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@article{176934,
        author = {Ajay Biradar and Chaithrashree H J and Harshith P U and Niranjan S R and Dr. Shivashankar},
        title = {Design of Criminal Detection and Automatic Fare Deduction Model using Face Recognition in Metro Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {7731-7738},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176934},
        abstract = {Urban metro networks are growing more and more challenged to security, efficiency, and commuter convenience of modern urban metro networks due to the aging ticketing systems and manual observation. In this paper, we present a facial recognition based metro access system relying on CNN driven criminal detection as well as automatic ticket deduction, which guarantees the secured and convenient transitional of travelers. The face detection and feature extraction are done using Multi-Task Cascaded Convolutional Networks (MT-CNN) combined with FaceNet and it uses a highly accurate real time identity verification. Law enforcement authorities achieve more public security by running an integrated criminal database that enables the tracking and identification of wanted criminals. With automated fare collection module, physical tickets or cards are done away with hence curb ticketing fraud while boarding. An interactive web based system is also included in the system in which the commuters should register, monitor their travel history, and related with payment means making the system user friendly. As for the site, it offers tickets for the metro from Moscow as well as the latest real time metro information and security notifications together with a one stop solution for metro commuters as well as authorities. A real time access control is achieved through its precursor using ESP-32 micro controller, LCD screen, servo motors as its supporting devices in order to make gate automation more efficient. The system is validated experimentally for its efficiency in terms of face recognition accuracy, processing time and security enhancement process. By enabling deep learning, IoT integration and a user friendly web application, the intelligent metro solution is set to accelerate urban transformation of urban transportation through its scalability and simplistic and technologically advanced means of metro access and surveillance.},
        keywords = {Face Recognition, Criminal Detection, Automated Fare Collection, Smart Metro Systems, Deep Learning, IoT Integration, Real-time Surveillance, Contactless Ticketing, Smart Transportation.},
        month = {May},
        }