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Poll-Rover 🗳️

Democracy starts with knowing where to go.

Poll-Rover is an AI-powered civic tech platform designed for the 2026 Indian Elections. It empowers every voter by providing a high-trust, accessible, and intuitive interface to discover their assigned polling stations, evaluate accessibility features, and navigate directly to the ballot box.

Poll-Rover Scale & Deploy Live Site Weekly Performance


📊 Agent Performance Dashboard (Weekly KPIs)

The Poll-Rover ecosystem is monitored via a suite of Key Performance Indicators (KPIs) to ensure the highest reliability for voters.

Agent Reliability (Success Rate) Efficiency (Latency) Quality Score
🛰️ Harvester Success Latency Accuracy
🛡️ Quality Validation Time Precision
🏗️ Orchestrator Build Rate Uptime
🧑‍🤝‍🧑 Assist Response TTI Satisfaction
🩺 SRE Ops Remediation MTTR Health

Note

Metrics are aggregated every Sunday at 23:59 UTC and published to the Weekly Performance Report.


🧠 The Intelligence Mesh (Autonomous Agent Framework)

Poll-Rover operates on a sophisticated 5-agent autonomous pipeline to ensure data reliability and voter support:

  1. 🛰️ Harvester Agent: Daily autonomous extraction of polling station data from ECI and State CEO portals (TN, KL, PY, AS, WB).
  2. 🛡️ Quality Agent: Runs post-harvest verification, cross-referencing coordinates with OpenStreetMap for 100% locational accuracy.
  3. 🏥 SRE Ops Agent: Automated health audits of the entire data mesh, ensuring zero stale entries and platform stability.
  4. 🧑‍🤝‍🧑 Citizen Assist AI: A multilingual (English, Tamil, Malayalam) support agent powered by localized LLMs (Ollama/Gemini) to answer voter queries instantly.
  5. 🏗️ Orchestrator: Manages the YAML → Python → Zola build pipeline, converting raw civic data into a high-performance static visualizer.

✨ Gold Standard Features

🔍 Global Station Search

Integrated header search bar for instant discovery. Type a Station ID, Name, or Landmark to fly directly to the booth location on the interactive map.

🧭 One-Click Routing

Found your station? Click "Get Directions" in the popup to launch turn-by-turn navigation via Google Maps deep-links.

♿ Accessibility-First Design

Every station is evaluated and color-coded based on its accessibility rating:

  • Green (High): Fully accessible with ramps, audio booths, and braille.
  • Yellow (Moderate): Partial accessibility features present.
  • Red (Limited): Basic facilities only.

🌓 Royal Civic Indigo UI

A premium, institutional design system optimized for high-contrast legibility. Features a sleek Dark/Light theme toggle with persistence and cache-busting for a seamless experience.

⚡ Lazy-Loading Architecture (New)

Poll-Rover now uses a next-gen discovery engine that reduces the initial map payload from 27MB to 3KB (99.9% reduction). Data is partitioned into district-level chunks and fetched on-demand based on proximity and user interaction.


📖 User Guide

  1. Discover: Open the Live Map and explore your region.
  2. Filter: Use the Accessibility Filters (♿, 🔊, ⠿) to find stations meeting your specific needs.
  3. Search: Use the global search bar to jump to your booth.
  4. Navigate: Click a marker and select "Get Directions" to find your route.
  5. Assist: Click the Citizen Assist icon to ask the AI about voting dates, procedures, or station details.

🛠️ Technology Stack

  • Core: HTML5, Vanilla CSS (Royal Civic Indigo), JavaScript
  • Static Site Engine: Zola (High-performance SSG)
  • Map Engine: Leaflet.js with Custom Data Layers
  • Automation: GitHub Actions (Daily Deployment Pipeline)
  • Data Engineering: Python 3.11 with YAML/GeoJSON processing
  • AI Models: Llama 3.2 (via Ollama) & Gemini 2.0 Flash

🚀 Deployment & Scaling

Poll-Rover is configured for Daily Automated Deployments. The deploy.yml workflow:

  1. Harvests regional data.
  2. Audits data health.
  3. Builds the static site.
  4. Pushes live to GitHub Pages.

Democracy is a journey—Poll-Rover is your map. 🏛️🗳️✨

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AI-powered civic tech for the 2026 Indian Elections. Discover polling stations, accessibility features, and routing via an autonomous 5-agent pipeline.

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