India’s air pollution crisis is underserved in rural and Tier-2/3 cities, where most AQI tools provide little visibility or guidance.
VayuLens proposes an AI-powered advisory agent that collects data from ground stations, satellites, and weather APIs.
Forecasting models (24–72 hrs) and Granite LLMs generate personalized health alerts, tips, and visualizations.
An animated “Air Twin” avatar makes exposure and health risks engaging and relatable for users.
IBM’s Agent Development Kit will orchestrate the workflow from data ingestion → prediction → reasoning → alerts.
Tech stack includes Flutter (mobile app), Node.js/Firebase (backend), and Mapbox (pollution maps).
Anticipated challenges: heterogeneous data integration, forecast reliability, real-time orchestration, and user experience design.
Expected outcome: a scalable agentic AI pipeline that turns complex environmental data into simple, actionable insights.
Future roadmap: pilot in smaller cities, expand with Watsonx.ai, enable community reporting, and evolve into a policy-level advisory tool.
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