Special Issue on Implicit BIOmetric Authentication and Monitoring through Internet of Things
摘要截稿:
全文截稿: 2020-09-30
影响因子: 3.255
期刊难度:
CCF分类: C类
中科院JCR分区:
• 大类 : 计算机科学 - 3区
• 小类 : 计算机:人工智能 - 3区
Overview
According to reliable forecasts, the expected number of connected IoT devices could exceed 25 billions by 2020. An important fraction of this number includes last generations mobile and wearable devices featuring an arsenal of advanced sensors (high speed/depth/multi-focal cameras, finger imaging, accelerometers, gyros, etc.), up to 5G communication capability and growing computing power. These collection of features makes them particularly suited to capture both static and dynamic biometrics, to continuosly monitor health signals and/or to provide information about the operating context. In summary, these capabilities will enable a new generation of Internet of Biometric Things (IoBT) approaches which will greatly extend the range and the target of "mainstream" biometric applications. This Special Issue aims at gathering the latest research findings and applications for transparent acquisition and processing of biometrics and health signals in the context of ubiquitous IoBT-based user authentication and monitoring, outlining new application scenarios for mobile biometrics.
Topics include, but are not limited to:
IoBT enabled biometrics
Ubiquitous user authentication/recognition
Ubiquitous biometric monitoring
Implicit IoBT-enabled authentication/recognition
Implicit IoBT-enabled activity recognition
Implicit IoBT-enabled context detection
Dynamic biometrics capture and processing
Implicit psychophysical assessment
Deep Learning for IoBT applications
Health signals analysis via mobile devices
Elders monitoring through IoBT devices and approaches