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@article{178084,
        author = {CH.SWAPNA and A.RANADHEER and A.PRANAV and CH.AKHIL},
        title = {FACIAL AND VOICE BASED VEHICLE  SECURITY SYSTEM USING ML AND IOT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2807-2812},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178084},
        abstract = {This paper presents the design and development of a smart vehicle locking system combining facial recognition and voice commands for enhanced security and ease of use. A laptop handles image processing and machine learning to identify authorized users via the built-in camera. An ESP32 microcontroller supports Bluetooth-based voice recognition and real-time GPS tracking. The Blynk IoT platform enables remote monitoring and control. Once a face is recognized, the user can lock or unlock the vehicle through authenticated voice commands. GPS data from the ESP32 provides location tracking. This dual-authentication approach improves vehicle safety through machine learning accuracy and hands-free operation. Integrating technologies like image processing, ML, Bluetooth, and IoT, the system offers a comprehensive and practical security solution for vehicles, suitable for fleet management and smart transport systems.},
        keywords = {Facial Recognition, Voice Authentication, ESP32, IoT, Vehicle Security, Blynk, Machine Learning, GPS},
        month = {May},
        }