Despite being one of the oldest professions, agriculture is gaining importance due to food insecurity concerns. AI is a potent instrument simulating human intelligence using computers, robots, and digital equipment. AI can revolutionize farming by modernizing agricultural practices and ensuring sustainable food production.
Improving the accuracy and predictability of AI systems necessitates continual updates and the expansion of their database. AI is based on imitating human intelligence and performing basic to complex tasks with learning, reasoning, and perception objectives.
How AI Useful in Agriculture
AI can assist with the complex and routine tasks involved in agriculture, complementing existing technologies. It can gather and process big data to make informed decisions and take action. AI can simplify crop selection, reduce errors and minimize the risk of crop failures, breed disease-resistant crops, monitor soil health, protect crops from diseases and pests, optimize irrigation and nutrient application, and even automate harvesting. By using AI, farmers can make their work more efficient and profitable.
Combining AI with Other Technology
AI cannot function independently in agriculture; it needs support from other technologies, such as big data, sensors, and software. Data engineers and analysts are crucial in making AI technology work. Combining AI with big data can help farmers make informed decisions based on real-time information about crop needs. IoT sensors can monitor and measure various metrics in fields, providing accurate information to farmers.
Combining AI with autonomous tractors and IoT can help solve the labor shortage problem and reduce errors. Agricultural robots are also used for manual work, providing longer work hours, precision, and fewer errors than human workers. By combining AI with other technologies, farmers can make their work more efficient and cost-effective, resulting in better productivity and increased profits.
Why AI Adoption is so Difficult for Farmers
Farmers may find it challenging to adopt AI because they must understand how it can benefit their physical work on the land. They may perceive AI as something only applicable in the digital world. The lack of understanding of practical applications of AI tools may prevent farmers from viewing new technologies as confusing and overly expensive.
AgriTech providers must clearly explain their solutions’ usefulness and implementation to farmers. AI has the potential to be helpful in agriculture, but technology providers need to work with farmers to ensure its proper implementation.
Top 10 Applications of Artificial Intelligence (AI) in Agriculture
Crop and Soil Monitoring
Monitoring crops and soil is essential for maximizing productivity and protecting agricultural health. Traditionally, this was done through human observation, but drones and computer vision models have made it easier and more accurate. AI can analyze aerial image data captured by drones to track crop health, make accurate yield predictions, and detect crop malnutrition.
For instance, AI can identify wheat growth stages and detect maturity in tomatoes with impressive accuracy. Computer vision models can also estimate soil texture and organic matter, eliminating time-consuming lab analysis. With the help of AI, farmers can quickly identify problem areas and take immediate action, ultimately leading to healthier and more productive crops.
Insect and Plant Disease Detection
Artificial intelligence (AI) computer vision can now automate the detection of plant diseases and pests, making agriculture more efficient. Using image recognition technology based on deep learning, AI can classify, detect, and segment images to monitor plant health.
A deep convolutional neural network was trained using images of apple black rot to identify and diagnose disease severity with 90.4% accuracy. AI computer vision can even count the number of flying insects with 92.5% accuracy, making it a promising tool for monitoring food systems while reducing labor inefficiencies.
Use of Weather Forecasting
Artificial intelligence can help farmers make more informed decisions by providing accurate weather forecasting. By analyzing data from various sources, AI algorithms can predict weather patterns, temperature changes, rainfall, and other weather-related factors that impact crop growth.
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armers can use this information to determine the best time to sow seeds, select appropriate crops, and manage irrigation systems. AI can also help farmers prepare for extreme weather conditions like droughts, floods, and storms. With accurate weather forecasting, farmers can optimize crop yields and improve their profitability while minimizing the risks associated with weather-related events.
Livestock Health Monitoring
Livestock health monitoring is an essential aspect of modern agriculture. Traditional methods of monitoring animal health and behavior can be time-consuming and inaccurate. Computer vision, however, has proven to be an effective solution. With overhead cameras and AI algorithms, companies like CattleEye can track and monitor cattle remotely and in real-time, enabling farmers to identify potential problems immediately.
Computer vision can also detect diseases, count animals, and monitor significant activities such as giving birth. Moreover, this technology can be combined with other technologies like drones to collect data and provide farmers with better insights into animal health and welfare.
Mechanizing the Spraying
UAVs equipped with computer vision technology can recognize the target spraying areas and accurately operate regarding area coverage and amount to be sprayed. However, challenges such as assigning task sequences and flight trajectories for individual UAVs remain. To overcome these challenges, researchers from Virginia Tech have developed a smart spray system that uses servo motor-controlled sprayers and computer vision to detect weeds. The system can analyze each weed’s size, shape, and color and deliver precise amounts of herbicide with precision targeting.
Automatic Weeding
While detecting weeds is one thing, physically removing them is another challenge. However, with the help of computer vision robots, it is possible to detect and remove weeds. This is not only more environmentally friendly but also saves a lot of time and effort for farmers. Automatic weeding also contributes to more sustainable farming practices by reducing the need for herbicides. With the help of AI, robots can precisely locate and remove weeds, making the process more efficient and effective than traditional manual weeding methods.
Precision Farming and Predictive Analysis
Artificial intelligence (AI) has proven to be a valuable tool for precision farming and predictive analysis. By guiding weather management, crop rotation, timely harvesting, optimal planting, pest control, and nutrient management, farmers can make informed decisions and improve crop yields. With AI, farmers can analyze large amounts of data from various sources, such as weather forecasts, soil sensors, and satellite imagery, to predict crop performance and potential issues.
Aerial Imagery Analysis
AI can aid in surveying land and monitoring crops and livestock through aerial imagery analysis from drones and satellites. This technology allows farmers to receive immediate notifications of problems in their fields without constantly checking them. It is also useful for improving the precision and efficiency of pesticide spraying, as it ensures that the pesticides are only applied where needed, saving money and minimizing environmental impact.
Sorting and Grading
Computer algorithms can accurately and quickly differentiate between high-quality produce and defective or unattractive items by analyzing factors such as size, shape, color, and volume. This process can be completed much faster than a trained human professional. By automating the sorting and grading process, farmers can increase efficiency and reduce waste.
Supply Chain Optimization
By providing real-time data on transportation logistics, inventory levels, and market demand, AI can help farmers make informed decisions about distribution and sales. This technology can also help farmers reduce waste, improve efficiency, and cut costs. AI-powered livestock health monitoring is another important application in agriculture.
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By analyzing animal behavior and vital signs, AI can detect early signs of illness or injury, allowing farmers to intervene before a serious health problem develops. This technology can improve animal welfare, reduce mortality, and increase farm productivity.
Conclusion
AI has the potential to revolutionize agriculture, from precision farming and crop health monitoring to supply chain optimization and livestock health monitoring. As technology advances, the integration of AI in agriculture is likely to become even more widespread and essential for sustainable food production.
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