How is artificial intelligence applied in agriculture?

AI has become one of the most important technologies in every field including education, banking, robotics, agriculture, etc. In the agricultural sector, it is playing a very important role and it is helping to transform the agricultural industry.

AI saves the agriculture industry from various factors like climate change, population growth, food safety and employment issues in the sector. Today’s agriculture system has reached another level thanks to AI.

AI has improved crop production and real-time monitoring, harvesting, processing and marketing. Various high-tech computer-based systems are designed to identify various important parameters such as weed detection, crop quality, pests, etc.

In agriculture, farmers need to have knowledge about fertilizers, soil resources, pesticides for different crops, growing and irrigation cycles, and weather effects.

Pests alone destroy up to 40% of the world’s crops each year, and farmers now have to produce more food using less water and energy. Rapid urbanization has also led to a global shortage of agricultural workers, meaning farmers need to rely less on their workforce.

AI Applications in Agriculture

AI in agriculture is the application of information technology and AI to solve problems in agricultural production. With the development of AI, many new applications of this technology have been introduced into agriculture, helping to improve productivity and production efficiency, while minimizing risks and production costs.

The benefits of AI for agriculture are enormous. That is why this technology has been increasingly applied in agricultural production and cultivation.

Weather and price forecast

Weather forecasting analysis devices are one of the applications of AI in agriculture. This device is used to collect and analyze weather data, thereby forecasting future weather conditions, helping farmers choose the right time to plant and care for crops.

Current weather forecasting analysis devices are often equipped with sensors and measurement technologies such as spectrometers, atmospheric spectrometers, air humidity and temperature meters, radars, satellite systems, and weather modeling technologies based on AI algorithms.

Weather forecasting devices are very useful in helping farmers make decisions in accordance with weather conditions. For example, when the device detects that there will be heavy rain in the next few days, farmers can decide to postpone spraying pesticides or harvesting fruits to ensure the safety of the crops and minimize the risk of crop loss.

With price forecasting, AI can help farmers get a better idea of ​​the prices of food items in the coming weeks, which can help them maximize their profits.

Plant health monitoring

Crop quality depends largely on soil type and soil nutrition. AI-based algorithms will help identify nutrient deficiencies in the soil so that farmers can supplement them in time and warn of pests that harm crops.

Designed to monitor and provide information, the plant health monitoring system provides information on soil moisture, nutrients, CO2 concentration, temperature, air humidity and other indicators related to plant health.

The system works by using sensors to collect data and then using artificial intelligence algorithms to analyze this data. The analysis results are provided to farmers or agricultural experts so they can make smart decisions about how to grow and care for crops.

Soil and plant health monitoring systems can help farmers optimize production, increase productivity and reduce costs. They also help agricultural researchers better understand how plants and their environments work, and develop solutions to improve productivity and quality of agricultural products.

Agricultural Robots

Robots are widely used in various fields, mainly in manufacturing, to perform complex tasks. Nowadays, AI companies are developing robots for use in the agricultural sector. These AI robots are developed in such a way that they can perform multiple tasks in agriculture.

These robots can be used to monitor, manage, tend crops, harvest, and use fertilizers and pesticides more efficiently. They can also help increase productivity, reduce costs, and reduce the environmental impact of farming.

Features of agricultural robots include sensors to monitor plant health, soil analysis and weather forecasting, control systems to control spraying and watering, and the ability to automate operations such as harvesting. Agricultural robots are often remotely controlled or fully automated, depending on the needs of the user.

The use of agricultural robots can help increase productivity and efficiency in agricultural production, while reducing the impact of this activity on the environment. However, the deployment of agricultural robotic systems requires a large initial investment and high technical training for users.

AI robots are also being trained to inspect crop quality, detect and control weeds, and harvest crops at a faster rate than humans. Several autonomous fruit harvesting robots have been developed by companies around the world, including orange picking robots, strawberry picking robots, and tomato harvesting robots.

Automated systems for climate-based irrigation of high-value crops are also being developed. The Demeter system is equipped with cameras and a global positioning system (GPS) to control harvesting in the fields. In addition, some types of robots to control and eradicate weeds are also being researched and designed by companies.

AI-based smart spraying

With AI sensors, farmers can easily detect weeds and weed-affected areas. Once such areas are detected, herbicides can be sprayed precisely to reduce herbicide usage and save time.

Many AI companies around the world are building robots that integrate AI and computer vision technology to spray weed killers with precision. Using AI-based smart spraying systems can significantly reduce the amount of chemicals used in fields, thereby improving crop quality and helping to save production costs.

Plant disease diagnosis

AI-powered pest detection systems in agriculture are an important tool in protecting crops from harmful diseases and insects. The system uses data modeling and techniques to analyze data from sensors. The system then analyzes the data to determine whether a pest is present, assesses the severity of the pest, and recommends solutions.

AI systems can also detect changes in plant growth, such as whether the plant is growing faster or slower. This can help detect health problems and help farmers intervene early to address the problem. Timely correction helps protect plant health and increase agricultural productivity.

Precision farming

Precision farming is an application of AI in agriculture. It uses technologies such as machine learning, computer vision, and sensor technology to help identify, collect, and analyze data to make precise farming decisions and predict yields.

Additionally, precision farming systems use sensor technology to collect data about soil, crops, and the surrounding environment to make precise farming decisions such as watering, fertilizing, pruning, etc. These systems can minimize the use of fertilizers, pesticides, and water, increasing yields and reducing costs for farmers.

The Benefits of AI in Agriculture

AI enables better decision making

Predictive analytics is a boon for the agriculture industry. It helps farmers solve key farming challenges, such as analyzing market demand, forecasting prices, and finding the optimal time to sow and harvest crops.

Moreover, AI-powered machines can also determine the health of soil and crops, give fertilizer recommendations, monitor the weather, and can also determine the quality of crops. All such benefits of AI in agriculture enable farmers to make better decisions and farm more efficiently.

AI helps save production costs

Precision farming using AI-powered equipment helps farmers grow more crops with fewer resources and costs. AI provides real-time insights to farmers, allowing them to make informed decisions at every stage of cultivation. With these informed decisions, it reduces product and chemical losses and makes efficient use of time and money.

Furthermore, it also allows farmers to identify specific areas that require irrigation, fertilization, and pesticide treatment, which saves on the overuse of chemicals on crops. All of this adds up and leads to reduced herbicide use, better crop quality, and higher profits with fewer resources.

AI reduces labor shortages.

The problem of labor shortage in agriculture has always been a burning issue. AI can solve this problem through automation in agriculture. With AI and automation, farmers can get the job done without the need for additional people, and some examples are driverless tractors, smart irrigation and fertilization systems, smart sprayers, vertical farming software, and AI-powered harvesting robots. AI-controlled machines and equipment are much faster and more accurate than humans.

Challenges of applying AI in agriculture

Seeing the advantages of AI for sustainable farming, implementing this technology seems like a logical step for every farmer. However, there are still some notable challenges:

Farmers are unfamiliar with AI-powered devices

Despite the numerous benefits of using AI in agriculture, most farmers around the world are still unfamiliar with using AI-powered solutions and equipment. To address the issues, AI companies should provide basic equipment to farmers and once they are familiar with it, then provide them with more advanced machines.

Lack of experience with emerging technologies

Adopting AI and emerging agricultural technologies in developing countries can be a challenging task. It will be difficult to sell such technologies in areas where such agricultural technologies are not being applied. In these areas, farmers need support and training from technology development companies or sales companies to use advanced technologies.

Privacy and security issues

Since there are still no clear regulations and policies regarding the use of AI, it can raise many legal issues. Moreover, due to the use of software and the Internet, there can also be some privacy and security issues such as cyber attacks and data leaks. All these issues can create a big problem for the farm owner or farmer.

In short, AI technology will continue to be developed and applied strongly to analyze, monitor and predict various environmental impacts on crop yield and quality. Along with that, in the face of the real impact of climate change, accurate weather forecasting helps farmers make the right decisions about time and cultivation objects to maximize farming profits.