Smart Crop Monitoring and Automation Irrigation System Using Machine Learning and IOT

Abstract

Agriculture is still a major occupation in rural areas of India. Increase in technology creates many opportunities in different fields and attracts human resources from rural areas. Farmers are facing sever human and natural resource problems. Monitoring crops with low man power is the major problem. Smart crop monitoring and automation irrigation system deals with these problems by developing a mobile application which helps farmer to get detailed information about plant diseases and to use irrigation system efficiently. This model uses image processing techniques to identify the picture of the leaf and also provides information about temperature and moisture on field. The Raspberry Pi is the project's control unit, which controls and executes the entire system's operation. Pi camera is placed at the face of the moving vehicle to take the pictures of the leaves. These pictures are analyzed using convolution neural network which is an efficient machine learning algorithm. If the captured leaf image has a disease that is already in the given dataset then farmer will get output message which contains disease cause and pesticide or fertilizers we need to provide to eradicate the disease. Mobile application also sends the data which is sensed using sensors.

Code and data availability

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