Platform Impact
Measurable results from our AI-powered traffic management system.
How It Works
From raw camera feeds to intelligent decisions — an 8-step AI pipeline that transforms traffic data into city-wide optimization.
Traffic Cameras
Real-time video feeds from traffic cameras capture raw traffic data across the entire city network. Every vehicle, pedestrian, and movement is recorded for AI analysis.
Vehicle Detection
YOLO-based computer vision detects and classifies vehicles in real-time — cars, bikes, buses, trucks, and emergency vehicles. Each vehicle is identified with 98.5% accuracy.
Vehicle Tracking
DeepSORT tracking algorithm assigns unique IDs to each vehicle, tracking movement paths, speed, direction, and lane changes across multiple camera views.
Traffic Analytics
Real-time analytics engine processes detection data to compute vehicle counts, average speed, lane occupancy, density maps, and traffic flow metrics every second.
Congestion Prediction
LSTM and XGBoost AI models analyze historical patterns and real-time data to predict congestion levels 15, 30, and 60 minutes ahead with confidence scoring.
Optimization Engine
AI-driven optimization recommends adaptive signal timing, dynamic routing, lane management, and traffic flow adjustments to minimize congestion city-wide.
Digital Twin
A real-time 3D digital twin of the city visualizes every vehicle, traffic light, and congestion zone. The virtual city mirrors the physical world with sub-second latency.
Decision Support
Actionable intelligence delivered through the command center dashboard and AI Copilot. Operators receive clear recommendations with explainable AI reasoning.
Platform Features
Nine integrated modules that work together to create a comprehensive traffic intelligence platform.
Vehicle Detection
YOLOv8-based real-time vehicle detection from traffic camera feeds. Detects and classifies cars, bikes, buses, trucks, and emergency vehicles with 98.5% accuracy. Generates vehicle counts, speed estimates, and density analysis for every frame.
Traffic Prediction
Multi-time horizon congestion prediction using LSTM and XGBoost ensembles. Predicts traffic conditions 15, 30, and 60 minutes ahead with confidence scoring. Factors in historical patterns, weather data, events, and real-time sensor inputs.
Emergency Corridor
Intelligent emergency vehicle routing with automatic traffic signal preemption. Detects ambulances in traffic, generates fastest green wave corridors, and provides estimated time saved. Reduce emergency response times by up to 40%.
Accident Detection
AI-powered automatic accident detection from traffic camera feeds. Identifies road blockages, sudden stops, possible collisions, and anomalous events. Assesses severity, impact zone, and generates recovery estimates with diversion suggestions.
AI Copilot
Natural language traffic management assistant. Ask questions about congestion, get prediction explanations, request optimization strategies, and receive real-time traffic insights. Every response includes explainable AI reasoning with confidence metrics.
Smart Dashboard
Enterprise-grade traffic command center with real-time KPIs, interactive charts, heatmaps, and live 3D city view. Monitor total vehicles, congestion index, average speed, active incidents, and emergency alerts at a glance.
3D Digital Twin
Real-time 3D city simulation powered by Three.js and React Three Fiber. Animated vehicles, dynamic traffic lights, building models, and congestion heatmap overlays. Interactive orbital controls for full city exploration.
Heatmaps
Real-time congestion heatmaps overlay on the 3D city view. Color-coded zones from green (free flow) through yellow and orange to red (critical congestion). Identify bottleneck areas instantly across the entire city network.
Forecasting Engine
Advanced time-series forecasting engine using ensemble ML models. Analyzes historical traffic patterns, current conditions, and external factors to predict future congestion. Provides actionable recommendations with explainable AI.