AI in agriculture aids in the detection of pests, plant diseases, and undernutrition in farms. Artificial intelligence sensors can identify and target weeds before deciding which herbicide to use in the area. Precision agriculture, often known as artificial intelligence systems, is assisting in enhancing the overall quality and accuracy of harvests.

THE ROLE OF COMPUTER VISION

You need a lot of land to feed billions of people. These days, hand cultivation is not possible. At the same time, crop failures are frequently caused by pest infestations and plant diseases. Such invasions are challenging to spot and stop in the bud given the magnitude of modern agriculture operations.

This adds a new application for computer vision techniques. Aerial photography is used by growers to identify early indicators of plant disease or pests at the macro level and close-up photographs of leaves and plants at the micro level to identify crop illnesses. The common method for computer vision used in these studies is convolutional neural networks. There are now many more applications for AI in agriculture being developed.

Please take note that we are using the term “computer vision” quite broadly here. Images are frequently not the most reliable sources of information. The greatest method to study many significant aspects of plant life is in other ways. It is frequently possible to gather hyperspectral images with specialized sensors or carry out 3D laser scanning to better understand plant health. In agronomy, such techniques are increasingly applied thanks to AI in agriculture. Although specialized models are required to process this data, convolutional neural networks in particular can be used because of the spatial organization of the data.

HOW ROBOTS ARE BEING UTILIZED IN AGRICULTURE?

Autonomous agricultural robots have the ability to dig holes in the ground and plant seeds while adhering to established basic patterns and taking into account the unique features of the area. Robots are also capable of managing the growing process and interacting with each plant separately. Robots will harvest when the moment is perfect, once again treating each plant exactly as it should.

Robots designed specifically for harvesting are being created and deployed more and more. Combine harvesters have long been in use. Still, it has only recently been able to create, for instance, a robot that selects strawberries thanks to advances in computer vision and robotics.

It is already evident that ML, AI, and robotics can function well in agriculture even though many agricultural robots are still prototypes or are only being tested on a small scale. It is safe to assume that in the near future, an increasing amount of agricultural activity will be mechanized.

WHAT IS THE FUTURE FOR AI IN AGRICULTURE?

Agriculture and animal husbandry are sometimes viewed as outdated professions. Today, however, AI in agriculture is becoming a common instrument for many farms. Due to the fact that agriculture is still one of the world’s largest and most significant businesses, even a small improvement in efficiency will result in significant gains. That is why there are a lot of companies that are prioritizing AI in agriculture.