Dr Veronica Naosekpam thank you for your contribution to the discussion

Yes, farmers are now using robots and machine learning algorithms for agricultural processes such as precision farming, automated seeding and harvesting, soil analysis, automated irrigation, and livestock monitoring. Robotics brings precision and efficiency to repetitive and labor-intensive tasks. These versatile machines can handle a wide range of tasks, from planting and irrigation to pest control and soil analysis. By automating these processes, farmers can reap the benefits of increased productivity, reduced labor costs, and a reduced need for harmful chemicals. With AI, farmers are better able to monitor crops to adjust in real time to events like the recent rainstorms in California, or drought conditions, to alter water input or put up canopies. AI utilized plant growth data to further advise on crops that are more resilient to extreme weather, disease or harmful pests. AI algorithms can analyze the chemical composition of soil samples to determine which nutrients may be lacking. AI can also identify or even predict crop diseases. Agricultural robots applying precision techniques can significantly reduce the amount of pesticides used by applying pest-detection robotic solutions and eliminating those using precision techniques. The same kind of state-of-the-art agricultural solutions can now be found in autonomous seeding robots. AI can help detect field boundaries and bodies of water to enable sustainable farming practices, improve crop yields, and support India's 1.4 billion people and the rest of the world. Agricultural robots, also called Agribots or Agbots, use artificial intelligence (AI) technology to perform agriculture activities like harvesting, sowing, mowing, and spraying, among others. These robots have automated tasks, enhanced productivity, and reduced labour-intensive processes, saving time and money.Robots are used on crop farms for harvesting, weed control, mowing, pruning, seeding, monitoring, spraying, sorting, and packing. On livestock farms, robots can perform the tasks of feeding, milking, monitoring, cleaning, and herding. Interest in mobile robotics in agriculture has grown considerably in the last few years due to its ability to automate tasks such as planting, irrigation, fertilization, spraying, environmental monitoring, disease detection, harvesting, and weed and pest control. Agricultural robots are pieces of technology that help farmers complete a range of tasks. They can be programmed to assist farmers with harvesting, weed control, planting seeds, cloud seeding, soil analysis and much more. Using image recognition technology based on deep learning, we can now automate detection of plant diseases and pests. This works using image classification, detection, and image segmentation methods to build models that can “keep an eye” on plant health. Artificial Intelligence (AI) technologies have recently been applied to the field of plant pathology for identifying plant abnormalities and infestations. These technologies can have the capability to transform the method in which plant maladies are identified, diagnosed, and managed. Different AI techniques like convolutional neural network, artificial neural network, and deep learning have been successfully used for disease detection in rice, wheat, maize, cotton, tomato, peas, potato, cucumber, cassava, berries, peach, grapes, olives, mango, banana, apple, sweet paper, tea, and so on. Some types of AI, such as machine learning, allow for the efficient analysis of vast datasets, identifying patterns, and generating key insights. Predictions can then be made for medical diagnosis and personalized treatment recommendations.

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