The AI-Driven IoT Fertilizer Advisor is an innovative solution designed to advance precision agriculture by delivering real-time, data-driven fertilizer recommendations to optimize farmland productivity. This project integrates IoT sensor technology with a rule-based AI system to provide actionable insights for farmers, bridging real-time land conditions with expert agronomic knowledge.
- Real-Time NPK Analysis: Employs IoT-based sensors to monitor Nitrogen (N), Phosphorus (P), and Potassium (K) levels in farmland soil, ensuring accurate and timely data.
- AI-Driven Fertilizer Recommendations: Utilizes a rule-based AI system to analyze sensor data and recommend optimal fertilizer usage tailored to specific land conditions.
- Multilingual Web Application: Provides a user-friendly, multilingual interface, enabling farmers worldwide to interact seamlessly with the system.
- Knowledge-Bridging System: Connects farmers with expert agronomic advice by integrating real-time data with verified rule sets, supporting informed decision-making.
- Data Validation: Ensures reliability by validating AI-generated recommendations against verified agricultural datasets, maintaining high accuracy.
- Precision Agriculture: Enhances farmland optimization by enabling data-driven decisions, reducing waste, and improving crop yields sustainably.
The following diagram illustrates the high-level architecture of the AI-Driven IoT Fertilizer Advisor system, showcasing the integration of IoT sensors, AI processing, and the web application.
The circuit diagram below details the wiring and connections for the IoT-based NPK sensor device used in the project.
- Deploy the IoT device in the farmland to collect real-time NPK data.
- Access the web application via a browser to view sensor data and fertilizer recommendations.
- Use the multilingual interface to interact with the system in your preferred language.
- Review AI-generated fertilizer suggestions, validated against expert agricultural datasets.
- Apply the recommended fertilizer quantities to optimize crop growth.
This project is licensed under the MIT License. See the LICENSE file for details.
For questions or feedback, please contact the project maintainers at mugeshkrish007@gmail.com(mailto:mugeshkrish007@gmail.com).