AI & ML Based Crop Disease Detection

AI & ML Based Crop Disease Detection

Dhanashri Pagar1, Uchita Thakare2, Priyanka Borse3, Dr. Ulhas Patil4

1 UG Student, Dept. of  E&TC, MVP Samaj’s Karmveer Baburao Thakare College of Engineering, Nashik, Maharashtra

2UG Student, Dept. of  E&TC, MVP Samaj’s Karmveer Baburao Thakare College of Engineering, Nashik, Maharashtra

3UG Student, Dept. of  E&TC, MVP Samaj’s Karmveer Baburao Thakare College of Engineering, Nashik, Maharashtra

4 Associate Professor Dept. of  E&TC, MVP Samaj’s Karmveer Baburao Thakare College of Engineering, Nashik, Maharashtra

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ABSTARCT - In the agricultural field, crop diseases and physiological disorders have a large impact on its yield and quality. Minimizing Pomegranate yield is highly affected due to various diseases. The diseases have a tendency to show signs on the plant that can be easily detected by the cameras. These diseases can be identified by collecting the image data of leaves over a period of time, applying the algorithm of segmentation, noise reduction, data extraction using mean pixel value of channels and canny edge detection. Further the study can be extended to design AI based hardware to implement the discussed algorithmic process of disease identification using fruit’s disease detection.

This project will be succeed in detecting the diseases, which in turn helps the farmers to detect the crop diseases at their early stages.

Artificial Intelligence & Machine Learning powered by 4G has opened new doors of technology and innovations in the field of agriculture. There is a vast scope of application and development of the above mentioned technologies to detect any shortcomings that may lead to heavy losses for farmer. The use of Artificial Intelligence & Machine Learnings to analyze the data collected from fruits detection and identify the diseases that may affect the pomegranate yield.

Keywords:{Pomegranate, AI, Sensor, Image Processing, Edge Detection, Leaf detection, RGB, Segmentation.}