Deep Learning approach for Identification and Classification of Tulsi Leaf Disease

Tulsi (Ocimum sanctum) is commonly known as holy basil; it consists of numerous amounts of medicinal value. It is popular not only for the medicinal value it has, but also for its spiritual significance in many parts of the world for its healing and traditional aspects. However, environmental destruction and not taking care of the Tulsi plant can impact the leaves and overall growth of the plant. This approach helps improve Tulsi plant health by using a smart application. The dataset used is collected from the local environments from different locality to get different insights on the Tulsi plant. The dataset is then preprocessed to enhance the data quality and model performance. This application incorporates features which is user friendly interface and allows individuals to check on the plant with very effortless way and in addition to this it helps user to detect the diseased leaves prior rather than last. This model not only helps the individuals but also contributes in conservation of Tulsi by promoting a healthy growth of the plant. By proper identification of the healthy and unhealthy leaves this application promotes the proper measures to be maintained for the plant health which ensures a very strong and healthy growth of the plant. This approach not only distinguishes the disease but also helps to conserve the Tulsi for the sustainability of earth as it also has the property of improving the air quality which is very essential for the environment.