Edge AI Station α AI Application

Turn vehicle traffic data into actionable insights for operations and optimization.

Traffic Monitoring · Gate Management · Traffic Flow
Analysis · Wrong-Way Driving Detection

EDGEMATRIX Smart Traffic is an AI-powered application that automatically detects vehicles crossing virtual counting lines configured within camera footage. The system classifies vehicles by type and counts traffic by direction (IN / OUT), providing accurate and real-time traffic data.

Ideal for factory and logistics facility gate management, roadway traffic surveys, and parking lot safety monitoring, Smart Traffic enables organizations to quantitatively measure vehicle movement, improve operational efficiency, enhance visibility, and support data-driven traffic analysis.

｜App Features｜

Vehicle Classification

Configure virtual counting lines to automatically count passing vehicles by class, including Cars, Trucks, Buses, Motorcycles, and Bicycles.

Directional Traffic Analysis

Count vehicle movements in both IN and OUT directions. The system can also be configured to identify vehicles traveling against the designated traffic flow, enabling wrong-way driving detection.

External System Integration

Leverage Node-RED to enable notifications, data storage, dashboard visualization, and integration with existing business systems.

｜App Intro Video｜

Applied to Smart Traffic.(※Under development image.)

｜Usage Scenes｜

Gate passage management for factories and facilities

Cameras are installed at the entrances and exits of factories and facilities to automatically count vehicles passing through lines. This can be used to keep track of the number of trucks entering and leaving the facility and to analyze logistics volume by time period, eliminating the need for manual recording and human verification. By identifying and recording the IN/OUT direction, it also supports the visualization of traffic history.

Construction

Logistics Center

Parking Lot

Traffic volume survey and traffic flow analysis

Using camera footage installed at designated locations, vehicles passing through are automatically counted by vehicle type and the direction. This enables the collection of quantitative traffic volume data without manual labor, and can be used as basic data for understanding traffic congestion trends, analyzing traffic flow by time of day, and formulating road maintenance plans and urban transportation policies. Compared to conventional manual surveys and simple sensors, installation work is reduced and installation locations can be selected flexibly.

Intersections

Roads

Highways

School Zones

Detection of vehicles driving in the wrong direction
on highways and parking lots

By applying this technology, setting up two sidings—one for normal traffic and one for reverse-direction vehicles—enables detection of reverse-direction vehicles and allows prompt alert issuance to administrators. This contributes to preventing accidents and driver disputes on roads and in parking lots, while enhancing security.

Roads

Parking lots

*Node-RED is a visual programming development tool for interconnecting hardware devices, APIs, and online services.

| App Overview |

Performs real-time counting and provides the following functions.

Vehicle Counting Across
Virtual Lines

Record IN/OUT Counts
by Vehicle Type and Direction

Configurable Reset Timing
for Cumulative Counts

Visual Monitoring
with Overlay Display

Inference Result Processing and
External Transmission via Node-RED

Using the Node-RED environment included with AI Station, inference results from AI applications can be processed, formatted,
and transmitted to external systems for integration.

Generic Node-RED Flow (Post-Processing) Overview

As AI Station is often deployed in on-premises environments and private networks where internet connectivity is unavailable, web applications for visualization are optional for AI Station-compatible applications (AIP), unlike existing store applications (EAP). However, for customers operating AI Station in environments with internet access, inference results can be transmitted to your website through Node-RED post-processing, enabling the provision of web applications for visualization. The architecture can be easily extended to support email notifications, signal tower integration, external API transmission, and dashboard visualization. By providing a web application for visualization, you can promote your AI application to a broader range of customers, and we encourage consideration of web application development and deployment as part of your solution.

Grafana

*This screen is taken from the analysis screen of Kaleidoscope (a multifunctional people detection app).
We plan to use a general-purpose visualization system that can be built with OSS, consisting of Grafana + InfluxDB.
*We plan to provide a manual on how to build a general-purpose visualization system and a general-purpose Node-RED flow for sending visualization data to InfluxDB.
*Compliant with Grafana dashboard functionality.
*The number of vehicles by vehicle type and entry direction can be visualized in real time using graphs, tables, etc. The raw data used for visualization can also be downloaded in CSV format.

｜Function Details｜

Detection Methods

　　　　

It has an automatic counting function for the number of vehicles passing through the line. It automatically counts the number of times an object crosses the line set by the user within the camera image. It's possible to identify the direction of entry (IN) and exit (OUT) and count them separately. By configuring settings for correct (forward) and wrong (reverse) directions, the system can detect vehicles traveling in the wrong direction and immediately notify administrators. Classification and aggregation by vehicle type (target class) is possible. Any combination of the following five classes can be set: “Car,” “Truck,” “Bus,” “Motorbike,” and “Bicycle.” The number of vehicles crossing each class is counted and overlaid in real time on the video. Overlay display function. Real-time cumulative passage counts for each target class, bounding boxes (detection target frames), line positions, and passage directions are overlaid on the video. Operators and facility managers can immediately grasp the on-site situation.

Contact Us ▶

App Provider Company

Company Name:EDGEMATRIX Inc.

About Us:We contribute to society through the development of “Video Edge AI” infrastructure technology. Our mission is to implement “Video Edge AI” in society.

URL:https://edgematrix.com/en

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