In this work, we explain a framework for early detection of diseases in wheat crops from visual symptoms. We target wheat crops owing to their extensive use in the Indian subcontinent. Existing literature lists several algorithms that can be used in detection, classification, and quantification of crop diseases by analysis images. However, the evaluation process is tedious, time consuming and more over very much subjective. Infrastructure for image acquisition, communication, and processing is lacking in rural areas owing to lesser technological penetration. In this work, we will develop a user-friendly IoT reference architecture to provide on-field disease detection and prediction using cloud analytics.

IOT, Image Processing, Wheat Crops, Disease

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