Abstract:
The full results of my plan, which is a "seasonal fruit distribution system," are available here. The steps used to turn the concept into a functional website are covered in full in this article. For system users, one specific characteristic that stands out is the user dashboard. The economy depends on agriculture; hence diseases of plants must be kept to a minimum. Although it is crucial to identify issues early on, inspecting by hand is labor-intensive, sluggish, and prone to mistakes. It also takes a lot of time. Fruit shape, texture, and color data may be extracted using artificial intelligence, which can help with virus diagnosis. In this project creating a web application for the webpage displays the company's basic details, a fruit list, and information on field leases. Additionally, the user may schedule a meeting in the field lease by choosing a location by acors and they can schedule a meeting to purchase fruits in bulk. In the web app user interface, a dataset of fruits will be used to analyze certain information provided by the user. Following the application of several models, an accuracy outcome will be displayed in the website. Also create a detection system to detect 4 class of data like: ‖Rot_Apple‖, ―Scab_Apple‖, ―Normal_Apple‖ & ―Blotch_Apple‖. Applying CNN model to generate the disease detection through the web app. This project consists two dashboards like: User dashboard & Admin dashboard. The report includes the structure, style of the user interface, and technologies utilized in the building of the web application, covering every step from inception to execution. Python was employed for the backend. MySQL was utilized as the database system and JavaScript and ReactJS for the user interface. All you need to set up our system application is a regular desktop computer and internet connectivity; you don't need any expensive software or computer components.
