Detecting Plant Disease and Suggesting Sustainable Solutions by using Deep Learning Technique

Crop loss due to pests and diseases poses a significant challenge in global agriculture, resulting in substantial economic ramifications, with an annual loss of crops valued at Rs 50,000 crore. This project addresses the pressing issues surrounding disease identification and management in agriculture. To revolutionize disease detection, we are pioneering an innovative approach leveraging Convolution Neural Networks (CNNs). By harnessing the power of AI platforms in collaboration with government resources, our aim is to deliver effective and efficient solutions to combat plant diseases. Our overarching goal is to simplify the process of disease identification and treatment through the utilization of advanced technology. Our project harnesses various convolution neural networks, including VGG-16, ResNet, DeepNet, and YOLO V3. We intend to train our model using these convolutional networks and select the one that exhibits the highest accuracy for our specific project requirements. Beyond merely identifying the type of disease, our project also provides tailored remedies for treating these specific diseases. We leverage Chat GPT technology and collaborate with government platforms to achieve this objective. Additionally, we translate these remedies into local languages to ensure accessibility for those in need. Moreover, we employ text-to-speech conversion, enabling the vocalization of remedies. This empowers farmers to receive guidance audibly and take prompt action to mitigate crop diseases.