Agriculture is important for the economic sector of every country. Everyone in whole world is directly and indirectly dependent on agricultural products for everyday needs. The demand for food is increasing with the global population on a daily basis. At this point, the traditional techniques of farmers are insufficient to meet the demand. Some novel automation techniques are required to meet the current demand globally for agricultural produce. Artificial Intelligence in the agriculture sector is playing a very important role to transform the agriculture industry. AI has the potential to transform traditional agriculture by increasing the efficiency of time, labor, and resources, increasing environmental sustainability, providing accuracy in monitoring and data analysis for better agricultural results. AI useful in agriculture from seed to seed involves improving crop production, preservation, harvest, processing, and marketing. Many high-tech computer-based tools and agri-bots have already been introduced to determine various important parameters for better agriculture. In this article, we will discuss how artificial intelligence is revolutionizing agriculture by employing more efficient methods along with difficulties in AI adoption.
Artificial Intelligence
Artificial Intelligence is a tool that mimics human intelligence and ability processes by machines, advanced computer systems, robots, and digital devices. AI has many uses, including natural language processing (NLP) for understanding spoken human language, computer vision for viewing analog-to-digital conversions such as video, and speech recognition and expert systems for mimicking information.
www.justagriculture.in page579 The three cognitive abilities of learning, thinking, and self-improvement are the foundation of AI encoding, which rely on every action and result. In recent years, the fastest growing industries include banking, healthcare, retail, pharmaceutical research, intelligent process automation, marketing, and agriculture.
Why is AI necessary in farm?
We need to use some innovative technologies to overcome the obstacles in traditional agriculture. The difficulties in farming when using traditional methods are as follows:
Labor Challenges: It would be challenging to access enough labor for agricultural practices due to expensive labor costs. This issue immediately affects the income and production of the agricultural sector.
Weather Factors: Using traditional methods, we are unable to predict sudden weather changes that negatively impact our agriculture and cause difficulties with sowing, harvesting, and spraying.
Decision Making: When it comes to improving agriculture, traditionally we have not been able to make intelligent decisions about sowing, crop variety selection based on field characteristics, irrigation timing, soil nutrient deficiencies, spraying area, or dosage calculations.
Accuracy in Data Collection and Analysis: It is impossible to collect accurate data on insect pests, diseases, and weeds without the use of cutting-edge technologies. We can reduce the amount and applications of pesticides using accurate data for better crop production.
Use of AI in Agriculture
Farmers will face many challenges, just as they would with traditional farming methods. AI is being widely used in this sector to address these challenges. Artificial Intelligence has become a game-changing technology in agriculture. AI benefits farmers in various ways, which are detailed below.
1. Environmental Protection:
AI allows for more efficient ways to produce, harvest, and sell crop products, as well as inspect defective crops and focus on improving agricultural practices for environmentally friendly crop production. AI provides us with more accurate data about insect pest infestations, diseases, and weeds, as well as different management methods. AI methods based on robotics, computer vision, and machine learning can assist farmers in spraying chemicals only where the pests are, reducing the use of chemicals sprayed throughout the field. Environmental protection through pesticide reduction is a major functional benefit of AI technology. Hence, AI technology assists framers in pest control and reduction of pesticide residues.
2. Weather and Price Forecasting:
Weather plays a vital role in agricultural decision making and planning. Artificial Intelligence technology can allow farmers to obtain weather data, which will be helpful for timely sowing, harvesting, spraying, and other agricultural practices; increasing crop yield and profits by minimizing crop risk. Weather predictions can also help with pest management; taking precautions by adopting timely practices, reduces input costs and yield loss. Farmers can use price forecasts to get a clear idea of crop prices in the coming weeks, allowing them to maximize profits.
3. Pest Pests and Disease Detection:
AI methods are able to monitor pests and diseases, and are helpful in identifying pests as well as the areas that are affected by them. We can now identify plant diseases and pests using image recognition technology based on deep learning. This technology builds models that can “take a look” at the health of the plant using image classification, detection, and segmentation methods. Using AI techniques monitoring, detection, and management of insect pests and plant disease is made easy and eco-friendly. After using AI-based techniques, there is a noticeable reduction in the amount and number of pesticide applications; able to accurately identify and count a large number of insects. AI computer vision has a bright future for tracking the state of our food systems. Apart from reducing labor inefficiencies, it also does so without compromising the accuracy of the data.
4. Soil Health Monitoring:
Today, good soil health is essential to meet the growing demand for food. However, using traditional methods, we are unable to determine specific soil properties for each crop. Artificial Intelligence (AI) and Machine Learning (ML) technologies have made it possible to track soil characteristics in fields, such as quality, fertility, microbial and nutrient deficiencies, as well as vegetation patterns, either through image capture with a camera recognition tool or by using a deep learning-based tool. Visual perception AI can analyze and interpret this data better than humans to monitor crop health, make accurate yield predictions, and identify crop malnutrition. AI models can alert farmers to particular problem areas so they can respond immediately.
5. Innovations in Harvesting Methods:
Harvesting crops requires a lot of work and effort. AI-based computer vision models are helpful in observing and estimating crop growth maturity without hiring more people. A variety of agribots have already been developed to automate harvesting; reducing losses, costs, environmental impact and food waste. AI-powered equipment outperforms human agricultural workers in terms of speed, difficulty and accuracy. A significant portion of that work is now being handled by AI with ease and remarkable efficiency.
6. Intelligent Spraying:
Using UAVs types of equipped with computer vision AI, ecofriendly pest management requires that the required amount of pesticides or fertilizers be sprayed as uniformly as possible in the target spraying area. With real-time recognition of target spraying areas, UAV sprayers can operate with extreme accuracy in terms of area and amount to be sprayed. As a result, we can reduce animal poisoning, natural resource contamination and pesticide residues in crops. Virginia Tech has developed a smart spray system based on servo motor controlled sprayers that use computer vision to identify www.justagriculture.in Page 582 weeds, analyzing the size, shape and color of each pesky plant to deliver the exact amount of herbicide at the right time.
8. Livestock Health Monitoring:
We cannot neglect the importance of animals in our agriculture system and they require a little more tracking than plants. Cattle Eye is an excellent illustration of an AI-first agriculture company. Management of couches made easy by using cameras and drones (UAVs) for data collection. Tracking animal health and behavior, identifying abnormal behavior and monitoring vital activities like giving birth are all made possible with ease and accuracy using overhead cameras and computer vision algorithms. Remote tracking and observation of cattle can be useful to quickly spot issues and inform farmers about the health of their livestock and access to food and water.
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