ABSTRACT
Technology has reconceived farming over the years, and technological advances have affected agriculture in multiple ways. Agriculture is one of the oldest and mainstay occupations in many countries around the world.
According to United Nations (UN) estimates, there will be 9.8 billion people on the planet in 2051 and 13.2 billion in 2500. The UN Food and Agriculture Organization projects that by 2050, we would need to produce 60% more food to infuse a global population of 10.8 billion people.
Our natural resources will be heavily taxed if farming is done as normal. This is driving farmers and agri-based company to identify new ways to increase production. As a result, the use of artificial intelligence (AI) and machine learning based on agriculture will lead to high production.
Artificial intelligence will not only enable farmers to improve efficiency but also increase the quantity, quality, and growth of crops. The main concern is to audit various applications in agriculture, such as crop yield predictions, price stock monitoring, intelligent spraying, predictive plantation, crop and soil monitoring, weather forecasting, diagnosis of diseases, and agribots.
Because of global warming, the temperature of Earth changes continuously, resulting in alterations to the climate and an increase in population. Farmers can select which type of crop to plant and the ideal time to seed the crop with the use of AI applications, which can help them with this challenge.
In agriculture, the type of soil and the nutrients contained in the soil have an important impact on crop productivity and value. The quality of soil and the nutrients it contains have declined as a result of increased deforestation. This makes it difficult for farmers to decide which crop to plant and how much fertilizer to use, which can be overcome by developing AI applications that can detect pests and illnesses, as well as nutritional deficiencies in the soil, giving farmers advice on the best pesticides to apply. The technology for picture recognition can help with this task.
The farmers capture the images and identify the disease. Every day, farms produce lakhs of data points on temperature, weather, soil nature, moisture, water condition, and usage of water. Artificial intelligence applications can be developed to help farmers avoid inaccurate farming and by offering appropriate advice on water management, crop rotation, harvesting time, the type of crop to be cultivated, insect assaults, and the appropriate fertilizer to use. Farmers may practice managed farming, and AI drones can help in proper layout in farming.
Machine learning and AI can be used to monitor stock prices to increase farmers’ profits. Artificial intelligence in agriculture not only automates farmers but also increases crop yield and production, which can meet the needs of the world. The AI AgroWeb is a multi-problem solver for farmers.
