soloshun/sonu-ai

Ghana AI hackathon # Sonu - Crop Disease Detection System **Ghana AI Hackathon 2025 Submission** A comprehensive AI-powered crop disease detection and community outbreak tracking system designed specifically for Ghanaian farmers. Sonu combines computer vision, geospatial analysis, and Progressive Web App (PWA) technology to create a national agricultural "immune system." ## Table of Contents - 🎯 Project Overview - 🏗️ System Architecture - 🚀 Key Features - 🛠️ Technology Stack - 📱 Application Structure - 🤖 AI/ML Implementation - 🗺️ Community Outbreak Mapping - 📲 PWA Implementation - 🚀 Getting Started - 📊 Dataset & Model - 🎨 UI/UX Design - 🔧 Development - 📈 Impact & Innovation ## 🎯 Project Overview Sonu addresses critical challenges in Ghana's agricultural sector by providing: - **Instant Disease Detection**: AI-powered analysis of crop photos with 96% accuracy - **Treatment Recommendations**: Localized treatment plans with organic and chemical options - **Community Intelligence**: Real-time outbreak mapping and early warning system - **Offline Capability**: Full functionality without internet connectivity - **Farmer-Centric Design**: Optimized for low-end smartphones and poor connectivity ### Innovation Highlights - **Beyond Detection**: Complete treatment ecosystem, not just identification - **Community-Powered**: Crowd-sourced outbreak data for preventive action - **Accessibility First**: PWA design for universal smartphone access - **Local Context**: Tailored for Ghana's agricultural ecosystem and farmer needs ## 🏗️ System Architecture ```mermaid graph TB subgraph "Frontend Layer" PWA[Progressive Web App] UI[React Components] SW[Service Worker] end subgraph "AI Processing Layer" ONNX[ONNX Runtime Web] MODEL[EfficientNet Model] PROC[Image Preprocessing] end subgraph "Data Layer" DISEASES[Disease Database] TREATMENTS[Treatment Database] OUTBREAKS[Outbreak Data] end subgraph "Geospatial Layer" MAP[Leaflet Maps] GPS[Location Services] CLUSTER[Disease Clustering] end subgra …