Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/12298
Title: Development of a Vehicle Driving Authorization Permit and Fake Driver Detection System Using Fingerprints Techniques
Authors: Adekunle, Salako Emmanuel
Abdullahi, Muhammad Bashir
Adepoju, Solomon Adelowo
Keywords: Vehicle
Authorization Permit
Fingerprint
Fake Driver
Detection
Issue Date: Mar-2020
Publisher: Advances in Mathematics & Computational Sciences
Citation: Salako, E. A., Muhammed, B.A. & Solomon, A. A. (2020): Development of a Vehicle Driving Authorization Permit and Fake Driver Detection System Using Fingerprints Techniques. Journal of Advances in Mathematical & Computational Sc. Vol. 8, No. 1. Pp 1-14
Series/Report no.: Vol. 8 No. 1, March 2020;
Abstract: The world at large is characterized by the rising of vehicle thefts thereby leaving many owners of vehicles helpless in the hand of thieves and unauthorized drivers. The safety of the vehicle has become a matter of major significance to the owners. Among the issues of concern that could easily lead to stealing of vehicle or driving by the unauthorized drivers is the lack of good parking spaces in offices arena or residential areas and lack of availability of sophisticated security devices. As a technological approach to providing the solution to the aforementioned problem, this research was on the development of a vehicle driving authorization permit and fake driver detection system using fingerprint technique. The system had majorly three modules, namely enrolment, driver’s, authentication and Global System for Mobile (GSM). An enrolled driver sent a destination code from a registered mobile number to the authentication module before the commencement of the journey that would be used for the authentication at the various checking points. The developed system was designed and implemented using C# and SQL programming languages. Eight biometric standard metrics were used to evaluate the system. Series of tests were carried out in five different towns in five states of Nigeria. The developed system was able to suitably identified fake drivers and permitted genuine drivers to proceed on the journey earlier specified. The result of the analysis showed an excellent system accuracy value of 96.25% with a lower Equal Error Rate of 3.75% with the mean-time of 49 seconds to create a reference template.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/12298
Appears in Collections:Computer Science



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