SkyCrop - Smart Crop Prediction
Overview:
SmartHarvest is a web-based demonstration application designed to provide crop recommendations to farmers. The tool, titled "SmartHarvest - Smart Crop Prediction," aims to help users "Leverage predictive analytics to choose the most profitable crops for your land and season". Users can select a geographical region and a planting month to receive a prediction for the most suitable and profitable crop.
This application is a client-side prototype and uses a mock dataset for its predictions. It serves as a proof-of-concept for a smart farming tool.
Features:
• Recommendation Engine: Predicts the best crop based on user inputs for the planting season (month) and region.
• Region-Specific Data: Includes options for five distinct agricultural zones: Northern Plains, Southern Plateau, Coastal Areas, Himalayan Region, and Desert Region.
Detailed Prediction Results: The output provides comprehensive details for the recommended crop, including:
• A descriptive summary.
• Predicted Profitability (e.g., High, Very High).
• Confidence Level percentage.
• Predicted Yield in Quintals/Acre.
• Predicted Profit in ₹/Acre.
• A list of potential commercial products from the crop (e.g., Flour, Mustard Oil, Textiles).
• Yield Trend Visualization: A dynamic bar chart displays the "Historical & Predicted Yield Trend," showing data for two past years ("Actual") and three future years ("Predicted").
• User-Friendly Interface: A clean, responsive interface with a loading animation to simulate data analysis.
How It Works
• The SmartHarvest application operates entirely on the client-side within the browser.
• Mock Data Source: All crop predictions are sourced from a hardcoded JavaScript object named cropData within the index1.html file. This object contains pre-defined crop recommendations for each region and month combination, along with associated metrics like profitability, yield, and potential products.
• Prediction Simulation: When a user clicks the "Predict Best Crop" button, the application performs a lookup in the cropData object based on the selected inputs. To enhance the user experience and mimic a real analytical process, a 1.5-second delay is intentionally added using setTimeout before displaying the results.
• Technical Stack
The application is built using standard web technologies and relies on CDN-hosted libraries:
• Structure: HTML
Logic: JavaScript
• Getting Started:
No complex setup or local server is required to run this application.
Open the file directly in any modern web browser (e.g., Google Chrome, Firefox, Microsoft Edge).
Our progress over time:-
And our final prototype website can be viewed on: (https://smart-harvest-copy-3f990842.base44.app)
Frontend: User interface (HTML), styling (CSS), and client-side logic (JavaScript).
Backend: This application is currently a client-side prototype and does not have a dedicated backend. A backend developer would be responsible for creating an API, managing a database, and implementing a real prediction model.
Contributors:
• Manan Singhal
• Viransh Jain
• Smit Shubhanshu Kamatnurkar
• Animesh Panda