Vision AI Safety Platform

QVision

Existing CCTV analysed live — detecting incidents and unsafe behaviour, masking personal data on the spot.

QVision — AI 기반 교통 분석·안전 모니터링·스마트 관제 구성
Overview

Cameras you already have, working as traffic and safety sensors

CCTV footage gives traffic counts by vehicle type, and potholes and incidents are detected live and passed to the control room.

QVision AI 비전 기반 교통 분석·안전 솔루션 구성 — 영상 입력원부터 차량 인식·보행자 감지·교통량 분석·이상행동 감지·사고 알림·통합 관제 연계까지
Recognising what is thereVehicles, pedestrians and two-wheelers told apart automatically, and their movement followed
Traffic flowCounts by vehicle type, congestion and changes in speed, hour by hour
Spotting dangerWrong-way driving, stopped vehicles, potholes and unsafe behaviour — caught before they become accidents
Into the control roomEvents reach the control screen and the person on duty, and end up in statistics and reports
Features

Vehicles and road hazards, read live from the video

Traffic is counted by vehicle type from the camera feed, and damage to the road surface is found live and sent to the control room.

TMS

Live traffic counting

Vehicles are detected and classified from the footage, counted by type and turned into statistics.

  • Counting by type Passing vehicles sorted by type and counted automatically
  • By direction at junctions Counts kept separately for each direction through the junction
  • Fixed or mobile Works for permanently installed and for mobile surveys
TMS 실시간 교통량 검출 화면 — 차종 분류·통행량 계측
Road Safety

Live pothole detection

Potholes are found live in the driving footage, and their location and details go to the control system.

  • Whatever shape they take Trained on potholes of many shapes and sizes
  • Detected and sent live Found while driving, and reported as it happens
  • Control room integration A system to monitor and manage everything that has been found
포트홀 실시간 검출 데모 화면 — 차량 영상 인식 모듈과 관제 서버
TMS · Traffic Measurement Solution

Traffic counted by vehicle type, automatically, as statistics

Vision AI tells the vehicles apart and counts them by direction of travel.

Training dataTrained across many road environments to detect more reliably
Vehicle classesThirteen classes in all — the ministry’s twelve, plus buses
Direction trackingCounts tracked according to the direction taken through the junction

Traffic survey system

Fixed and mobile cameras counting by vehicle type

Signal control

The counts feed the traffic signal control system

Parking management

Bay occupancy and vehicles entering and leaving, identified to support parking management

Incident Detection

Hazards on camera, turned into events for the control room

AI incident detection classifies what it sees and alerts both the system and the person on duty.

Wrong-way driving
Stopped vehicle
Congestion
Pedestrian on the carriageway
Fallen object
Poor visibility or smoke
Road surface damage (pothole)
Volume and vehicle type

Detection can be extended to suit the operation, with a human review step to cut false alarms. Personal image data is masked according to the operating requirements and regulations.

Designed against false alarmsConfidence score, consecutive frames and human review before it is confirmed
Night and bad weatherDetection in low light, backlight and rain, corrected with real operating data
Protecting personal image dataBlurring, separated access rights and retention limits keep it within the rules
Ideal Use Cases

It suits places like these

For places that need more out of the cameras already on the poles.

Control rooms where someone must keep watching

Too many screens to follow live, so footage only gets checked after the event

Where traffic surveys are done by hand

Roads and junctions where the people and the weeks it takes are the problem

Where road inspection depends on patrols

Potholes and cracks that ought to be found before anyone reports them

Where image data protection matters

The original footage never leaves, and personal data is masked where it is filmed