Cognitive sensing for distributed behavioral biometrics

Abstract

This paper presents a cognitive sensing framework that enables tracking and identification of individuals' behavioral biometrics through thermal, pressure, photonic, acoustic, and laser sensors. Besides low cost, those sensors can produce sparse behavioral biometric data that can be analyzed quickly. To achieve this goal, we will develop: (1) a set of cognitive capabilities for sensing systems, such as spatial, data, context, and group awareness; (2) a multi-agent architecture for system operation and adaptation that enables heterogeneous sensors to achieve consensus in behavior analysis; and (3) a set of tools for situation understanding, cross-layer adaptation, and behavior based collaboration. The developed computing infrastructure will enable research activities about behavioral biometrics based on low-cost, low-power, distributed platforms with a variety of sensing modalities. The developed cognitive sensing intelligence has great potentials to cope with the technical challenges in behavioral biometrics caused by long distances and crowded scenes.