AgriSURE-Greenathon-2024

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Agriculture Prediction Platform

Overview

This platform leverages Ai/ml and various technologies to help farmers manage their crops effectively. It gathers data about crop location, type, planting date, soil, water resources, irrigation systems, land area, and market prices to predict crop value and income. It also forecasts the impact of unexpected weather events and provides prevention techniques.

Features

• Crop Information Input: Users can enter crop location, name, variety, planting date, soil type, water resources, irrigation system, and land area.
• Market Price Integration: Current and forecasted market prices are used to predict crop value and income.
• Weather Impact Analysis: The platform assesses the impact of unexpected events such as rain, storms, heatwaves, and cyclones on crops.
• Visualization: Data is presented using plots (e.g., with PyPlot) to help users understand potential impacts and trends.
• Alerts and Prevention: Farmers are notified of upcoming dangers and given advice on how to protect their crops based on current and forecasted weather.

Technologies Used

• Flask: For creating the web application.
• ChatGPT: For handling user inputs and generating recommendations.
• APIs: For weather forecasts and market prices.
• PyPlot/Other Plotting Libraries: For data visualization.

Setup

Prerequisites

• Python 3.8+
• Flask
• Requests
• Pandas
• Matplotlib (or other plotting libraries)
• API keys for weather and market data

Installation

1. Clone the Repository

   git clone <repository-url>
   cd <repository-directory>

2. Install Dependencies

   Create a virtual environment and install the necessary packages:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   pip install -r requirements.txt

3. Set Up Environment Variables

   Create a .env file in the root directory and add your API keys and other sensitive information:

   WEATHER_API_KEY=<your-weather-api-key>
   MARKET_API_KEY=<your-market-api-key>

4. Run the Application

   flask run

   The application will be available at http://127.0.0.1:5000.

Working Diagrams & Working Prototype Picture of Platform

Architecture Diagram

Flow Diagram

WireFrame Diagram

Prototype Screenshots

API Integration

Weather API

• Base URL: https://api.weatherapi.com/v1/
• Endpoint: forecast.json
• Parameters: key, q (location), days (number of days to forecast)

Market Data API

• Base URL: https://api.marketdata.com/v1/
• Endpoint: prices
• Parameters: apikey, commodity, location

Visualization

Use libraries such as Matplotlib to create plots. Example:

import matplotlib.pyplot as plt

def plot_data(x, y):
    plt.plot(x, y)
    plt.xlabel('Time')
    plt.ylabel('Price')
    plt.title('Market Price Over Time')
    plt.show()

Alerts and Recommendations

Implement logic to analyze weather forecasts and market data to provide actionable insights and alerts. Use ChatGPT to generate recommendations based on this data.

Contributing

Feel free to fork the repository and submit pull requests. For any issues or feature requests, please open an issue on GitHub.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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Feel free to adjust and expand this based on your specific needs and the features you implement!