ASYNCHRONOUS TIME ENCODER BASED QUASI-STATIC MODELLING FOR HUMAN AREA NETWORK IN VANET
R. Vimal Karthick, G. S. Raj, R. Srinivasan, S. Sibi Chakkaravarthy and P. Visu
DOI : 10.3844/jcssp.2014.2284.2291
Journal of Computer Science
Volume 10, Issue 11
Power constraints play a key role in designing Human Area Networks (HANs) for bio authentication vehicle based on driverâs identity. To alleviate the power constraints, we advocate a design that uses an asynchronous time encoding mechanisms for representing bio authentication information and the skin surface as the communication channel. Time encoding does not require a clock while allows perfect signal recovery; the communication channel is operated below 1 MHz We (i) review the fundamental theory behind time encoding and signal recovery, (ii) describe the implementation of a HAN prototype, (iii) describes the implementation of bio authentication for vehicle identity and (iv) present research data obtained from our experimental platform. We demonstrate that the fidelity of the proposed signal representation and transmission scheme is well above the bio medical monitoring requirements even in the case of additive channel-noise and neighbouring channel interference. Consequently, the traditional HAN architecture consisting of clocked A/D converters feeding into digital RF channels can be replaced with a less power demanding time encoding/decoding pair that uses the skin surface as a communications channel. Here we propose a multilayer mathematical model using volume conductor theory for galvanic coupling HAN on a human limb with consideration on the inhomogeneous properties of human tissue. By introducing and checking with quasi-static approximation criteria, Maxwellâs equations are decoupled and capacitance effect is included to the governing equation for further improvement. Finally, the accuracy and potential of the model are examined."
© 2014 R. Vimal Karthick, G. S. Raj, R. Srinivasan, S. Sibi Chakkaravarthy and P. Visu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.