@article{
 title = {Adaptive rule engine based IoT enabled remote health care data acquisition and smart transmission system},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {Adaptive rule engine,ECG,IEEE 802.15.4,data rate,energy consumption},
 pages = {253-258},
 id = {8f3e323a-a90c-3b68-b09d-d4c4bbff6757},
 created = {2015-04-30T11:14:14.000Z},
 file_attached = {true},
 profile_id = {5e73f9af-1f10-3a70-a285-d3fbb699efe2},
 group_id = {e134fb94-8118-3ebe-b82d-bfbf0a8ae633},
 last_modified = {2015-04-30T11:59:24.000Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 abstract = {In the remote health care monitoring applications, the collected medical data from bio-medical sensors should be transmitted to the nearest gateway for further processing. Transmission of data contributes to a significant amount of power consumption by the transmitter and increase in the network traffic. In this paper we propose a low complex rule engine based health care data acquisition and smart transmission system architecture, which uses IEEE 802.15.4 standard for transferring data to the gateway. The power consumed and the network traffic generated by the device can be reduced by event based transmission rather than continuous transmission of data. We developed two different rule engines: static rule engine and adaptive rule engine, which decides whether to transmit the collected data based on the important features extracted from the data, thereby achieving power saving. In this paper, ECG data acquisition and transmission architecture is considered. The metrics used for performance analysis are the amount of power saving and reduction in network traffic. It is shown that the proposed rule engine gives a significant reduction in energy consumption and network traffic generated.},
 bibtype = {article},
 author = {Kiran, M. P R Sai and Rajalakshmi, P. and Bharadwaj, Krishna and Acharyya, Amit},
 journal = {2014 IEEE World Forum on Internet of Things, WF-IoT 2014}
}

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