Improvised Guard for Next Level Security Automated Vehicle Security System using Artificial Intelligence and Convolutional Neural Network


Authors : Joel M John; Noel Phillip Issac; Jerin Thomas; Subin Alexander; Syamraj B S

Volume/Issue : Volume 5 - 2020, Issue 7 - July

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/32w0m9l

DOI : 10.38124/IJISRT20JUL121

Abstract : This paper details fully automated vehicle security system involving vehicle model, make detection, driver face recognition and parking system guided by a virtual assistant. The core technology of the system is built using a sequence of deep Convolutional Neural Networks (CNNs). This system performs face recognition of the driver and vehicle model, make detection and permit access by opening barrier gate. This allows bigger organizations to control and monitor vehicle traffic as well as gain user data for security purpose. For quantitive analysis, we show that our system outperforms the leading vehicle security system. Proposed paper project website is also available at http://www.astound.ga/igns.

Keywords : Virtual Assistant, Recognition, Authorization, Validation, Vehicle, User interaction.

This paper details fully automated vehicle security system involving vehicle model, make detection, driver face recognition and parking system guided by a virtual assistant. The core technology of the system is built using a sequence of deep Convolutional Neural Networks (CNNs). This system performs face recognition of the driver and vehicle model, make detection and permit access by opening barrier gate. This allows bigger organizations to control and monitor vehicle traffic as well as gain user data for security purpose. For quantitive analysis, we show that our system outperforms the leading vehicle security system. Proposed paper project website is also available at http://www.astound.ga/igns.

Keywords : Virtual Assistant, Recognition, Authorization, Validation, Vehicle, User interaction.

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