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@article{172046,
        author = {Sibbala Chandana and Kotha Greeshma Reddy and Gabburi Neha and Civini Meghana and Pathakamuri Harshitha and Dr. Senthilkumar S},
        title = {SMART TICKET: AN INTELLIGENT PUBLIC TRANSPORT SYSTEM WITH FRAUD DETECTION AND LOYALTY PROGRAM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {1764-1769},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172046},
        abstract = {This research explores the development and implementation of a user-friendly, secure, and scalable web-based system designed for seamless user identification and verification. Built on the Flask framework, the system integrates user registration, QR code generation, and facial recognition functionalities, offering a comprehensive solution for various use cases such as public transportation, access control, and digital ticketing. By combining Flask's flexibility with MongoDB's robust data storage capabilities, the application is designed to handle large-scale user data securely while maintaining high performance.
The face recognition component of the system is integrated to enhance security and streamline the user experience, making it faster and more convenient compared to traditional manual verification methods. In addition, the use of QR codes for automated ticketing and penalty management aims to reduce human error and operational overhead, while rewarding loyal users with a loyalty program.
The proposed solution also ensures multi-language support, catering to diverse user needs, and is designed with accessibility in mind to accommodate those with varying levels of technological literacy. Our system’s architecture and design prioritize both security and user-friendliness, ensuring a positive user experience across multiple domains.
In the future, the system can be expanded to include advanced encryption for enhanced data protection, real-time monitoring features, and machine learning capabilities to further optimize face recognition accuracy and system performance. The work presented in this paper demonstrates the potential for integrating cutting-edge web and biometric technologies to improve efficiency, reliability, and user experience across multiple industries.},
        keywords = {Smart Ticketing, Public Transport, Fraud Detection, QR Code, Face Recognition, Loyalty Program, Scalability, Security},
        month = {January},
        }