SmartCropCare: An Integrated Approach to Advanced Agriculture and Crop Health
摘要
In the ever-evolving landscape of agriculture, embracing digital advancements is crucial for sustainable and efficient crop management. Building on previous work that incorporated IoT for real-time monitoring and crop recommendation systems, this work, titled “SmartCropCare” advances traditional farming practices through the integration of image-based analysis for disease detection. The system utilizes ResNet9, a customized deep neural network, to classify crop leaves, accurately distinguishing between healthy and diseased states. Upon detecting a disease, the model identifies the specific ailment and provides tailored solutions for effective disease management. By enhancing the precision of disease detection, SmartCropCare empowers farmers with a powerful tool to make informed decisions, thereby increasing efficiency, productivity, and profitability in the agriculture industry. This work not only embraces the latest technological advancements but also continues to build upon previous innovations to offer comprehensive and practical solutions for modern farming challenges.