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AI/ML
Farmer Supporter
Summary

Make a significant impact on the agricultural sector by developing a website that assists farmers in making informed decisions. This project focuses on leveraging AI to provide expert advice on crop management, market insights, and real-time problem-solving.

Requirements
  1. Integrate features for adding and managing produce listings.
  2. Offer offline storage for articles and chat history.
  3. Include agricultural knowledge updates, weather forecasts, and pest alerts.
  4. Ensure the AI can guide through complex agricultural decisions.

Submission Guidelines

  1. Figma (Optional): Provide a link to your Figma design / prototype for your project.
  2. GitHub Repository: Provide the link to your GitHub repository containing all the relevant source code and project files.
  3. Deployed Link: Share the link to the deployed version of your project. For web applications, consider hosting on platforms like Netlify or Heroku. If it's a mobile app, upload the APK to Google Drive and provide a public link.
  4. Walkthrough/Presentation: Create a concise 2 to 5-minute maximum screen recording. Walk through key features, functionalities, and any unique aspects of your project. Clearly articulate how users can interact with and benefit from your solution. Ensure your presentation covers essential details without exceeding the time limit.
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Limited OpenAI API keys available at no cost for your hackathon project. Reach out here with your use case, and get keys for Speech-to-Text, Chat Completions, Embeddings, and more. Keys deleted post-hackathon.

Explore Models

You have the freedom to explore a wide range of models for your project. Not limited to the following options:

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Additional Resources

Take your project further with these valuable resources:

Suggested Approach

Day 1 - 2: Project Planning & Setup

Product Management & AI/ ML Specialists:
  • Define project scope and objectives clearly.
  • Identify key AI functionalities needed: NLP for chat, data analysis for market insights, algorithms for weather and pest predictions.
  • Establish a roadmap and assign roles.
Frontend & Backend Developers:
  • Set up the basic structure of the website.
  • Plan the UI/UX design in collaboration with Product Designers.
  • Establish a version control system and project repository (e.g., GitHub).
Data Science & AI/ ML Specialists:
  • Research and select appropriate AI models and datasets for the project.
  • Start working on the AI model for the chat interface.

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Day 3 - 4: Development & Integration

Frontend Development:
  • Develop the user interface for the website, ensuring it's intuitive and user friendly.
  • Implement features for offline access (service workers, cached pages).
Backend Development:
  • Create APIs for AI interactions and data retrieval (market insights, weather, pest alerts).
  • Set up the database for produce listings and chat history
AI/ ML & Data Science:
  • Integrate AI models into the backend.
  • Test and refine the chatbot's response accuracy and relevance
Product Design:
  • Refine the design based on user flow and feedback from the team.
  • Ensure the website is responsive and accessible on various devices.

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Day 5: Testing, Refinement, & Presentation

All Team Members:
  • Conduct thorough testing across different scenarios and devices.
  • Debug and refine based on test results.
  • Prepare a presentation showcasing the website's features, AI capabilities, and potential impact on the agricultural sector
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