Background
In the context of continued global population growth and increased pressure on resources and the environment, improving agricultural productivity has become an important means of ensuring food security and promoting sustainable agricultural development. Challenges facing traditional agriculture include inefficient use of resources, high labor costs, and weak ability to deal with natural disasters and pests. The integration of artificial intelligence (AI) and sensor technology not only revolutionizes agriculture, but also makes enough to enhance agricultural productivity and green production patterns.

I. Precision Planting and Soil Management
1. Soil sensor and AI analysis
Soil condition is the basis of crop growth, through sensor technology, real-time monitoring of soil moisture and other key indicators. Sensor data can be analyzed through AI systems to predict only the need to add water and no need for excessive irrigation. Soil nutrient sensors can measure the content of nitrogen, phosphorus, drilling and other nutrients in the soil, AI technology based on these data combined with the growth stage of crops and varieties of characteristics, you can develop a more accurate fertilization program, to ensure that the crops in all periods of growth can obtain sufficient and appropriate amount of nutrients, not only to avoid the waste of fertilizers, but also to improve the yield and quality of crops. For example, in a corn plantation, with the help of soil sensors and AI analysis, the use of fertilizer can be reduced by 20% - 30%, while corn yields can be increased by 10% - 15%.
2. Intelligent seeding and planting planning
Artificial intelligence, combined with sensor data, enables smart seeding and scientific planting planning. ai systems can analyze big data on soil properties, climatic conditions, and topography to predict and select the most suitable location and type of crop for planting. Using satellite images and land information monitored by sensors, the AI can identify the differences in soil fertility between different plots, and guide farmers to plant crops with high nutrient demand in plots with high fertility, and crops with high adaptability in plots with low fertility. In the seeding section, the intelligent seeder, under the guidance of AI, accurately controls the seed depth, planting spacing and the number of seeds to ensure that each seed grows in the most suitable environment, further enhancing the seed germination rate and annual yield.

II. Intelligent Irrigation and Water Management
1. Real-time monitoring and automatic control
Various types of sensors distributed in the farmland, such as meteorological sensors, soil moisture sensors, crop water sensors, etc., play a central role in the intelligent irrigation system. Meteorological sensors monitor rainfall, evapotranspiration, wind speed and other meteorological parameters, soil moisture sensors provide feedback on the soil moisture status, and crop moisture sensors directly sense the water demand of crops. These data are transmitted to the artificial intelligence control system, AI algorithms comprehensive analysis automatically control irrigation equipment, according to the weather and soil condition to adjust the irrigation volume, to avoid the waste of water resources, while ensuring that the crop growth of the water required to improve crop yield.
2. Optimized allocation of water resources
For large areas of farmland or irrigated agriculture, the optimal allocation of water resources is crucial, AI analyzes the distribution of water resources and the importance of water demand in the region, and then makes intelligent allocation to ensure that the crops use water during the period of water demand in the first place. It realizes the efficient and fair distribution of water resources and improves the stability of agricultural production in the whole region.

III. Pest and disease monitoring and precision control
1. Early warning of pests and diseases
Pests and diseases are important factors affecting agricultural productivity, and sensor technology and artificial intelligence have revolutionized pest monitoring and control. Through image sensors and AI analysis, the emergency response of crops, such as leaf discoloration, spotting, and wilting, can be read quickly, and early warnings can be issued at the early stages of pests and diseases. For example, spectral sensors can detect changes in spectral characteristics due to pests and diseases and predict pest and disease conditions in advance. Through early warning, farmers can take timely control measures to avoid large-scale outbreaks of pests and reduce crop losses.
2. Precise control and pesticide reduction
Based on the results of sensor monitoring and AI analysis, precise control of pests and diseases can be realized.AI develops unique control programs based on the types of pests, diseases and factors.The methods used include biological control and intelligent application of pesticides, which reduces the use of pesticides by 40% - 60%, lowers the cost and reduces the pollution of the environment, and at the same time, effectively controls pests and diseases and guarantees the yield and quality of fruits.

IV. Animal husbandry in the application of artificial intelligence and sensors
Livestock farming is an important part of modern agriculture, and the combination of artificial intelligence (AI) and sensor technology is changing the way farming is done. Through intelligent monitoring and environmental control, these technologies not only improve the efficiency of livestock health management, but also optimize the farming environment, thereby increasing productivity and reducing costs.
1. Smart monitoring of animal health
Real-time health monitoring with sensors
In modern animal husbandry, the health status of livestock directly affects farming efficiency. Smart sensors (e.g. temperature sensors, motion sensors, heart rate sensors, etc.) can be integrated into smart collars to help farmers realize round-the-clock monitoring of livestock health. Temperature sensors monitor the body temperature of livestock and identify potential signs of disease. Motion sensors record the amount of activity of the livestock, and a decrease in activity may indicate ill health. Heart rate sensors detect fluctuations in heart rate to determine heart health. These data are transmitted in real time to the AI analysis platform, which builds a health model through big data analysis. Once an abnormality is detected, the system automatically warns farmers to take timely measures, such as isolating sick animals and diagnosing and treating them. This intelligent monitoring system can effectively reduce the mortality rate of livestock and improve farming efficiency.
AI Predicts and Prevents Disease
AI combines a variety of sensor data to analyze trends and predict the health of livestock. For example, if the AI finds that the gradual decrease in movement of cows may indicate early hoof disease, the system can alert farmers in advance to intervene and reduce losses.
Data shows that after applying AI smart monitoring, the early detection rate of livestock diseases can be increased by 30% and the mortality rate can be reduced by 20%, thus significantly improving the farming profit.
2. Intelligent Farming Environment Optimization
Real-time monitoring of farm environment
A good farming environment is crucial to the growth of livestock. Sensor technology can monitor key environmental parameters such as temperature, humidity and air quality in the farm and transmit the data to the AI control system to ensure that livestock are in an optimal growing environment. Temperature sensors ensure that the environment is at the right temperature to prevent heat or cold from affecting livestock health. The humidity sensor maintains proper air humidity to minimize respiratory diseases. The air quality sensor detects the concentration of carbon dioxide, ammonia and other gases to ensure that the air is clean and fresh, reducing the risk of livestock falling ill due to air pollution.
AI Intelligent Control System
The AI system automatically adjusts ventilation, temperature control, humidification/dehumidification equipment according to sensor data to ensure that the breeding environment is always in the best condition. In hot weather, AI automatically controls the ventilation system and cooling equipment to keep the farm cool. In cold weather, AI adjusts the heating system to maintain the appropriate temperature. When the air is polluted, AI activates air filtration equipment to reduce the concentration of harmful gases. After applying AI intelligent environmental control, the research data show that the growth cycle of livestock is shortened by 15%, the feed conversion rate is increased by 10%, and the overall farming cost is reduced by 12%.

V. Future Prospects: Promoting Sustainable Agricultural Development
With the continuous progress of technology, AI and sensors will play a greater role in guaranteeing global food security and improving agricultural economic efficiency. Intelligent agriculture not only improves production efficiency, but also provides a strong impetus for the sustainable development of agriculture, enabling agriculture to move forward in the direction of more accurate, efficient and environmentally friendly.