Plant Disease Detection And Fertilization Suggestion Using A.I
Author(s):
Harish Yadav, Prajwal Dewangan, Pradip Abuj, Aakanksha Patne, Rohan B. Kokate
Keywords:
Agriculture, Artificial intelligence, Disease detection, CNN, Image processing.
Abstract
Automation of plant diseases in agriculture is the primary concern of every country as the demand for food is increasing rapidly due to population growth. In addition, modern technology has improved the efficiency and accuracy of plant and animal disease detection. The detection process is the first step in a series of activities aimed at fighting diseases and limiting their spread. Some diseases are also transmitted between animals and humans, which is why the fight against them is difficult. For many years, scientists have been researching how to treat common diseases that affect both humans and plants. However, many aspects of the detection and discovery process have yet to be completed. Some diseases will turn out to be pandemics because it is difficult to detect them in time due to the fact that the technology used in medical processes was not enough to detect all diseases in time. Our goal is to define ailments more deeply and show how AI can quickly identify them. We discuss how machine learning and deep learning can be used to automatically detect plant diseases. The shift from traditional machine learning to deep learning in the previous five years is another area of ​​focus in our study. Deep discussions are also held on various datasets related to plant diseases. There is also a presentation of difficulties and problems with current systems. Automatic disease detection is a feature of the proposed system.
Article Details
Unique Paper ID: 159365

Publication Volume & Issue: Volume 9, Issue 11

Page(s): 1154 - 1158
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