Monitoring and Controlling the Infected Cereal Crops Based on Image Processing with Proposed Architecture

Agriculture is the backbone of our country. Agriculture is the science of cultivating the soil, harvesting crops, and raising livestock which is considered as one of the economic activities in Asian countries.  In India, sector of agriculture is destroying now-a-days .The main goal of this project is to increase the productivity and profit. There are several automated systems available in literature, which are developed for irrigation control and environmental monitoring in the field. However, it is essential to monitor the plant growth stage by stage and take decisions accordingly. In addition to monitoring the environmental parameters such as pH, moisture content and temperature, it is inevitable to identify the onset of plant diseases too. To prevent the losses occur in agriculture production. Plant disease identification by continuous visual monitoring is very difficult task to farmers and at the same time, it is less accurate and can be done in limited areas. Hence, this project aims to develop an image processing algorithm to detect the diseases in the rice plant. Rice blast disease occurs in rice plant due to magnaporthe grisea and this disease also occurs in wheat, rye, barley, and millet. Due to rice blast disease, around 60 million people were affected in 85 countries worldwide. Image processing technique is adopted as it is more accurate. Early disease detection can increase the crop production by inducing proper pesticide usage. Hardware prototype of the proposed system will be developed using the Arduino Processor.