INCHEON AIRPORT

AI recognition-based next-generation airport immigration management system

Development time

7 Month

Manpower

4 Professionals

The Brief

AI vision recognition-based next generation airport immigration control system development and demonstration project promoted by the Ministry of Justice and Information and Communication Industry Promotion agency to implement deep learning-based CCTV data analysis system for detection and prediction of various crimes and terror attempts. Ellexi has been selected as a main AI technology developer for this project.

Service

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Development AI module for detecting & tracing individual(s)

API based system integration

Maintenance

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1

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2

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3

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4

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5

Data Collection & Modelling

Identification of specific person and development of tracking module using multiple cameras (3 or more)

Dashboard / Visualization

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System should detect and track an individual(s) abnormal/dangerous behavior with multiple cameras in real time and should be able to integrate with existing security monitoring system.

Technological Challenges

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Abnormal Behavior Recognition

System should detect and trigger alarm for any actions categorized as below.

Function

Challenges

2-person detection

Accuracy and processing time

  • Abnormal behavior detection in designated area)

Backward(reverse) movement

Accuracy and processing time

  • Abnormal behavior detection in designated area)

Make a dash

Accuracy and processing time

  • Abnormal behavior detection in designated area)

Leave belongings behind

Accuracy and processing time

Abnormal behavior, event, object tracking

  • Identification of abnormal behavior, accuracy, and processing time

  • Categorization of identified abnormal behavior.

  • Accuracy of object tracking

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공항

Road Map

  • Modelling module

  • Abnormal Behavior Explanation module

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  • Detection module

  • Prediction

  • Module upgrades

Key Features

Abnormal behavior Detection

  • Multi-camera feature extraction

  • Specified/unspecified abnormal behavior detection

Reasoning function

  • Detection of more the five (5) simultaneous events

  • Specified/unspecified detection reasoning.

  • Facial recognition module integration capability

  • Operator Feedback function

Learning Features

  • Specific area learning

  • Specified/unspecified abnormal behavior detection learning features

Abnormal behavior description function

  • Multi-camera object extraction

  • Specified abnormal behavior classification visualization.

  • Object recognition-based abnormal behavior description display

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The Result

Multiple-camera support: 2 or more

Multiple-camera object tracking: 3 consecutive cameras

Specified abnormal behavior detection accuracy: above 90%