Artificial Intelligence Technology in the Agricultural Sector

Project Code :TCMAPY1567

Objective

The primary objective of this project is to develop an AI-powered agricultural system that assists farmers in making informed decisions about soil health, crop selection, disease management, and pest control.

Abstract

The Fashion Adviser App is an intelligent and user-centric application designed to provide personalized fashion recommendations using advanced AI capabilities powered by the Gemini API. The app offers a seamless interface where users can register, securely log in, and interact with the system to receive outfit suggestions tailored to their style preferences, occasion, or seasonal trends. Once logged in, users can input their fashion queries or needs, and the app processes this data via the Gemini API to generate accurate and stylish recommendations. The system maintains a personalized profile for each user, allowing them to manage their preferences and access past recommendations. Designed with simplicity and effectiveness in mind, the application enhances user engagement and decision-making in everyday fashion choices. The logout feature ensures a secure exit, maintaining session integrity and data privacy. This solution not only simplifies the fashion selection process but also introduces a smart, AI-driven approach to daily dressing, making fashion guidance accessible and interactive. With potential for future enhancements like style history, wardrobe integration, and voice-based inputs, the Fashion Adviser App stands as a modern solution for personalized, tech-assisted fashion consultation. Keywords: Fashion recommendation, Gemini API, personalized styling, user profile, AI-based suggestions, outfit planning, smart wardrobe, secure login, interactive interface, fashion adviser.

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

Specifications

H/W CONFIGURATION:

·       Processor                                 - I3/Intel Processor

·       Hard Disk                                - 160GB

·       Key Board                               - Standard Windows Keyboard

·       Mouse                                     - Two or Three Button Mouse

·       Monitor                                   - SVGA

·       RAM                                       - 8GB

S/W CONFIGURATION:

·       Operating System                   :  Windows 7/8/10

·       Server side Script                    :  HTML, CSS, Bootstrap & JS

·       Programming Language         :  Python

·       Libraries                                  :  Flask, Pandas, MySQL. Connector, Os, Smtplib, Numpy

·       IDE/Workbench                     :  PyCharm

·       Technology                             :  Python 3.6+

·       Server Deployment                 :  Xampp Server

Demo Video

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