This system mainly focus to increase the productivity of rice crops which is one of a critical problem that the farmers are facing. Using Php code this study helps to connect globally the farmers through online-Global Positioning System and know their productivity and problems that they face during production. Images of rice crops captured by the farmers with the very short duration of rice growth period is uploaded. The LAB values are determined for the captured image. Clustering and segmentation is done for the images to separate the foreground and background of the image. These values are compared with the pre-estimated Nitrogen(N) values that are obtained using (leaf color chart) LCC. Multi class support vector machine(MSVM) is used to procure the amount of Nitrogen values to be tacked on to make the crop lusher. Based on the N value status the amount of urea to be added is determined. When the farmer capture picture of the rice crops, the amount of N present in it will be displayed on the screen.

Production, Rice crops, ICT

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