CropCare

CropCare is a web application designed to provide farmers with essential weather forecast information and irrigation pattern suggestions, aiding in optimized crop management. Developed as the final project submission for GHW-Data, CropCare aims to enhance agricultural practices through data-driven insights.

Features

• Weather Forecast: Displays a comprehensive weather forecast, including temperature, humidity, and precipitation probability.
• Irrigation Pattern Suggestions: Analyzes forecast data to suggest irrigation patterns based on predefined conditions. (Further enhancements needed for crop-specific recommendations)
• Customizable Crop Selection: Users can choose their crop type, though it currently doesn't influence functionality.

Technologies Used

• Frontend: HTML, CSS, JavaScript (with Axios for HTTP requests, and Chart.js for visualization)
• Backend: Node.js (server.js not included in this repository)
• External APIs: OpenWeather API (weather data), BigDataCloud API (reverse geocoding)
• Development Tools: Visual Studio Code, Git

Usage

1. Clone the repository:

   git clone https://github.com/Loskoss/Cropcare.git

2. Navigate to the project directory:

   cd CropCare

3. Start the backend server:

   node backend/server.js

   Ensure Node.js is installed and dependencies are installed via npm or yarn.
4. Open index.html in a web browser.
5. Enter the latitude and longitude of the farm location.
6. Select the crop type from the dropdown menu (not currently utilized).
7. Click on the "Get Location" button to use the current location (optional).
8. Click on the "Submit" button to fetch weather data and irrigation pattern suggestions.
9. View the weather forecast and irrigation pattern displayed.

Future Work

1. Enhanced Crop Selection: Implement crop-specific weather recommendations and irrigation patterns.
2. User Accounts: Enable user registration to save farm locations and preferences.
3. Email Alerts: Provide email notifications for weather forecast changes and irrigation recommendations.
4. Historical Data Analysis: Analyze historical weather data to offer long-term farming insights and trends.
5. Crop Suggestion : suggest crop based on historical data.

Contributing

Contributions, suggestions, feature requests, and bug reports are encouraged. Please open an issue or submit a pull request.