The Challenge
The CityFlow department was drowning in data but starving for insights. They had thousands of traffic cameras, induction loop sensors, and GPS feeds from municipal vehicles, but each system lived in a silo. City planners were making decisions based on months-old PDF reports, and emergency responders lacked a unified view of current traffic conditions.
They needed a “Single Pane of Glass” to visualize the pulse of the city in real-time.
The Solution
Sparkable built a high-performance, WebGL-powered command center dashboard.
Real-Time Data Aggregation
We built an ingestion pipeline that normalized data from 15 different proprietary formats into a unified GeoJSON stream. This allowed us to overlay traffic speed, accidents, and roadwork on a single map.
High-Performance WebGL Visualization
Standard map libraries couldn’t handle the volume of data. We utilized deck.gl to render over 50,000 data points (moving vehicles, sensor statuses) at 60fps in the browser.
Predictive Traffic Modeling
We didn’t just show what was happening; we showed what would happen. By training a model on historical patterns, the dashboard could alert operators to probable congestion hotspots 30 minutes before they formed.
Key Technologies
- Mapbox GL JS & deck.gl: For large-scale geospatial visualization.
- Apache Kafka: For handling the massive stream of sensor events.
- Node.js: For the API layer.
- React: For the complex UI state management.
The Results
The dashboard is now the central tool for the city’s traffic management center.
- 15% Reduction in Commute Times: Through better timing of traffic signals based on live data.
- 30% Faster Emergency Response: Ambulances are routed around congestion automatically.
- Data-Driven Planning: City planners now use the tool to simulate the impact of new construction projects.
“We finally have eyes on the city. This tool has fundamentally changed how we manage urban flow and safety.” — David Rossi, Director of City Transportation