CLASSIFICATION OF PLANT LEAF DISEASES USING MACHINE LEARNING AND IMAGE PREPROCESSING TECHNIQUES WITH SMART AGRICULTURE

CLASSIFICATION OF PLANT LEAF DISEASES USING MACHINE LEARNING AND IMAGE PREPROCESSING TECHNIQUES WITH SMART AGRICULTURE

• Yashodhan Sonawane¹ 2) Dhiraj Khachane² 3) Onkar Khaire³
  Dr. A.D.Sonawane

^#Department of Electronics & Telecommunication, RSCOE
Pune, Maharashtra, India

Abstract— Farm crops are often ruined by various diseases. This means the farmers have to incur huge losses. They can't barricade their entire fields or remain on the field all day. We propose here a leaf disease detection system with smart agriculture. In this system, the various sensor detects wildlife and environmental conditions on the eld, as well as possible intruders. When any suspicious activity or condition is detected, it reports to the owner of the field. It acts as a system that is adaptable and provides farmers with a practical means of protecting their crops from major diseases and land from attacks. This system proposes a machine learning approach that is based on improved convolutional neural networks (CNNs) for the real-time detection of leaf diseases. The smart Agriculture part checks the water level in the soil if it is low the system will automatically send readings to farmers. It also has a smoke sensor if smoke is detected the system will automatically sprinkle water in the field. This ensures the complete safety of crops thus protecting the farmer’s loss.

Keywords—machine learning, CNN algorithm, detection, monitors, report, moisture, smoke, sensor