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Smart Gate - multi-model multi-agent biometric System

License: MIT

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Please, see our license . When (re-)using (part) of this work, you must cite the following publication:

Thenuwara, S.S.; Premachandra, C.; Kawanaka, H. A Multi-Agent Based Enhancement for Multimodal Biometric System at Border Control. Array 2022, 14, 100171.

How to setup the project in local machine

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How to run the project

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The reason for initiating this research is that airports operate on very strict schedules, and verifying a person's authorization at security checkpoints can be a challenging task when relying solely on online models. To address this issue, I propose an autonomous agent solution that utilizes a multi-model concept, incorporating facial, fingerprint, and voice biometrics, as well as passport documents, to compare physical appearances at the airport. The use of a multi-model concept will ensure a high level of accuracy in identifying individuals, and the integration of various biometric technologies will provide an additional layer of security. Facial recognition technology can be used to match an individual's face to their passport photo, while fingerprint and voice biometrics can be used to further verify their identity. In combination with passport documents, this system will significantly enhance the overall security of airport checkpoints.

AI-powered biometric authentication can be achieved without any hassle using an automated system.

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Moreover, the use of autonomous agents will reduce the need for manual verification and human intervention, thereby minimizing the risk of errors and delays. The proposed system will provide a faster, more efficient, and secure method for verifying travelers' identities at airports. Face recognition and document verification using a multi-agent system is a cutting-edge technology that is revolutionizing the field of biometric security. This technology allows for the identification and verification of individuals with an unprecedented level of accuracy and speed. The multi-agent system works by using multiple agents, each with their own specialized task, to carry out the face recognition and document verification process.

The face recognition component of the system involves the use of advanced algorithms and machine learning techniques to analyze an individual's facial features and match them with a pre-existing database of known faces. This process is incredibly fast and can identify individuals in real-time, making it an ideal solution for security applications. The document verification component of the system involves the use of specialized sensors and software to analyze the authenticity of various types of documents, such as passports, IDs, and visas. This technology can detect fake or altered documents with a high degree of accuracy and can help prevent identity fraud and other forms of criminal activity.

In conclusion, the integration of autonomous agents with a multi-model concept incorporating various biometric technologies and passport documents is a promising solution to the challenges posed by airport security checkpoints. It will ensure a high level of accuracy, speed, and security while reducing the need for human intervention.

More Details:

https://www.susara.lk/reseach.php

http://dl.lib.mrt.ac.lk/handle/123/16112

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Publications

2022/07 A multi-agent-based enhancement for multimodal biometric system at border control, Array Volume 14, July 2022, 100171 https://doi.org/10.1016/j.array.2022.100171

2022/01 Border Control by Multi-biometric Identification using Face and Ear images. 2nd International Conference on Image Processing and Robotics (ICIPROB) IEEE

2019/09 Hybrid Approach to Face Recognition System using PCA & LDA in Border Control, 2019 National Information Technology Conference (NITC), Colombo, Sri Lanka, 2019, pp. 9-15, doi: 10.1109/NITC48475.2019.9114426.

2017/01 Multi-Agent Approach to Face Recognition in Border Control, The 12th International Research Conference General Sir Kotelawala Defense, Sri Lanka

2019/11 Fuzzy Logic-based Approach for Back Analysis of VISA Granting Process, 3rd SLAAI-International Conference on Artificial Intelligence

2016/11 Border Control by Multi-biometric Identification using Face and Ear images," International.

2022/02 Conference on image processing and robotics (ICIPRoB2022) Japan, 2022.