ABSTRACT
The agricultural sector is one of the most critical industries in the world, especially in India. It is considered the primary source of income for more than 60% of Indians. Like any other industry, the agriculture industry faces problems like climate change, labor shortage and the effects of pandemics. The complexity of agricultural management is a daunting task that can be handled only by highly experienced individuals. This is why it is often difficult to carry out manual inspections. As digital technologies transform every industry, they are also transforming agriculture. In agriculture, computer vision technology is expected to increase efficiency and reduce the risk of errors. This discipline combines the theory and technology of artificial intelligence to develop systems that can collect and interpret data. Artificial intelligence and computer vision, especially the idea of deep learning, have emerged as promising approaches to broader issues in agriculture. They have made various contributions in fields such as the detection and classification of plant disease, plant health monitoring, animal monitoring, weed detection, quality inspection of agricultural food products, forecasting and harvesting of crops etc. Because deep learning uses more complex models, which make massive parallelization possible, it can solve more complicated problems quickly and satisfactorily. Here, we are essentially focusing on the application of artificial intelligence and computer vision technology so far developed or utilized by various specialists in the field of agriculture.
