CommuteIQ – Autonomous Bengaluru Commute Intelligence Agent CommuteIQ is a multi‑agent AI system that recommends the best travel mode (Metro, Cab, BMTC bus, Auto) for any route in Bengaluru. It combines real‑time traffic, weather, safety alerts, events, and parking data into an intelligent reasoning engine.
🎯 What It Does Takes a route and departure time as input.
Runs six specialized AI agents in sequence:
Traffic Intelligence – analyses congestion hotspots and delays. Weather Intelligence – evaluates rain, visibility, and mode‑specific impacts. Transport Optimization – scores each mode on time, cost, reliability, safety, weather fit, eco‑friendliness, and comfort (weighted composite score). Safety Evaluation – flags road blocks, maintenance, school traffic, flood risks. Route Analysis – calculates event delays, parking occupancy. Final Decision – synthesises all evidence, builds a reasoning chain, and recommends the optimal mode. Outputs a rich Streamlit dashboard with hero card, reasoning chain, mode comparison, weather/traffic/safety panels, alternatives, events, and parking info.
🏗️ Technical Stack Python 3.8+
Streamlit – interactive UI
Elasticsearch – optional historical data store (traffic snapshots, alerts, recommendations)
Mock data (Bengaluru routes, hotspots, schedules) – works out‑of‑the‑box in demo mode
✨ Key Features Autonomous reasoning – no human input beyond route and time.
Modular agents – each agent can be improved independently.
Demo‑ready – runs immediately without API keys or Elasticsearch.
Production‑ready – can plug into real TomTom/OpenWeather APIs, AWS deployment, and Elasticsearch for historical learning.
Confidence scoring – each recommendation includes an AI confidence percentage based on data quality and risk levels.
📊 Sample Capabilities Supports 6 major Bengaluru routes (Whitefield → MG Road, Electronic City → Koramangala, etc.).
Scores Metro, Cab, BMTC, Auto on 7 dimensions.
Considers peak hours, rain probability, surge pricing, metro frequency, parking fullness, school dismissal events, and road maintenance.
Displays a human‑readable reasoning chain (e.g., "🚦 Congestion on ORR: HIGH – 53 min road delay").
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