Farming has always been the most primitive and vital activity in the world. However, these demands for food grains have steadily increased since humans first discovered agriculture and moved from a wandering, hunt-and-gather lifestyle to farmers'. In the agricultural sector today, many food producers are struggling to manage the threats and risks to their crops from pests and other diseases exacerbated by climate change, monoculture, and the widespread use of pesticides. All of these add up and emerge as a new challenge for farmers. As agriculture relies on the forces of nature for most of its products and with the uncertainty of rain, the shortage of available labor and the growing need for better yields each year has put farms and farmers under extreme pressure. It means that the agricultural industry must develop massively in the coming years. With all of these challenges in mind, the leading concern today is automation in the agricultural industry. The population is increasing tremendously, and with this increase, the need for food and employment also increases. The conventional methods used by our farmers today are not sufficient to meet these requirements. Therefore, modern automated methods have been added to make things simpler and more fruitful. Artificial intelligence in the agricultural sector can be implemented using many technological advancements. These cover things like artificial intelligence consulting services, data analysis, the Internet of Things, and the use of cameras and other sensors, etc. By examining different data sources such as weather, soil, crop performance, and temperature, AI in agriculture will proficiently produce better predictive information. These AI-based technologies can help the agricultural sector produce better crops and improve a wide range of agriculture-related tasks across the food supply chain. These new methods have increased food requirements and provided employment opportunities for billions of people across the system. The use of AI in agriculture has revolutionized agriculture and has defended crop yields against several factors such as population growth, climate change, employment issues, and food security concerns. Challenges faced by the agricultural sector Here are some of the significant challenges that exist in agriculture: With each passing day, it becomes difficult for farmers to prepare the soil, sowing seeds, and harvesting as various climatic factors such as temperature, precipitation, and humidity play a vital role in agriculture. Growing pollution and deforestation also lead to climate change, which is becoming a major challenge for farmers. Every crop needs precise nutrition in the soil. The three main types of nutrients required in the soil are phosphorus, potassium, and nitrogen. The deficiency of any of these nutrients can lead to poor crop quality. Protecting plants or weeds also plays an important role. It can lead to increased production costs and absorb nutrients from the soil, resulting in a nutrient deficiency if not controlled at the right time. Despite many application possibilities in agriculture, there is still a loss of knowledge of the most modern technologies in most countries of the world. Benefits of AI-based agriculture solutions Now, let's first understand the concept of precision agriculture and how it is helping to revolutionize applications in the agricultural sector: 1. Manage environmental challenges through the use of weather forecasts. Weather information plays a much-needed role in the evolving field of precision agriculture, which is an agricultural practice that maintains control and precision while cultivating crops. Various environmental challenges such as climate change and others are the biggest threats to agricultural productivity. However, AI-based systems and data-driven agriculture use more innovative resource management that helps farmers manage modifications based on changing environmental conditions. 2. Soil and crop health monitoring system Using emerging solutions and installing IoT sensors in agricultural soil, farmers can instantly identify soil moisture content and know its chemical composition and structure. These implanted devices can be configured to automatically notify farmers when the level of elements such as potassium, nitrogen, phosphorus, or the moisture content in the soil reaches inadequate values. Remote sensing complemented by 3D laser scanning is also helpful for cropland harvest measurements, ensuring crops are growing in perfect soil conditions. Drones also play an important role along with professional multispectral sensors and cameras to detect and quantify crop health issues earlier, providing valuable information that helps increase yield and lower input costs. Predictive analytics with the use of technologies collect the information and data necessary to decide how to boost production and take any corrective actions to achieve the goal. 3. Predictive analysis and precision agriculture On the other hand, precision farming involves a range of strategies and devices that allow farmers to optimize and improve soil productivity and quality. With these tools, you can perform the proper intervention, in the right place, at the right time, meeting the special requirements of different crops and different land areas with excellent levels of precision. 4. AI-enabled system to assess farm data and detect pests For every crop that humans grow, at least one insect or pest desires to eat it! And farms produce thousands of numbers of data points every day. But farmers can now analyze a variety of things in real-time, incorporating AI into agriculture. For example, they can install sensors in their fields to monitor when the insects emerge, and the sensors can understand what type of insect it is. If it is a helpful or neutral insect, it leaves and does nothing. But if it is a severe bug or a harmful pest, it pushes the information to the cloud. Thus, AI-based technologies help farmers optimize planning to produce more generous yields through the appropriate use of resources, management of crop choices, etc. 5. Sustainable agriculture with adequate irrigation The increasing demand for food has led farmers to increase their yield in various ways, which leads to soil abuse. In addition, growing yields over time decrease the land's quality, which produces a yield too low even to pay the price of seeds. There are several services provided by AI, such as FarmShots, which focus on examining agricultural data using drones and satellites using AI to identify pests, diseases, and reduced nutrition. Plant. Using this AI software can observe and restrict fertilizer use by up to 40 percent. Irrigation is a human-intensive process, which requires around 70% of the available freshwater. Various automation systems can now take advantage of AI and machine learning to analyze soil quality, historical weather patterns, and crop type to help farmers manage their water resources properly. Using cognitive IoT solutions can help better water management by planting the right crop at the right time, reducing water wastage, and improving yields. What is the reach of AI in agriculture? Agriculture has witnessed an accelerated adoption of machine learning and artificial intelligence algorithms in field farming techniques and agricultural products. Today, cognitive computing has become an innovative artificial intelligence technology in agriculture, which can experience, learn and react to various situations to improve efficiency. AI can also help farmers predict demand by analyzing historical food demand patterns, population growth rate, staple food patterns by region, and other data and information. The scope of AI in agriculture is broad and allows for spraying using sensors, weeding, and other means installed in drones and robots. These technologies help save the excessive use of pesticides, water, herbicides, preserve soil fertility, and contribute to the efficient use of labor and increase productivity while improving quality. Final Thoughts These AI-based technologies are used today to solve the goals of various industries such as transportation, finance, healthcare, and now agriculture. The implementation of this AI technology has transformed the entire food journey with huge benefits. For example, artificial intelligence helps farmers automate their cultivation and farming and leads to precise agriculture for better crop yield and better quality while using fewer resources. AI uses modern techniques that help farmers observe their crops without needing to monitor the inside of the farm personally. Today, several companies and start-ups are eagerly awaiting the development of AI in agriculture. AI in agriculture is redefining the conventional model of agriculture. The future of AI in agriculture is becoming progressive in developing a global transformation with different advanced strategies.

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