Fruits Pesticides detection Technology flutter

Project Code :TCMAAN1185

Objective

To develop a mobile-based expert system for diagnosing gynaecological diseases using Machine Learning and Natural Language Processing, offering personalized AI-driven diagnosis, voice interaction, symptom checking, and prescription generation for empowering users with private, accessible, and informed health insights.

Abstract

The Pick Fresh application is designed to connect users with nearby sellers, enhancing local commerce through a location-based and multilingual platform. Users can browse and send product requests to sellers within their area, and the application supports multiple languages including Tamil, Telugu, Kannada, Hindi, and English to ensure accessibility for a wide audience. Once a product request is submitted, sellers have the option to accept it. If the seller's location is within a 1-kilometer radius of the user, the user automatically receives a notification, enabling timely and efficient communication. Additionally, the application integrates a fruit disease detection feature that allows sellers to identify and address fruit quality issues using AI, ensuring better product standards. This innovative system improves the overall user experience by bridging language gaps, enabling intelligent product management, facilitating seamless interaction between buyers and sellers, and promoting hyperlocal engagement.

Keywords: Location-based, Multilingual, Hyperlocal, Notifications, Fruit Detection, AI-powered, User-Seller Interaction.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.