CityFlow is a data-driven Decision Support System (DSS) designed to help municipal authorities identify traffic congestion hotspots, understand their root causes, and recommend practical interventions for improving urban mobility.
Unlike traditional traffic dashboards that only visualize data, CityFlow focuses on supporting better decision-making through structured analytics and explainable recommendations.
The initial prototype is validated using data from four Indian cities:
- Solapur
- Kolhapur
- Nashik
- Pune
The long-term vision is to build a scalable framework that can be applied to any city with standardized road network data.
- Identify urban traffic congestion hotspots.
- Analyze the factors contributing to congestion.
- Generate data-driven recommendations for city authorities.
- Validate the methodology across multiple cities.
- Build a reusable decision-support framework for urban mobility planning.
- Road network analysis
- Hotspot detection
- Root cause analysis
- Recommendation engine
- Interactive Power BI dashboard
- Python
- PostgreSQL
- Power BI
- Git & GitHub
Current Stage: Discovery & Planning
The project is currently focused on designing the overall solution architecture, data strategy, and analytics framework before implementing the first working prototype.
The repository is organized into dedicated folders for documentation, datasets, database scripts, source code, dashboards, outputs, and presentations to support a structured development workflow.
- Phase 1 – Discovery & Planning
- Phase 2 – Solution Design
- Phase 3 – Data Strategy
- Phase 4 – Data Collection
- Phase 5 – Analytics Engine
- Phase 6 – Dashboard & Decision Support
- Phase 7 – Validation
- Phase 8 – Documentation
- Phase 9 – Future Enhancements
CityFlow aims to transform urban traffic management from reactive decision-making to proactive, data-driven planning through analytics, explainable insights, and decision support.