Functional requirements of Plant Disease Detection System with non-functional

Functional Requirements

1. User Management:
   • Registration & Authentication: Allow users (farmers, agronomists, researchers) to create accounts, log in, and recover passwords. Support multi-factor authentication for enhanced security.
   • Profile Management: Enable users to manage their profiles, including contact information, preferences, and roles.
2. Disease Detection:
   • Image Upload:
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     Allow users to upload images of plant leaves or other plant parts for disease analysis.
   • Disease Identification: Utilize machine learning or image recognition algorithms to analyze uploaded images and identify potential plant diseases.
   • Symptom Analysis: Provide analysis of symptoms and compare them with known disease patterns in a database.
3. Disease Database:
   • Disease Catalog: Maintain a catalog of plant diseases, including descriptions, symptoms, causes, and treatment options.
   • Image Library: Store and manage a library of disease images for comparison and training purposes.
4. Recommendations:
   • Treatment Suggestions: Provide recommendations for treatment or management based on detected diseases, including chemical treatments, organic solutions, or preventive measures.
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   • Prevention Tips: Offer tips and best practices for preventing common plant diseases.
5. Monitoring and Alerts:
   • Disease Alerts: Notify users about emerging or widespread plant diseases in their area based on detected patterns and external data sources.
   • Seasonal Notifications: Send notifications about seasonal disease risks and preventive measures.
6. Reporting and Analytics:
   • Disease Reports: Generate reports on detected diseases, including frequency, severity, and geographical distribution.
   • Trends Analysis: Provide analytics on disease trends over time and across different regions.
7. User Feedback:
   • Feedback Mechanism: Allow users to provide feedback on the accuracy of disease detection and recommendations.
   • Crowdsourcing: Collect user-contributed data to improve disease detection algorithms and database accuracy.
8. Integration:
   • Weather Data Integration: Integrate with weather data sources to assess how weather conditions may impact plant disease risks.
   • Agricultural Management Systems: Interface with other agricultural management systems for comprehensive farm management.
9. Admin and Moderation:
   • Content Management: Allow administrators to update disease information, manage user accounts, and review system performance.
   • Algorithm Training: Enable administrators to update and train disease detection algorithms with new data.

Non-Functional Requirements

1. Performance:
   • Scalability: Ensure the system can handle increasing numbers of users, image uploads, and disease detections efficiently.
   • Response Time: Maintain quick response times for image processing, disease identification, and recommendation generation.
2. Reliability:
   • High Availability: Achieve high availability with minimal downtime to ensure continuous access to the system.
   • Fault Tolerance: Implement mechanisms to handle system failures and ensure uninterrupted service.
3. Security:
   • Data Encryption: Ensure encryption of sensitive data, including user information and plant disease images, both in transit and at rest.
   • Access Control: Implement robust authentication and authorization mechanisms to protect user accounts and data.
   • Compliance: Adhere to relevant data protection regulations (e.g., GDPR) to ensure privacy and security.
4. Usability:
   • User Interface: Design an intuitive and user-friendly interface for easy image upload, disease detection, and report viewing.
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   • Accessibility: Ensure the system is accessible to users with disabilities, following guidelines such as WCAG (Web Content Accessibility Guidelines).
5. Maintainability:
   • Code Quality: Maintain high code quality and follow best practices to facilitate system updates and maintenance.
   • Documentation: Provide comprehensive documentation for users and developers, including user manuals, API documentation, and system guides.
6. Support:
   • Customer Service: Offer timely and effective support through various channels, such as live chat, email, and phone.
   • Help Center: Maintain a knowledge base or help center with FAQs, guides, and troubleshooting information.
7. Compatibility:
   • Cross-Browser Support: Ensure compatibility with major web browsers (e.g., Chrome, Firefox, Safari).
   • Mobile Responsiveness: Design the system to be fully functional on mobile devices, providing a seamless experience across platforms.
8. Backup and Recovery:
   • Regular Backups: Implement regular backups of data, including user information, disease databases, and image uploads, to prevent loss.
   • Recovery Procedures: Establish procedures for data recovery and system restoration to handle data loss or corruption.
9. Integration:
   • Interoperability: Ensure the system can integrate seamlessly with other agricultural tools, databases, and external services.
   • API Flexibility: Provide flexible APIs to accommodate various integration needs with external systems.
10. Data Quality:
    • Accuracy: Ensure the accuracy and reliability of disease detection algorithms and database information.
    • Timeliness: Provide timely updates to reflect current disease patterns, treatment options, and user feedback.