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⚡ A full-stack location intelligence platform featuring real-time demand analysis, interactive mapping, and AI-powered feasibility scoring.

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⚡ ChargeLK: Intelligent EV Infrastructure Planner

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ChargeLK is a full-stack Location Intelligence platform designed to optimize the expansion of Sri Lanka's Electric Vehicle (EV) charging network.

Unlike standard map apps that just find chargers, ChargeLK uses a geospatial scoring engine to identify critical infrastructure gaps—analyzing the distance between existing chargers (supply) and high-traffic hotspots (demand) to recommend the perfect spot for the next station.

Key Features

🌍 Interactive Islandwide Map: Visualizes the entire EV network from Jaffna to Matara using high-performance Leaflet maps.

🧠 AI Feasibility Engine: Click any location on the map to instantly generate a Viability Score (0-100) based on proximity algorithms.

📊 Smart Visualization: Dynamic radial gauges and charts visualize demand density vs. competition saturation.

⚡ Premium UI/UX: A modern, glassmorphism-inspired interface with custom SVG markers and smooth animations.

📍 Multi-City Navigation: One-click "Fly To" navigation for major hubs like Colombo, Kandy, and Trincomalee.

🛠️ Tech Stack

Frontend (The Glass Cockpit)

  • React.js (Vite): Lightning-fast UI rendering.

  • Leaflet & React-Leaflet: Advanced mapping and custom marker layers.

  • Tailwind CSS: For the polished, responsive "Glassmorphism" design.

  • Recharts: Data visualization for the score gauges.

  • Lucide React: Beautiful, consistent iconography.

Backend (The Geospatial Brain)

  • Python (Flask): Robust REST API handling analysis requests.

  • Geopy: Performs real-time geodesic distance calculations (Haversine formula).

  • Pandas: Data structuring for station and hotspot management.

📦 Installation & Setup

This project follows a Monorepo structure (Frontend + Backend in one repo).

Prerequisites

  • Node.js (v16+)

  • Python (v3.8+)

  1. Clone & Install

git clone https://github.com/chanuque/ChargeLK cd ChargeLK

  1. Setup Backend (Python)

cd backend pip install -r requirements.txt python app.py // Server starts on http://localhost:5000

  1. Setup Frontend (React)

(Open a new terminal)

cd frontend npm install npm run dev // App opens on http://localhost:5173

🔮 The Logic Behind the Score

The AI Scoring Engine evaluates three key metrics:

  • Demand Proximity: Is the location near a known hotspot (Mall, Hotel, Tourist Site)? (+Score)

  • Competition Distance: Is there already a charger nearby? (-Score for saturation)

  • Grid Gap: Is this a "desert" with no coverage? (+Score for strategic value)

Built by Chanuque

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⚡ A full-stack location intelligence platform featuring real-time demand analysis, interactive mapping, and AI-powered feasibility scoring.

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