Advanced Wearable Systems, Biometric Authentication, Real-Time Health Analytics, Edge Computing, and AI-Driven Applications.
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Advanced Wearable Systems, Biometric Authentication, Real-Time Health Analytics, Edge Computing, and AI-Driven Applications.
Dr. Suneel Pappala, Associate Professor, Artificial Intelligence and Data Science, St. Mary’s Group of Institutions Hyderabad, Telangana, India.
Velpula Harikishan, Assistant Professor, Computer Science & Engineering, St. Mary’s Group of Institutions Hyderabad, Telangana, India.
T. Shanti Latha, Assistant Professor, Computer Science & Engineering, St. Mary’s Group of Institutions Hyderabad, Telangana, India.
Abstract: Wearable technology has rapidly evolved into a critical component of modern health, fitness, and security systems, largely driven by advances in real-time monitoring and biometric sensors. This paper provides a comprehensive overview of the current state and future prospects of wearable devices, focusing on the integration of advanced sensors that continuously capture physiological and environmental data. Real-time monitoring enables instantaneous feedback, empowering users to make informed decisions about their well-being and performance. Key biometric sensors such as fingerprint, iris, retinal, and facial recognition devices are explored, highlighting their technologies, applications, and challenges. These sensors utilize sophisticated imaging, infrared illumination, and pattern recognition algorithms to provide accurate, non-invasive identification and health tracking. The scalability of wearable technology is examined through manufacturing, technical infrastructure, and organizational strategies that support growth without compromising quality or user experience. Challenges such as sensor accuracy, power consumption, data privacy, and seamless integration remain central to ongoing research and development. Emerging trends in artificial intelligence, edge computing, and 5G connectivity promise to enhance data processing speeds, security, and personalized user interaction, driving the next generation of wearable devices. Furthermore, the paper discusses the implications of biometric data in healthcare, security, and smart environments, underscoring ethical and privacy considerations.
Keywords: Fingerprint Recognition, Iris Recognition, Retinal Scanning, Face Recognition, Health Monitoring, IoT Devices
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