Introduction

Over 58% of India’s population relies primarily on agriculture as a source of income, making India one of the key players in the global agricultural industry. India is the world’s largest producer of milk, pulses, and spices. It also has the largest herd of cattle (buffaloes) and the largest area planted to wheat, rice, and cotton. It is the second-largest producer of wheat, rice, cotton, sugar, farmed fish, fruit, vegetables, tea, and farmed vegetables. Around half of the population of India is employed in agriculture, and the country has the second-largest agricultural land area in the world. As a result, farmers play a crucial role in the industry that produces food for us. Technology has redefined farming over the years and technological advances have affected the agriculture industry in more ways than one. AI will serve as a crucial foundation for lowering labor costs and raising productivity. Farming has always required a lot of labor, and there is still a lot of human involvement.

Using AI for intelligent spraying of chemicals:

Thousands of data points on temperature, soil, water use, weather, etc. are generated daily by farms. This information is used in real-time by artificial intelligence and machine learning models to gain insightful knowledge, such as when to plant seeds, which crops to choose, and which hybrid seeds to use to increase yields. AI systems are helping to improve the overall harvest quality and accuracy – known as Precision Agriculture. AI technology aids in the detection of pests, plant diseases, and under nutrition in farms. Artificial intelligence (AI) sensors can identify and target weeds before deciding which herbicide to use in the area. This lowers the need for herbicides and lowers costs. Numerous technical firms have created robots that accurately monitor weeds with spray guns by using computer vision and artificial intelligence. These robots can reduce the amount of pesticides typically sprayed on crops by 80% and the cost of herbicides by 90%.These clever AI sprayers may substantially reduce the quantity of pesticides needed in the fields and hence increase the quality of agricultural produce and bring in cost efficiency.

Using AI-based robots for farm harvesting :

Have you ever wondered who actually picks the produce from the agricultural land? Actually, the majority of the time, the food that ends up on your dinner plate is not the result of a regular farm worker, but rather robotic robots that are capable of bulk harvesting with greater accuracy and speed. These devices aid in increasing crop yield size and decreasing agricultural waste that is left in the field.

What Are Agricultural Robots?

Automating some tasks in the agriculture sector is what agricultural robots do. For instance, they can apply pesticides or plant seeds based on a human-programmed algorithm. Some of these robots even cooperate with actual farmers to complete the task.

The tasks that agricultural robots can accomplish vary. However, we can generally break these tasks down into four categories: weeding, harvesting, planting seeds, watering plants, and thinning.

1. Robots for Weed Removal: The labor-intensive and costly procedure of weed removal Also, it depletes the resources used by crop farmers, reducing their revenues. Many farmers are interested in adopting robots to complete this labor for them because of this. Several robots are made to remove weeds from fields, freeing up farmers to concentrate on cultivating crops. By utilizing vision sensors and GPS technology to differentiate between the weeds and the neighboring plants, you can even teach robots to pull weeds without upsetting nearby plants.
2. Robots for Crop Harvesting: The use of agricultural robots for weeding is not universal. Some of them are made to perform the actual harvesting, which is another pricey and labor-intensive aspect of farm work. Even without human operators, some of them can function. Some robotic arms, for example, were designed to work in orchards, selecting ripe fruit that was not harmed. They employ sophisticated software with an algorithm and cameras to help the system recognize ripe fruit. It can spread seeds, spray insecticides, water plants, and even thin forests. Robots used for crop harvesting can also collect information about the crop, which will help farmers measure their yields. This kind of data is as important as the actual harvest.
3. Robots for Planting Seeds: The best option for a farmer with many acres of crops to grow is not to plant seeds by hand. It would be a waste of both time and money. That is why farmers nowadays often choose to use robots to plant seeds. As mentioned before, some agricultural robots work collaboratively with humans to plant the seeds. Others can be programmed to use GPS technology to plant seeds autonomously. For example, The RoboWeeder2 has the “ability to precisely place seeds into the ground at rates as fast as 0.4 acres per hour (40 seeded rows/hour)”.
4. Robots for Watering Plants: Many agricultural robots use soil moisture sensors to determine where and when plants need watering. Many of these robots can also manage irrigation schedules for fields and adjust them automatically based on weather patterns. That way, farmers don’t have to worry about over or under-watering their crops.
5. Robots for Thinning Plants: Another weeding operation that requires extreme caution and accuracy is thinning; failure to do so could harm the crops. For this reason, a lot of people have started using robots in this process. For instance, certain robots can meet both the criteria for spacing and thinning. Thinning is the removal of extra plants that are taking up too much space. “Spacing” is the term for the recommended distance between plants. Robots can readily complete these precise duties thanks to technological advancements.

Applications of AI in Agriculture:

1. Livestock health monitoring: Animals are another major component of our agriculture systems, and they tend to need a bit more tracking than plants. Cattle Eye is a great example of an AI-first company in the agriculture industry. They use overhead cameras and computer vision algorithms to monitor cattle health and behavior.This means that spotting a problem isn’t dependent on a cattle farmer being right there next to the cow. Instead, the cattle can be tracked and monitored remotely and in real-time so that farmers can be notified as soon as a problem is observed.Computer vision can also
   • Count animals, detect disease, identify unusual behavior, and monitor significant activities such as giving birth.
   • Collect data from cameras and drones (UAVs).
   • Combine with other technologies to keep farmers informed on animal health and access to food or water.
2. Intelligent spraying: UAVs equipped with computer vision AI make it possible to automate spraying of pesticides or fertilizer uniformly across a field. With real-time recognition of target spraying areas, UAV sprayers are able to operate with high precision both in terms of the area and amount to be sprayed. This significantly reduces the risk of contaminating crops, humans, animals, and water resources. While the potential here is great, currently some challenges still exist. For example, spraying a large field is much more efficient with multiple UAVs, but assigning specific task sequences and flight trajectories for individual crafts can be tricky.
3. Automatic weeding: Not every AI is a weedier, as intelligent sprayers are. Some computer-vision robots are removing undesirable plants in even more direct ways. Physical weed removal not only saves the farmer a lot of labor but also lessens the need for chemicals, making the entire agricultural process much more sustainable and environmentally benign.
4. Aerial survey and imaging: Surveying land, monitoring crops, and monitoring livestock are all excellent uses for computer vision.AI can scan satellite and drone photos to help farmers monitor their animals and crops. The accuracy and effectiveness of pesticide application can be improved with the help of aerial imagery.
5. Produce grading and sorting: Finally, even after the crops have been harvested, AI computer vision can still assist farmers. Imaging algorithms can be used to separate “excellent” product from defective or unsightly produce, much as they can be used to detect flaws, disease, and pests as the plants grow. Computer vision can automate the grading and sorting process by evaluating fruit and vegetables for size, shape, color, and volume with accuracy rates and speeds that are far greater than even those of a qualified professional.

Conclusion:

Artificial Intelligence in agriculture assists farmers in automating crop management functions. Technology has been employed in agriculture for a very long time to increase productivity and lessen the amount of demanding manual labor needed for farming. Since the advent of farming, humankind and agriculture have evolved together, from better loughs through irrigation, tractors, and AI. The most valuable applications of AI in agriculture are poised to be agricultural robots. Thousands of milking robots are currently working at dairy farms. By the end of 2023, this segment is anticipated to grow from $1.9 billion to $8 billion. In the upcoming three to five years, it is conceivable that robots will be created to do a wide range of more complex duties. When the climate changes, crop and soil monitoring systems are also essential