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This paper presents a design of reconfigurable hardware platform for wireless sensor networks to achieve high flexibility and robustness in system operation and resource utilization. The goal of this research is to develop a new type of sensor networks with cognitive features (e.g., context awareness and situation understanding) such that human behavioral biometrics can be measured through distributed low-cost sensors. The proposed reconfigurable hardware platform can adjust its sensing and computing resources with respect to changing contexts and situations. It includes three components: (1) reconfigurable analog circuit for adaptive sensor conditioning, (2) reconfigurable ADC for maintaining high signal-to-noise ratio, and (3) FPGA based reconfigurable computing for situation understanding. In behavioral biometrics applications, such a reconfigurable platform can automatically change circuit parameters, ADC resolutions, filter coefficients, and algorithms according to application contexts and situations derived from sensory signal features. As a result, the sensing system can be adaptive to various behavioral biometrics applications with high fidelity and accuracy. Experimental results have demonstrated the advantages of the proposed hardware platform.
Sensors, 2012 IEEE
Date of Conference: 28-31 Oct. 2012