Project

Traffic Vehicle Counter

Upload traffic video, define counting zones, and turn roadside footage into vehicle counts, classifications, and report-ready analytics.

Video UploadsObject DetectionVehicle TrackingCSV Reports
Problem

Manual traffic counting is slow and costly

Traditional traffic studies rely on manual counting or expensive hardware sensors. The results are limited in duration, prone to human error, and difficult to repeat. Cities and engineers need richer, continuous, and more affordable traffic intelligence.

Solution

AI vision turns any camera into a sensor

The Traffic Vehicle Counter uses computer vision to detect, classify, and track vehicles from standard camera footage. It produces validated counts and analytics that integrate directly into transport studies and smart-city dashboards — without specialized roadside hardware.

Workflow

From uploaded video to count report

The first product version should focus on a simple customer journey: submit footage, configure the study, run analysis, and receive usable traffic data.

01

Upload traffic footage

Share recorded roadside, intersection, parking entry, or corridor video from a standard camera.

02

Define count zones

Set virtual lines, directions, time windows, and vehicle classes for the study objective.

03

Run AI analysis

Object detection and tracking convert video movement into structured traffic events.

04

Review results

Inspect counts, classifications, turning movements, and export-ready tables for reporting.

Capabilities

What the system can measure

A single video feed becomes a rich, multi-metric traffic dataset.

VC

Vehicle Counting

Accurate directional vehicle counts across lanes and approaches.

CL

Vehicle Classification

Cars, trucks, buses, motorcycles, and more by vehicle type.

TM

Turning Movement Counts

Per-approach turning movements for intersection analysis.

QL

Queue Length

Lane queue estimation to understand delay and saturation.

CM

Congestion Monitoring

Flow, density, and speed indicators for congestion insight.

PC

Pedestrian & Cyclist Detection

Vulnerable road user detection for safety-focused studies.

Dashboard Direction

Build toward a customer project dashboard

The public page should lead customers into a future member area where every study has its own uploads, analysis jobs, and downloadable results.

Pilot dashboard should include

  • Project-based video uploads and analysis status
  • Vehicle counts by class, direction, lane, and time interval
  • Turning-movement summaries for intersections
  • CSV exports and technical report-ready charts
  • Manual review points for validation and quality control
Technology Stack

Built on modern vision tooling

Computer VisionObject Detection & TrackingEdge AIJetsonPythonDashboardsData Export (CSV / API)
Use Cases

Where it delivers value

  • Traffic impact studies and transport planning
  • Smart city intersection and corridor monitoring
  • Construction-zone and temporary traffic management
  • Before/after evaluation of road interventions
Future Roadmap

From counts to continuous intelligence

  1. Now

    Counting & Classification

    Reliable vehicle counting, classification, and turning movement counts from recorded or live video.

  2. Next

    Real-Time Dashboard

    Live congestion and queue monitoring with a smart-city dashboard and alerting.

  3. Future

    Multi-Camera & Edge

    Multi-camera corridor coverage with on-device edge inference and centralized analytics.

Start with one video and one counting objective.

Share your footage or study goals and we'll help define the first counting zones, analysis outputs, and report format.