Farmers Disease Diagnostic/Reporting Portal - Mobile Portal Al Based
Abstract : Background- Agricultural productivity and food security are heavily dependent on the health of crops and livestock. Farmers, especially in remote or resource-limited areas, often face challenges in diagnosing and reporting diseases that affect their livestock and crops.
Early diagnosis and timely reporting are crucial for effective disease management and prevention of widespread outbreaks. Description - A mobile portal powered by Artificial lntelligence (Al) for disease diagnosis and reporting can revolutionize how farmers manage animal and plant health.
This portal enables farmers to use their smartphones to access diagnostic tools, report symptoms, and receive actionable advice. Al algorithms can analyze reported data to provide accurate diagnoses and suggest appropriate treatments or interventions.
This technology can empower farmers with the knowledge and tools to manage diseases more effectively, ensuring the health and productivity of their farms.
lntegrate Al-based software with existing NDLM to allow farmers to submit images and descriptions of disease signs and symptoms. The Al will generate suspected disease/condition reports with preventive measures and send alerts to veterinarians for appropriate action (Al-based software, Mobile application).
Expected Outcomes . Enhanced Disease Diagnosis: . Timely Reporting and lntervention: . lncreased Access to Expert Knowledge: . lmproved Farm Productivity.
Data Collection and Analysis: Cost-Effective DiseaseManagement: Empowerment and Education of Farmers: lntegration with Existing Surveillance Systems . Community Engagement and Support: Sustainable Agriculture Practices
In previous work, The user application takes a picture of a leaf with the phone's camera. The trained model included in the "Plant Buddy" app is then used to process the taken image.
Based on the precision of the image, the programme then decides if the plant is healthy or unhealthy.
The suggested model performs 10–20% worse when photographs are taken outside.
An image dataset that was taken in a real-world environment can be used to get around this restriction.
Limited Internet Access: Many rural areas where farmers operate may have poor or unreliable internet connectivity. This can limit the effectiveness and accessibility of a mobile AI-based portal.
Data Privacy Concerns: Collecting and storing sensitive information about farm conditions and potentially proprietary farming practices can raise privacy and security issues. Ensuring data protection and compliance with relevant regulations is critical.
Technology Adoption Barriers: Some farmers may be hesitant or lack the technical skills to use mobile applications or AI-based tools. This can be due to a lack of familiarity with technology or resistance to change from traditional methods.
AI Accuracy and Reliability: AI systems depend on the quality and quantity of data used for training. If the AI model is not well-trained or if it encounters unfamiliar conditions, its diagnostic accuracy may suffer, potentially leading to incorrect recommendations.
This innovative platform integrates a user-friendly mobile interface with a robust backend infrastructure to deliver rapid and accurate disease diagnostics directly to farmers. Users can easily report symptoms or upload images of affected crops and livestock, which are then analyzed by advanced AI algorithms to provide near-instantaneous diagnostic results.
The system also offers personalized treatment recommendations and best practices based on the diagnosed conditions.
The portal features a real-time reporting mechanism that enables farmers to track and report new issues, while a data management system consolidates historical reports and trends for in-depth analysis.
Integration with external data sources, such as local weather and market information, enriches the diagnostic and treatment recommendations, making them more contextually relevant.
To ensure data security and user privacy, the platform employs robust encryption and complies with data protection regulations.
Rapid Diagnosis: AI-powered tools can quickly analyze data from images, symptoms, or environmental conditions to provide near-instant diagnostics, helping farmers address issues before they become severe.
Accessibility: Mobile portals make it easier for farmers in remote or rural areas to access diagnostic tools and information without needing to travel to specialized centers.
Early Detection: AI systems can identify patterns and early signs of disease that might be missed by the human eye, enabling earlier intervention and potentially reducing crop or livestock losses.
Personalized Recommendations: AI can offer tailored advice based on the specific conditions of a farm, such as local climate, soil type, and crop variety, leading to more effective disease management strategies.
Cost Efficiency: By reducing the need for on-site expert consultations and enabling self-diagnosis, AI-driven mobile portals can lower costs for farmers and agricultural businesses.
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