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Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part I

Research Article

Design of Intelligent Security Inspection System for Airport Passengers’ Carry on Luggage Based on Machine Learning

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-50571-3_7,
        author={Chun Zheng and Xiafu Pan},
        title={Design of Intelligent Security Inspection System for Airport Passengers’ Carry on Luggage Based on Machine Learning},
        proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part I},
        proceedings_a={ICMTEL},
        year={2024},
        month={2},
        keywords={Machine Learning Airport Passengers Personal Luggage Intelligent Security Check},
        doi={10.1007/978-3-031-50571-3_7}
    }
    
  • Chun Zheng
    Xiafu Pan
    Year: 2024
    Design of Intelligent Security Inspection System for Airport Passengers’ Carry on Luggage Based on Machine Learning
    ICMTEL
    Springer
    DOI: 10.1007/978-3-031-50571-3_7
Chun Zheng1,*, Xiafu Pan2
  • 1: Anhui Sanlian University
  • 2: Department of Public Safety Technology, Hainan Vocational College of Political Science and Law
*Contact email: zhenghaha020@163.com

Abstract

When carrying out the airport passenger baggage intelligent screening, due to the complexity of the algorithm, there are errors in the screening results. Therefore, the design of the airport passenger carry-on baggage intelligent screening system based on machine learning is studied. The hardware design of the system is completed by designing the interface between the security system and the departure system, the external interface between the security system and the baggage system, and the airport passenger carry-on baggage intelligent screening module; In the software design, the computer vision technology in the machine learning algorithm is used to identify the carry-on baggage of airport passengers, and the airport passenger carry-on baggage security detection algorithm is designed, which effectively realizes the intelligent security check of airport passenger carry-on baggage. The test results show that the change of ASII code value of the system designed in this paper is relatively stable, and the memory occupancy is always within 25%, which can effectively meet the requirements of users and improve the performance of the system.

Keywords
Machine Learning Airport Passengers Personal Luggage Intelligent Security Check
Published
2024-02-21
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-50571-3_7
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