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@article{177765,
        author = {Vishal A R and Jansi Rani S and Sarweswaren R},
        title = {Real-Time Lie Detection and Deception Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2779-2783},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177765},
        abstract = {Historically, lie detection has relied on invasive techniques such as polygraphs, which often lack accuracy and necessitate significant human intervention. This paper presents a mobile application designed for real-time, non-intrusive lie detection, leveraging advancements in Artificial Intelligence (AI) and Machine Learning (ML). The application evaluates facial micro-expressions and vocal stress signals by capturing live video and audio through a Flutter-based platform. The collected data is processed in the cloud using deep learning algorithms. By integrating technologies like TensorFlow, OpenCV, MediaPipe, and Firebase, the application delivers instant deception analysis while ensuring a user-friendly experience. This novel approach is scalable, adaptable, and applicable across various domains, including security, forensics, and psychology.},
        keywords = {Time Analysis, Facial Micro-Expressions, Vocal Stress Analysis, Artificial Intelligence (AI), Lie Detection, Facial Micro-Expressions, Deep Learning.},
        month = {May},
        }