Krishi Raksha seeks to overcome the challenges of plant disease and pest diagnosis with the following objectives:

AI-Powered Diagnostics: Develop an AI-powered application that processes images of plants to diagnose diseases and pests effectively.

Real-Time Results: Provide real-time diagnostic results with actionable recommendations to help farmers take immediate measures.

Accessibility: Ensure the tool is highly accessible even to farmers with minimal technological literacy.

Sustainability: Promote sustainable agriculture by enabling precise, data-driven decision-making.

User-Friendliness: Incorporate features such as voice assistants and intuitive navigation to enhance usability for end users.

Scope of the Project: Krishi Raksha is designed as an integrated digital solution for plant health management, with the following core functionalities:

AI-Powered Diagnostics: Utilize Gemini AI to perform real-time image analysis and provide immediate feedback on plant health.

Actionable Recommendations: Offer practical and actionable recommendations for every detection.

Scalability: Build a system capable of supporting various crops and farming practices, with future potential for IoT integration.

User Accessibility: Enhance accessibility for users with poor literacy or low technical skills through voice guidance and a user-friendly interface.

The core of Krishi Raksha is AI; as such, Gemini AI has been used as the main engine for disease and pest diagnosis. To maximize efficiency and reduce implementation simplicity, the app bypasses traditional odel training and preprocessing.

Direct AI Integration

 API-Based Analysis: Gemini AI has been integrated through an API that offers on-the-spot processing of user-uploaded images. This eliminates the need for custom model training by developers and pre-processing of datasets.

 Plug-and-Play Implementation: With pre-trained models, the system is ready to analyze raw user inputs without additional overhead for augmenting or cleaning the data.

 Standardized Outputs: Gemini AI ensures uniformity in output formats, hence simplifying how diagnostic information is presented to the user.

PSEUDO CODE:

START

//Initialize application

FUNCTION initializeApp() SET up user interface SET up event listeners for buttons END FUNCTION

// Function to handle file selection FUNCTION onChooseFile() DISPLAY file chooser dialog IF file is selected THEN UPLOAD file DISPLAY file name END IF END FUNCTION

// Function to handle image capture FUNCTION onCaptureImage() OPEN camera interface IF image is captured THEN UPLOAD captured image DISPLAY image preview END IF END FUNCTION

// Function to analyze uploaded image FUNCTION analyzeImage(image) SEND image to server for analysis RECEIVE analysis results DISPLAY results to user END FUNCTION

// Function to handle back to homepage action FUNCTION onBackToHome() NAVIGATE to homepage END FUNCTION

// Main application flow FUNCTION main() CALL initializeApp() WHILE application is running DO WAIT for user interaction IF user chooses file THEN CALL onChooseFile() ELSE IF user captures image THEN CALL onCaptureImage() ELSE IF user clicks back button THEN CALL onBackToHome() END IF END WHILE END FUNCTION

// Start the application CALL main() END

CONCLUSION: Krishi Raksha represents one of the first steps taken to update agriculture by using AI-powered diagnostics for disease and pests. Its development demonstrated the potential of leveraging pre- trained AI models like Gemini AI in empowering farmers with real-time, actionable insights. Though challenges remain, such as connectivity issues, data privacy, and user adoption, the foundational success of the app let it shine in its transformative potential.