Leveraging Business Optimization Technology to Enhance Airport Security and Prohibited Item Detection through AI-Driven YOLO in Baggage Scans

Jyothisri P and R Gnanaselvam

International Journal of Scientific Research in Science and Technology, 2025, vol. 12, issue 4, 113-121

Abstract: Modern airport security depends on automated baggage screening technology to warrant passengers safety and need to stop the movement of forbidden items. This work investigates real-time object detection using YOLO (You Only Look Once) to find forbidden objects in baggage. Ideal for real-time applications, YOLO, a deep learning-based object recognition system, identifies and localizes items in a single pass. In terms of airport security, YOLO may be taught to spot firearms, explosives, liquids, and other hazardous things from X-ray luggage scans.Flagging questionable items for human verification, the system runs real-time processing on every frame of the scan.The automated method can help security staff members quickly find dangers by using YOLO's speed and accuracy, hence lowering the need for manual inspection.This strategy keeps great throughput and reduces passenger delays while dramatically enhancing security.

Keywords: YOLO; Object Detection; Airport Security; AI; Prohibited Items; Baggage Scan; Business Optimization; Computer Vision; Deep Learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v12:y2025:i4:id:988

DOI: 10.32628/IJSRST251261

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