural data analysis, agricultural equipment transformation and upgrading, agricultural products supply and marketing chain tracking, etc., improve agricultural intelligence level, promote the development of agricultural modernization, play "head geese Effect, add bricks in the era of human agricultural intelligence. Comprehensive analysis, the following suggestions for the development of agricultural intelligence in my country:

1) Pay attention to the cultivation and management of artificial intelligence related professional talents. The root of promoting science and technology development is talent. Domestic agriculture and forestry universities should conduct professional reforms in accordance with the development trend of intelligence agriculture to meet the needs of new intelligence agricultural industries on new agricultural science and technology talents. In addition, it should be actively encouraged to support enterprises to cultivate composite talents that have both manual intelligence and agricultural background, solve the practical problems of farmers, and provide intelligence and talent support for new technologies such as artificial intelligence in agriculture. In terms of scientific research and team building, it is encouraged research teams with multidisciplinary cross-integration.

2) Promote infrastructure construction of agricultural intelligence development. The development of agricultural artificial intelligence is inseparable from massive data accumulation and network real-time response. The farm agricultural infrastructure is not perfect, and agricultural data has high acquisition costs, which greatly limits the breadth and depth of machine learning in scenarios. It should pay attention to the construction of 5G infrastructure construction in agricultural materials and rural areas, improve the level of infrastructure of intelligent agricultural sensors, build agricultural production information and digitalization projects, introduce agricultural data sharing mechanisms, etc., provide fundamentals for the large-scale application of artificial intelligent agricultural equipment And conditions.

3) Promote research and development of agricultural production intelligent control technology. Promote agricultural production intelligence sensation, identify research and development of operation decision models, for agricultural planting, breeding different environments, establish a multi-source data fusion, agricultural whole process decision support method, building field crops, greenhouses, livestock and poultry, and water products In the field of decision management and intelligent control models, using cloud? Edge-end architecture, realize the intelligent decision system based on "agricultural brain" under data driver management.

4) Strengthen the development of intelligent equipment and systems. For agricultural production needs, accelerate the popularity of intelligent machines, improve resource utilization and agricultural output rate, and improve economic benefits. Cultivate my country’s advantageous intelligent agricultural machinery such as agricultural drones, enhance the cross-boundary technology integration of agriculture and other industries, meet new generation information technology, open innovation model, seamless integration of human wisdom and machinery intelligence, re-assessing agricultural future, and create new business opportunities. First, research and development special equipment should consider reducing cost and improving adaptability, hardware, the sensors on smart devices such as robots and drones can increase or decrease depending on the actual situation, and the control part is indwelling the air interface; software, support secondary development And expand, provide a good platform for human machine collaboration and multi-machine collaboration. Second, Based on the cloud? Side-end architecture to build a "agricultural brain" intelligent decision system: Cloud platform provides storage and computing services, and the edge calculates the robots and other equipment on the Internet of Things and other equipment real-time dynamic management, the clouds are coordinated to the agricultural robot field The job provides decision support. Finally, the future agricultural robot will bear more and more job tasks and become key components in agricultural production. For this purpose, new technologies such as artificial intelligence, Internet of Things, big data, virtual perception system, multi-sensor fusion, human machine blending is required.