International Journal For Multidisciplinary Research

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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.

Airguard Ai: Revolutionizing Air Cargo Inspection through Pygame and YOLOv8 Simulation

Author(s) Aryan Malviya, Siddharth Singh, R. Brindha, R.K. Pongiannan
Country India
Abstract The objective of this project is to create a simulation for air cargo inspection using artificial intelligence (AI). This will be achieved by combining Pygame for simulating conveyor belts and YOLOv8 for detecting hazardous items. The
simulation replicates a conveyor belt system that transports air cargo for inspection. Pygame, a robust game development package, is used to build a graphically interactive environment where users may view and examine the cargo inspection process in a simulated context. The primary element of the project entails using YOLOv8, an advanced object detection model, to precisely locate dangerous things within the shipment. The real-time detection capabilities of YOLOv8 allow for quick and efficient examination of the cargo, ensuring the timely identification of any hazards.
The simulation serves as a platform to assess and verify the effectiveness of the AI-driven cargo inspection system across different scenarios. Users have the ability to engage with the simulation by modifying factors like the speed of the conveyor belt, the types of cargo, and the criteria for inspection. This allows them to assess the effectiveness of the system in identifying dangerous objects.
This project functions as an instructional tool to comprehend the incorporation of AI in cargo inspection, while also having practical implications for improving real-world air cargo security. Pygame and YOLOv8, when combined, offer a flexible and robust framework for simulating and evaluating AI-based inspection systems. This contributes to the progress of air cargo safety and security measures.
Keywords AI-Powered Inspection, Pygame Simulation, YOLOv8 Object Detection, Air Cargo Security, Hazardous Item Identification
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-23
Cite This Airguard Ai: Revolutionizing Air Cargo Inspection through Pygame and YOLOv8 Simulation - Aryan Malviya, Siddharth Singh, R. Brindha, R.K. Pongiannan - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.17980
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.17980
Short DOI https://doi.org/gtrss6

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