Is artificial intelligence (AI) also used in agriculture and agricultural engineering? Is artificial intelligence going to replace agricultural engineers and farmers? In the not-so-distant future, will artificial intelligence provide food for the people of the planet?
Artificial intelligence is here to stay and change our lives. These days, with the growth and expansion of artificial intelligence applications in different fields and industries, the discussion about the effects of AI and the changes it brings to employment and the labor market in different fields; is the discussion of world politicians and people like Elon Musk.
Perhaps the applications of artificial intelligence in the architecture design and development of computer games and similar areas do not seem very strange and far-fetched. But you should know and not be surprised that artificial intelligence is very practical and useful in agriculture and will revolutionize agricultural engineering in the not-too-distant future.
In the following, we answer the questions posed above and discuss the applications and benefits of using artificial intelligence in agriculture and agricultural engineering.
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How will artificial intelligence transform agriculture?
It is better to first explain a little about what agricultural engineering is and how AI might be used in it. Agricultural engineers, like other engineers, use engineering knowledge to solve problems and challenges related to planting, harvesting, and producing agricultural products. Their main work and concern is how they can better manage production processes so that resources are consumed less and more efficiently.
According to the definition of agricultural engineering on the website of the General Statistics Office of the US Department of Labor,
Agricultural engineers solve problems concerning power supplies, machine efficiency, the use of structures and facilities, pollution and environmental issues, and the storage and processing of agricultural products.
According to the definition of agricultural engineering, it can be said that the work of agricultural engineers is a kind of managing and optimizing resources and processes. This is exactly why artificial intelligence is very useful in this field. Data and data analysis are needed to optimize processes and make macro decisions. Artificial intelligence, in fact, the Python programming language and its powerful libraries, is a unique tool for data collection and analysis.
Python programming language plays a key role in the development of artificial intelligence and its tools. The powerful Pandas library, as well as the many features of the Python language for data visualization, have caused artificial intelligence to come to the aid of experts and engineers in any field and specialization that requires the collection and analysis of a large amount of data. Agricultural engineering is one of those fields and specialties.
AI applications in agriculture
Artificial intelligence (AI) is rapidly changing many industries and agriculture is no exception. AI is used to develop new and innovative methods to improve performance in the agricultural industry, reduce costs, and make agriculture more sustainable. The following are some of the most important applications of artificial intelligence and tools based on artificial intelligence in agriculture.
1. Monitoring of agricultural products
AI-based cameras and sensors are used to monitor the growth of crops to detect and diagnose pests, diseases, and other plant problems at an early stage. When pests and diseases are detected quickly, the necessary treatments are done quickly. In this case, the crop will not be destroyed and the farmers will not suffer losses.
2. Performance prediction
AI and its very important subfield, machine learning, are used to predict yield and yield based on various factors such as weather conditions, soil quality, and past data. As mentioned, management and engineering require data-driven decisions. Using data and the Python programming language, agricultural engineers can train algorithms (models) to predict the future by analyzing past data. Agricultural engineers use those forecasts to make decisions about planting, watering, and fertilizing.
3. Precision farming
Precision agriculture is opposed to traditional agriculture. In this concept and approach in agricultural management, decisions are made based on data, economic and environmental considerations, and by applying technologies and different tools, including AI-based tools. In precision agriculture, agricultural land is divided into smaller units, and each unit is managed based on its characteristics and with intelligent tools. In this way, fertilizers and pesticides are used more accurately and efficiently, and as a result, costs and environmental risks are reduced.
4. Livestock monitoring
AI-based sensors are used to monitor livestock for early detection and diagnosis of health problems, milk production, and other issues. This information obtained from sensors helps farmers to improve the health and productivity of livestock.
5. Robotic harvesting
Harvesting robots made with artificial intelligence are among the latest inventions in this field. Robots can harvest agricultural products more efficiently and with less waste. This helps to reduce labor costs and speed up the production and harvesting process.
Advantages of using artificial intelligence in agriculture
Agriculture and agricultural engineering with artificial intelligence is just the beginning. The benefits of using artificial intelligence and AI-based tools and technologies are so vital that it can be predicted that precision agriculture and artificial intelligence agriculture will replace traditional agriculture shortly.
Among the most important advantages of using AI in agriculture are the following:
1. Increasing the amount of agricultural products
AI helps farmers and engineers make more informed and intelligent decisions. As a result, in a certain amount of land and with a certain amount of seed, fertilizer, and irrigation, more crops are obtained compared to the past. When the crop is not affected by pests and diseases are detected early, the amount of damage to the crop is reduced and the productivity of the crop is increased.
2. reduction in costs
AI helps engineers and farmers reduce costs by using resources like water and fertilizers more efficiently and optimally.
3. Improving food security
The world is facing a food crisis. Land resources for agriculture are limited, and climate change and drought have made it harder to exploit those limited resources. Difficulties will increase in the future with the intensification of drought in different parts of the world. In such a situation, producing more food from fewer resources with the help of artificial intelligence technologies and data-driven agriculture means improving food security for the people of the planet.
4. Reducing environmental hazards
AI will greatly help in reducing the damage of agriculture to the environment. Using tools based on artificial intelligence and data analysis with them will allow engineers and farmers to use pesticides and fertilizers more accurately and efficiently.
Examples of human and AI collaboration in improving agricultural engineering
AI is still in its early stages of development in agriculture. However it has the potential to completely revolutionize the agricultural industry and agricultural engineering. In the following, we examine some very interesting examples of human and artificial intelligence cooperation in improving agriculture and agricultural engineering in different countries. By examining these examples, in practice, the importance and extraordinary efficiency of artificial intelligence in agriculture is determined.
1. Artificial intelligence farming in California
Farmers in California are using AI-powered cameras to monitor their vineyards. These cameras can detect pests and diseases much earlier than the human eye. Early and timely diagnosis allows farmers to act quickly and prevent damage to their crops.
2. Farming with AI robots in Australia
Farmers in Australia are using AI-powered harvesting robots to harvest lettuce. These robots can harvest lettuce faster and more efficiently than workers (humans). Also, they can selectively harvest lettuce. It means that they pick the products more carefully and if a product is damaged, they don’t choose it. This causes agricultural waste to be reduced.
3. Farming with AI-based tools in the US Midwest
Farmers in Midwestern states are using AI-based sensors to monitor soil moisture. These sensors can send data to farmers’ smartphones. Therefore, farmers know exactly when to irrigate their crops. The use of this technology helps to save water and improve the performance of farmers.