Paddy Leaf Disease Identification and Automated Remedial Initiation using Pesticide Sprayer

Rice is one of the most important staple crops in the world, providing food for billions of people. However, several illnesses, such as paddy leaf diseases, which can drastically lower crop yields and quality, frequently pose a threat to rice production. Our goal is to create a system that can automatically detect diseases in paddy leaves and use a pesticide sprayer to start corrective action. The pesticide sprayer is triggered to apply the appropriate treatment by the system, which uses image processing techniques to determine the type and severity of the disease. The proposed model detects paddy leaf diseases and provide necessary pesticide for the treatment of these diseases through an automated pesticide sprayer system. With this we could drastically lower the workload and expenses related to manual disease identification and treatment, the system is made to be economical, effective, and user-friendly. In addition to lowering the time and expense involved in diagnosing and treating diseases, the system is anticipated to increase treatment efficacy and precision. By limiting the quantity of pesticide used and lowering the possibility of overuse or misuse, the system is also anticipated to lessen the negative effects of pesticide use on the environment. All things considered, this project is a significant step toward the creation of creative and sustainable solutions to the problems the agriculture sector faces.