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Abstract
Agriculture is the backbone of our motherland-India and it places a major contribution to our economy. Most of the people in our country are practicing agriculture for generating income but the environmental factors like temperature, humidity and nutrient levels are affect the crop growth and reduces the yield.This project aims to observe the status of the nutrient level in the soil, humidity in the moisture, temperature in the atmosphere by using IOT sensors and analyses the status of the crop growth with the help of image processing techniques. The environmental factors are recorded with sensors and the image of paddy is captured by the camera. Then the captured image is pre-processed to remove the noise by median filters, image segmentation done by Otsu’s method, feature is extracted by SURF (Speeded-Up Robust Feature) and classification is carried out by SVM (Support Vector Machine).The proposed work classifies the paddy into well grown leaf with good yield and affected leaf with decreasing yield. The proposed algorithm classifies the leaf with 90% of accuracy.