| Abstract |
A smart city is a trend in urban planning that uses technology for communication and information to enhance nearly every element of urban life. In a smart city, inhabitants can communicate directly with each other and the infrastructure at any time. Due to the widespread use of smart devices, security and privacy concerns have grown into a serious problem that calls for strong solutions. The system is secured via biometrics, OTP creation, iris detection, and other security-related techniques. The biometric system is one of the more well-established security solutions. Obtaining images with near-infrared (NIR) or visible wavelength (VW) lighting under constrained and unconstrained conditions is the primary challenge with biometric security systems. This paper proposes a model for having secured access to amenities in smart cities. The model will use a combination of biometric features to provide access to ITS services. This includes the combinations of iris, periocular, and fingerprints. The proposed model elaborates on the level 3 type of authentication system and the amalgamation of iris, periocular, and fingerprint features for authentication. The suggested model operates on the concepts of data augmentation, feature learning with CNN, and deep learning for the detection of biometric authentication. © 2022 IEEE. |
