Artificial Intelligence to Transform Gardening Practices and Promote Sustainable Horticulture for a Greener Future

The rapid progress of agricultural technology has highlighted the need for more creative tools to adequately maintain the plants' health. Early disease detection and accurate plant identification are essential for preventing crop losses and advancing sustainable agriculture. To accomplish this, the proposed approach aims to design a web application that utilizes deep learning methods to identify the disease-robust plants that were fed to the System. The proposed approach offers very accurate disease and plant species identification by using the Convolutional Neural Network CNN ResNet-34 model. The system achieves an overall accuracy of 99.3% for plant identification and disease detection by processing user-uploaded plant photos with exceptional precision. The proposed approach performs better than other systems on the market, such as PlantSnap and Plantix, with quicker response times and better accuracy metrics. By incorporating state-of-the-art AI technology into an approachable platform, this initiative helps informed decision-making in agriculture and improves plant health management.