한국어 English Tiếng Việt bahasa Indonesia Unisem
한국어 English Tiếng Việt bahasa Indonesia Unisem

UniTraffic Introduction

Intelligent Transportation System, UniTraffic

TRAFFIC MANAGEMENT

UNISEM developed the solution that is based on AI’s Deep Learning method to help in solving traffic problems caused by complex and diverse traffic environment, and drivers’ traffic law disobedience.

UniTraffic is a set of VAS (Video Analytics System), LPDR (License Plate Detection and Recognition) and TMS (Transportation Management System) software which uses RAW image of CCTV to provide traffic flow monitoring and counting, violation detection, vehicles’ license plate number recognition and reporting on violating vehicles.

Image Recognition Technology

Image Recognition Technology

UniTraffic's core technologies are Deep Learning-based Image Processing technology and Multi-object detection that allow counting and classifying traffic objects (pedestrian, car, motorcycle, truck, etc.) and detect violations.

Who does UniTraffic help?

Traffic Statistics for Department of Transportation

Department of Transportation

UniTraffic provides all statistical information related to traffic flow and violations.

Traffic Monitoring Solution for City Administration

City Administration

By providing reliable and comprehensive information on traffic, including vehicle classification, UniTraffic allows developing a more effective strategy for infrastructure improvements.

Traffic Law Enforcement

Police

UniTraffic detects a wide range of violations and helps to identify the violator by recognizing license plates.

Traffic violations are detected by UniTraffic

Speeding

Speeding Violation Detection

Traffic Light

Traffic Light Violation Detection

Stop Sign

Stop Sign Violation Detection

No Parking

Illegal Parking Violation Detection

Lane violation

Lane Violation Detection

Case Study 1. Vietnam

Vietnam is famous for its complexity and diversity of the traffic system. With the highest level of use of motorcycles for everyday mobility and poor traffic infrastructure, it is very difficult to create a specific and effective ITS (Intelligent Transportation System) to minimize the congestion and lethality on the roads.

IoT division of UNISEM took into consideration the complexity and diversity of the Vietnamese traffic environment and created UniTraffic to help with traffic problems, traffic analysis and control in similar traffic environment by leveraging one of the 4th Industrial Revolution’s disrupting technology AI (Artificial Intelligence).

Case Study 2. Indonesia

Indonesia’s capital Jakarta has been ranked as one of the most congested cities. A high number of people use motorcycles as main transportation vehicle used every day to get to the workplace what makes the traffic congestion very complex.

In the video below you can see how using video recorded via ordinary camera, UniTraffic’s VAS (Video Analytics System) performances with high accuracy even without special preparations.

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