Artificial Intelligence For Agriculture To meet Need For 2050

 

There are so much researches are going on in the field of using Artificial Intelligence for agriculture to meet the need for 2050 Future. In this post I tried many possible research areas in the field of the agriculture sector. These methods are very useful for researchers working in the field of agriculture using IoT, AI, ML.

wheat, field, sunset

 

Artificial Intelligence for agriculture to meet the need for 2050 Future is founded on the idea that human intellect.  It may be characterized in such a manner that a computer can simply imitate it and carry out tasks ranging from simple to complicated. Artificial intelligence aims to improve learning, thinking, and perception.

Why AI in Agriculture?

Agriculture and farming are two of the world’s oldest and most significant occupations. It has a significant impact on the economy. Agriculture is a $5 trillion business worldwide.

By 2050, the world population is anticipated to reach more than nine billion people, necessitating a 70% increase in agricultural production to meet demand. As the world’s population grows, land, water, and resources become insufficient to keep the demand-supply chain going. As a result, we need to take a more strategic approach and become more efficient in how we farm so that we can be more productive.

Farmers’ challenges while employing traditional agricultural methods

The following is a list of some of the most common agricultural difficulties.

 In agriculture, climatic variables like as rainfall, temperature, and humidity have a vital effect in the life cycle of the crop. Climate change is a result of increasing deforestation and pollution, making it difficult for farmers to make judgments about how to prepare the soil, sow seeds, and harvest.

Every crop requires a unique type of soil nourishment. In soil, three major nutrients are required: nitrogen (N), phosphorus (P), and potassium (K). Nutrient shortage can cause crops to be of low quality.

Weed control is critical in agriculture, as seen by the agricultural lifecycle. If not regulated, it can lead to an increase in production costs as well as the absorption of minerals from the soil, resulting in nutritional shortage.

dji, drone, plant protection drone

Agriculture Artificial Intelligence Applications

Artificial Intelligence (AI) is being used by the agricultural sector to help produce healthier crops, manage pests, monitor soil and growing conditions, organize data for farmers, reduce effort, and enhance a wide range of agriculture-related jobs along the food supply chain.

Farmers can analyze weather conditions by using weather forecasting, which helps them plan the type of crop that can be grown and when seeds should be sown, with the help of Artificial Intelligence. With the change in climatic conditions and increasing pollution, it’s difficult for farmers to determine the right time for sowing seed.

Monitoring system for soil and crop health: The kind of soil and the nutrients in the soil influence the type of crop cultivated and the quality of the crop. Soil quality is deteriorating as a result of increased deforestation, making it difficult to evaluate the condition of the soil.

Ways  to protect crop using tech

Drones for crop health analysis: SkySqurrel Technologies has introduced drone-based Ariel imaging systems for agricultural health monitoring. In this method, the drone collects data from fields, which is subsequently uploaded to a computer via USB drive and evaluated by professionals.

Precision Farming and Predictive Analytics: AI applications in agriculture have developed applications and tools that assist farmers in performing accurate and controlled farming by providing proper guidance on water management, crop rotation, timely harvesting, type of crop to be grown, optimum planting, pest attacks, and nutrition management.

AI-enabled technologies predict weather conditions, analyze crop sustainability, and evaluate farms for the presence of diseases or pests, as well as poor plant nutrition, using data such as temperature, precipitation, wind speed, and solar radiation in conjunction with machine learning algorithms and images captured by satellites and drones.

rice paddies, a medley of the pool, farmers

Farmers who don’t have access to the internet may profit from AI right now using basic technologies like an SMS-enabled phone and the Sowing App. Meanwhile, farmers with Wi-Fi connection may utilize AI programs to receive an AI-customized plan for their fields on a continuous basis. Farmers can satisfy the world’s rising food demand with IoT and AI-driven solutions that boost output and profitability without depleting valuable natural resources.

AI will help farmers grow into agricultural scientists in the future, utilizing data to maximize yields down to individual plant rows.

Agricultural Robotics: AI firms are working on robots that can do a variety of jobs in farming areas. When compared to people, this sort of robot is trained to manage weeds and harvest crops at a faster rate with larger quantities.

These robots are programmed to inspect crop quality and detect weeds while picking and packing crops at the same time. These robots can also deal with the difficulties that agricultural labor faces.

A system that uses artificial intelligence to identify pests: Pests are one of the most destructive enemies of farmers’ crops.

AI systems analyze satellite photos and compare them to previous data to determine whether any insects have landed and, if so, what sort of insect has landed (locust, grasshopper, etc.). And send warnings to farmers’ cellphones so that they may take the necessary measures and apply the necessary pest management, allowing AI to assist farmers in their pest control efforts.

Hope you like this article in case you need consultation in this area or you want to persue your carrer in this field you may contact me at [email protected]

Dr. Pawan Whig

Senior IEEE Member

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