Multimodal biometric systems have progressively been introduced to solve these issues. Multimodal biometrics has been used to verify people to make authentication easier in smart city environments. Personal and biological problems, such as limited sample size and noise tracking devices, have a significant impact on the accuracy rate of unimodal biometric systems. While unimodal authentication technologies are more accurate, they only address a few issues, such as spoofing resistance and good privacy. ![]() Additionally, the iris is the most accurate biometric because it is distinctive and consistent over time 1. Among these different traits, fingerprints seem to be a commonly used biometric trait. Facial characteristics, retinal characteristics, vein patterns, speech patterns, keystroke dynamics, nail bed, ear design, fingerprints, and other biological attributes have also been studied for verification purposes. A biometric system is an automated system that recognizes a person related to behavioral or physiological characteristics, and it has made considerable progress in a variety of applications, such as surveillance, identification, access control, and protection. The future of smart city security is based on multimodal biometrics. The vital part of this approach is the inclusion of a fuzzy strategy with soft computing techniques known as an optimized fuzzy genetic algorithm. The proposed scheme provides a higher accuracy rate of 99.88% and a lower equal error rate of 0.18%. The result analysis shows that the proposed approach provides better performance in terms of the false acceptance rate, false rejection rate, equal error rate, precision, recall, and accuracy. ![]() Experiments with different biometric environments reveal significant improvements over existing strategies. Specifically, the proposed approach provides a solution to the existing challenges by providing a multimodal fusion technique with an optimized fuzzy genetic algorithm providing enhanced performance. This paper proposes an enhanced multimodal biometric technique for a smart city that is based on score-level fusion. The multimodal biometric technique with enhanced accuracy and recognition rate for smart cities is still a challenging issue. In recent years, research initiatives in the field of biometrics have grown at an exponential rate. Biometric security is a major emerging concern in the field of data security.
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