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Myrtle

Plant and Raw Material Identification Website

Overview

Myrtle is a cutting-edge online platform developed by team QuantumFrost for SIH to assist users in the accurate identification of various medicinal plants and raw materials. This innovative project leverages image processing and machine learning algorithms to provide insightful information about these botanical resources. With a rich heritage of floral diversity, India is renowned for its medicinal plant wealth, yet the identification of these valuable resources remains a significant challenge in Ayurvedic Pharmaceutics.

Problem Statement

India's diverse landscape, seasonal variations, and similar characteristics among different plant species have led to confusion and misidentification of medicinal plants and raw materials in the market. This misidentification extends to collectors, traders, and consumers alike, impacting the quality and efficacy of herbal products. The project addresses this pressing issue by developing a sophisticated software solution capable of accurately identifying these resources.

Key Features

1. Augmented Reality (AR) Plant Identification (AR, Computer Vision, Real-time Tracking)

  • Easily identify plants by pointing your smartphone camera at them.
  • Real-time information overlays on your screen, thanks to computer vision and real-time tracking.
  • An immersive experience that makes plant identification a breeze.

2. Blockchain-Verified Authenticity (Blockchain, Cryptocurrency)

  • Verify the authenticity and origin of medicinal plants encountered in the wild.
  • Each verified plant has a blockchain record, ensuring its source and quality.
  • Secure transactions are supported by cryptocurrency, providing assurance.

3. Machine Translation for Local Knowledge (Natural Language Processing, Machine Translation)

  • Travel to regions with different languages without worry.
  • The app translates plant information into your preferred language.
  • Access local knowledge effortlessly as you explore.

4. Customizable Plant Libraries (Data Science, Data Analytics, User Management)

  • Create, customize, and manage your personal plant libraries within the app.
  • Add notes, photos, and share your collections with the community.
  • Advanced data analytics ensure a seamless user experience.

5. Offline Mode and Multispectral Imaging (IoT, Big Data, Multispectral Imaging)

  • Use the app even in remote areas with limited internet connectivity.
  • A locally stored database of common plant species ensures accessibility.
  • Multispectral imaging technology enhances plant identification accuracy.

6. Geolocation Integration and Interactive Map (Geolocation, Internet of Things)

  • Input your location or use GPS data to narrow down potential plant species.
  • Explore nearby plant life on an interactive map with geolocation features.
  • IoT technology enhances your plant exploration experience.

7. Herbal Consultancy and Community Contribution (Chatbots, Community Engagement)

  • Connect with experts, researchers, and botanists through AI chatbots.
  • Get advice on medicinal plants and enhance your knowledge.
  • Contribute to the community by submitting plant information, images, and insights.

8. Plant Marketplace (E-commerce, Cryptocurrency)

  • Purchase specific medicinal plants from verified sellers within the app.
  • Secure transactions are supported by cryptocurrency, ensuring trust.
  • Explore a marketplace dedicated to authentic and high-quality plants.

Getting Started

To explore the Plant and Raw Material Identification Website, follow these steps:

  1. Visit the Website: Go to [https://myrtle-eta.vercel.app/]

  2. Upload an Image: Upload an image of a plant or raw material you want to identify.

  3. Receive Identification: The machine learning model will analyze the image and provide accurate identification along with detailed information.

  4. Browse the Database: Explore the extensive database to learn more about various plant species and raw materials.

Contributions

Contributions to the website, including code improvements, database updates, and educational content, are encouraged. Please refer to the Contribution Guidelines for details on how to contribute.

Feedback

We value your feedback! If you encounter any issues, have suggestions, or want to share your experience, please use the built-in feedback mechanism on the website.

License

This project is licensed under the Apache License - see the LICENSE file for details.

Acknowledgments

We extend our gratitude to the online community for supporting this project and to the open-source community for their invaluable contributions.