Developer/Data Sources

Aggregated Data Sources

Argus AI unifies fragmented traffic data from multiple sources into a single, normalized API. No more managing separate integrations or reconciling conflicting data.

Why Multi-Source Aggregation Matters

No single traffic data source provides complete coverage. Each has blind spots, latency limitations, and coverage gaps. By aggregating multiple sources, Argus AI delivers more accurate, timely, and comprehensive traffic intelligence.

3-5%

of vehicles are "connected" with telematics, leaving 95%+ of traffic invisible

30-60s

typical delay from traditional sources—too slow for real-time routing

<10s

Argus AI detection latency through AI video inference and multi-source fusion

Our Data Sources

Each source contributes unique intelligence. Together, they create comprehensive traffic awareness that no single provider can match.

911/PSAP Dispatch

Direct integration with emergency dispatch centers for verified incident alerts.

Coverage:Low
Latency:< 30 seconds
Data Types:
AccidentsRoad hazardsWeather eventsEmergency closures
Unique Value:

Authoritative, human-verified incidents with emergency response context.

Telematics Providers

Aggregated vehicle telemetry data from fleet and consumer devices.

Coverage:Growing
Latency:< 15 seconds
Data Types:
Speed anomaliesHard braking eventsTraffic flowRoute patterns
Unique Value:

Real-world vehicle behavior data across diverse road networks.

Public Roadway Sensors

Loop detectors, radar sensors, and infrastructure monitoring systems.

Coverage:Expanding
Latency:< 60 seconds
Data Types:
Traffic volumeSpeed measurementsOccupancy dataQueue detection
Unique Value:

Fixed-location, continuous monitoring with high accuracy.

Traffic Camera AI Inference

Computer vision analysis of DOT traffic cameras and private feeds.

Coverage:Nationwide
Latency:< 10 seconds
Data Types:
Visual incident detectionLane blockageVehicle classificationCongestion levels
Unique Value:

Real-time visual context that telematics cannot provide.

Dashcam Video Inference

AI-powered analysis of commercial fleet and consumer dashcam footage.

Coverage:Growing
Latency:< 10 seconds
Data Types:
Road hazardsNear-miss eventsInfrastructure damageWeather conditions
Unique Value:

Ground-level, driver-perspective intelligence at scale.

Public Data Feeds

DOT feeds, construction notices, event schedules, and weather services.

Coverage:Comprehensive
Latency:Variable
Data Types:
Planned closuresConstruction zonesSpecial eventsWeather alerts
Unique Value:

Contextual data for predictive routing and planning.

How We Aggregate

1

Ingest

Real-time streams from all data sources flow into our processing pipeline

2

Normalize

Data is standardized into a unified schema regardless of source format

3

Deduplicate

Multi-source events are correlated and merged to prevent duplicates

4

Deliver

Clean, enriched data available via REST API or real-time WebSocket

Why Connected Vehicles Alone Aren't Enough

Limited market penetration: Only 3-5% of vehicles on the road today have connected telematics, leaving massive blind spots in coverage.

No visual context: Telematics only provides speed and location. It can't distinguish between a traffic jam and a major accident, or identify debris in the road.

Siloed data: Major telematics providers don't share data with each other, fragmenting the already limited connected vehicle intelligence.

Argus AI solution: We combine telematics with 911 dispatch, video inference, and sensor data to fill the gaps that connected vehicles leave behind.

Data Source FAQ

Where does Argus AI get its traffic data?

Argus AI aggregates traffic data from six primary sources: 911/PSAP emergency dispatch, telematics providers (fleet and consumer), public roadway sensors (loops, radar), traffic camera video inference, dashcam AI analysis, and public data feeds (DOT, weather, events). This multi-source approach provides more comprehensive coverage than any single data provider.

How does video inference improve traffic data?

Video inference adds visual context that telematics cannot provide. Our AI can identify the type of incident (accident, debris, weather), estimate severity, count lanes blocked, and detect situations like stopped vehicles or pedestrians. This context enables more accurate routing decisions and ETA predictions.

What is the latency for each data source?

Video inference (traffic cameras, dashcams): under 10 seconds. Telematics: under 15 seconds. 911/PSAP dispatch: under 30 seconds. Roadway sensors: under 60 seconds. Our fusion pipeline delivers the fastest available detection regardless of source, typically achieving sub-10-second alerts for critical incidents.

How do you handle conflicting data from multiple sources?

Our pipeline includes intelligent deduplication and correlation algorithms. When multiple sources report the same incident, we merge the data, taking the earliest detection time and richest metadata. Each incident includes source attribution so you can see which sources confirmed it.

Access Unified Traffic Intelligence

Stop managing multiple integrations. Get all traffic data through a single API.