Deep Learning Software for Identifying Medicinal Plants and Their Benefits

Project Code :TCMAAN1171

Objective

The primary objective of the application is to provide an efficient tool for the accurate identification of medicinal plants, enhancing user knowledge and safety. It aims to create an engaging learning environment through interactive features and personalized suggestions. The system seeks to bridge the information gap for users lacking botanical expertise, empowering them to make informed decisions.

Abstract

DEEP LEARNING SOFTWARE FOR IDENTIFYING MEDICINAL PLANTS AND THEIR BENEFITS-ANDROID

ABSTRACT

The development of an Android-based application designed to assist users in detecting medicinal plants and providing appropriate suggestions for their usage. The application incorporates a seamless user flow with essential features, including user registration, secure login/logout functionality, plant input detection, and intelligent medicine suggestions based on plant attributes. The core functionality revolves around leveraging image processing and AI-powered detection algorithms to identify medicinal plants from user inputs (e.g., images). Upon successful detection, the application cross-references a comprehensive database of medicinal plants to provide accurate information about their properties and potential uses. Users can register and log in to store personalized data, enabling them to keep track of previous searches or preferred suggestions. The user interface is designed for simplicity and efficiency, ensuring ease of use for individuals with minimal technical knowledge. The application fosters an educational environment for promoting awareness about natural remedies and the sustainable use of plants in healthcare. This innovation contributes to the broader domain of digital health and natural medicine, providing a portable, reliable, and accessible tool for individuals interested in plant-based treatments. The application offers a new avenue for the integration of technology with traditional medicine, opening possibilities for enhanced public health outcomes and biodiversity conservation.

Keywords: Android application, medicinal plants, detection system, medicine suggestions, natural remedies, AI-based identification.

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

Block Diagram

Specifications

SOFTWARE FRONT END REQUIREMENTS

H/W CONFIGURATION:

  • Processor                        -    I3/Intel Processor
  • RAM                              -    8 GB
  • Hard Disk                      -    1TB

S/W CONFIGURATION:

  • Operating System                   -   Windows 10          
  • JDK                                         - java
  • Plugin                                     - Kotlin
  • SDK                                        - Android
  • IDE                                         - Android studio
  • Database`                                - MY SQL

Demo Video