Crop prediction and Plant Disease Detection using IoT and Machine learning

Agriculture is one of the major occupations widely used in India and it plays a crucial role in the country's development. Improving crop production is considered an important aspect of agriculture as about 60% of the country's total land is used for agriculture to satisfy the requirements of Billion people. Since agriculture plays an important role in most countries, this sector needs to be “smart”. If a farmer owns a piece of land, the farmer should be aware about the crops that can be grown in the area, the diseases that might affect the crops etc. Growing crops is a tough job because of the involvement of many different factors like soil type, temperature, humidity and so on. Technological growth in agriculture will increase crop yields. Remote sensing systems, such as IoT systems are increasingly used in smart farming systems and these generate large amounts of data. Systems which can just predict crops by evaluating soil features for a particular time period still exist, but here the proposed project will solve agricultural problems by monitoring fields using sensors for detecting soil characteristics, provide this information to the farmer in real time and introduce farmers to the most suitable crops along with feedbacks on existing crops and plant disease detection, thereby helping them to achieve greater productivity with reduced loss.