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.
Disease Detection:
Image Upload: 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.
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.
Recommendations:
Treatment Suggestions: Provide recommendations for treatment or management based on detected diseases, including chemical treatments, organic solutions, or preventive measures.
Prevention Tips: Offer tips and best practices for preventing common plant diseases.
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.
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.
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.
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.
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
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.
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.
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.
Usability:
User Interface: Design an intuitive and user-friendly interface for easy image upload, disease detection, and report viewing.
Accessibility: Ensure the system is accessible to users with disabilities, following guidelines such as WCAG (Web Content Accessibility Guidelines).
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.
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.
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.
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.
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.
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.
