Enhancing Crop Prediction and Resource Management

Welcome to the Enhancing Crop Prediction and Resource Management project repository!

Overview

This project aims to improve crop prediction and resource management for rice, wheat, and corn cultivation by integrating a KNN-based approach with IoT-driven smart irrigation technology. By leveraging data analytics and machine learning, our solution optimizes water usage, enhances crop productivity, and promotes sustainability in agriculture.

Key Features

• KNN-Based Crop Prediction: Predicts crop yield based on historical data and environmental factors.
• IoT-Driven Smart Irrigation: Monitors soil moisture levels and dynamically adjusts irrigation schedules.
• Data Analytics: Analyzes agricultural data to optimize resource allocation and decision-making.
• Crop-Specific Recommendations: Provides tailored recommendations for rice, wheat, and corn cultivation.

ICCICCT-2024 Acceptance

This project has been accepted and presented at the 2nd International Conference on Challenges in Information, Communication, and Computing Technology (ICCICCT-2024).

Repository Structure

• /code: Contains the source code for the project.
• /documentation: Includes project documentation, installation guides, and usage instructions.
• /demo_photos: Provides visual representations and demo photos of the project in action.

Getting Started

1. Clone the repository: git clone https://github.com/your-username/enhancing-crop-prediction.git
2. Explore the /documentation folder for detailed instructions on setting up and running the project.
3. Check out the /code directory to view the implementation of the KNN-based approach and IoT-driven smart irrigation system.

Contributors

• M SAKTHI SHARAN (https://github.com/Sakthi-S29)
• SHIVANI (https://github.com/Shivani01Durai)

Feedback and Contributions

We welcome feedback, suggestions, and contributions from the community! Please feel free to open an issue or submit a pull request with your ideas.

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