IoT based Soil Nutrition and Plant Disease Detection System for Smart Agriculture

In the coming years, farmers will face challenges to feed the increasing number of populations. They need to ensure food security and reduce the dependency on imports. The effective use of new technologies to increase the efficiency of farming will help the farmers to meet the need of increased population AI and IOT related automation to be designed to improve the way a farmer operates for various tasks. We propose a framework for IoT based Soil Nutrition and Plant Disease detection which uses various sensors to collect the plant-related data in form of images at different time intervals using MY THINGS smart sensor and Soil sensors such as proximal soil sensor (PSS) to test the soil fertility which helps to analyze the condition of soil new cultivation, ploughing, water or the land for harvesting. Temperature sensors are also used. Water quality sensors are used that will keep monitoring the quality of the water. All the data will we be sent to the farmer with the help of the IoT. For image classification, Local binary thresholding is used. At harvesting time robot performs image recognition and classification. The farmer will enter the required data to use the robotic arm to automatically harvest the crop. The arm is proposed to have four degrees of freedom and will be driven by the motors. Robotic arms will identify the crop using image recognition and will put that batch in the appropriate basket to be considered by the farmer for analysis. With regular monitoring, this proposed framework can greatly aid the farmers in maintaining crop health as well as quality.