- AI Vision Pro - Image recognition and analysis platform
- Generative AI - Google Vision Pro model (Gemini- Vision pro)
- SQL database
- AI and Machine Learning: Utilizes advanced artificial intelligence algorithms, including fine-tuned text-davinci-003 model for natural language processing and generative AI techniques.
- Image Processing: Sophisticated image processing algorithms capable of adapting to various environmental conditions.
- User Interface: Gradio Interface for intuitive user interactions.
- Database Interaction: Natural Language Processing (NLP) for generating SQL queries from natural language inputs.
An AI-powered plant disease detection mobile app that allows farmers to take pictures of their crops and receive instant diagnoses of any visible diseases. The app leverages computer vision algorithms to detect, classify, and analyze diseases from images. It also includes an offline mode to ensure accessibility in remote areas with limited connectivity.
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Challenge: Varying environmental conditions impact image quality and disease visibility, reducing detection accuracy. Solution: Robust image processing algorithms adapt to different lighting, enhance image clarity, and improve accuracy across diverse agricultural environments.
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Challenge: Remote farm locations may have limited internet connectivity, preventing real-time disease analysis. Solution: Offline mode allows images to be captured, stored locally, and synced with cloud servers when connection is restored - ensuring anywhere accessibility.
- Farmer opens app and selects the crop type they want to scan
- Farmer uses phone camera to capture images of plant(s) with potential issues
- App uploads images and leverages AI Vision Pro for instant disease recognition
- Analysis results are displayed to farmer with disease name, severity, and recommended treatments
- App offers option to sync images and results with cloud when internet connectivity is available
The app delivers value by enabling real-time, AI-powered crop disease detection, allowing farmers to diagnose and treat issues early for healthier plants and higher yield. Offline functionality expands access to remote agricultural areas. Overall, the project aims to revolutionize precision agriculture through cutting-edge AI technology.