delyce250/rwanda-nutrition-connect

# 🌍 Ndi Umuhuza — Rwanda Nutrition Connect **Rwanda Nutrition Connect** is an advanced data-driven web platform designed to enhance Rwanda’s nutrition intelligence ecosystem. It integrates **nutrition analytics**, **GIS mapping**, **machine learning**, and **AI assistance** to deliver actionable insights for public health and policymaking. 🎥 **Demo Video:** ▶️ Watch Project Demonstration --- ## 🧠 Project Description **Ndi Umuhuza — Rwanda Nutrition Connect** bridges data and decision-making in Rwanda’s nutrition sector. It uses **real-time analytics**, **predictive models**, and **AI-powered support** to monitor and improve nutrition outcomes across districts. The platform empowers government agencies, researchers, and NGOs to identify trends, predict malnutrition risks, and design evidence-based interventions. --- ## 🎯 Project Summary This platform combines: - Real-time **NISR** data analytics with interactive dashboards - **AI-powered nutrition predictions** using WHO growth standards - **GIS mapping** for district-level visualization of malnutrition data - A **24/7 AI Chat Assistant** (via **Ready.ai API**) providing personalized nutrition consultations --- ## 🛠️ Technology Stack ### 🔹 Frontend - **Next.js 14** – Modern React framework with static export optimization - **TypeScript** – Type-safe environment for scalable code - **Tailwind CSS** – Responsive and elegant UI design - **React Hooks** – Efficient component logic and state management ### 🔹 Backend & Database - **Supabase (PostgreSQL)** – Real-time database with Row Level Security (RLS) - **Edge Functions** – Serverless ML and analytics processes - **Realtime Subscriptions** – Instant updates for live dashboards ### 🔹 Data Visualization - **ECharts** – Dynamic and interactive charting - **Recharts** – React-based visual components - **Custom GIS Mapping** – District-level map visualizations ### 🔹 Machine Learning (Python) ```python import numpy as np import pandas as pd from sklearn.linear …