TY - GEN
T1 - Dynamic service switching for the medical IoT
AU - Kindt, Philipp
AU - Yunge, Daniel
AU - Tobola, Andreas
AU - Fischer, Georg
AU - Chakraborty, Samarjit
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/21
Y1 - 2016/12/21
N2 - With the Internet of Things (IoT) becoming a reality, power-efficient techniques are crucial to achieve sufficient battery lifetimes. Whereas current medical IoT devices typically acquire data with a constant quality, we propose an architecture that dynamically adjusts the data quality adaptively based on the current medical condition of the subject being monitored. Since transmission and processing make up a large fraction of the energy consumption, the reduction of the link traffic and processing effort caused by such an adjustment results in a decreased energy consumption of the devices. For example, if anomalies in the monitored data are detected, the monitoring is performed with an increased granularity and more exhaustive processing. Further, not all data generated by the medical sensors needs to be transmitted during all times. Only if certain events are detected, the transmission of the complete data needs to be activated. In this paper, we present a novel approach for body-worn medical IoT devices. In particular, a generic, distributed architecture for the power-management of the whole system, which is based on dynamically switching services, is presented. We show that such an architecture can reduce the energy-consumption of medical sensors by up to 80 % in real-world measurements.
AB - With the Internet of Things (IoT) becoming a reality, power-efficient techniques are crucial to achieve sufficient battery lifetimes. Whereas current medical IoT devices typically acquire data with a constant quality, we propose an architecture that dynamically adjusts the data quality adaptively based on the current medical condition of the subject being monitored. Since transmission and processing make up a large fraction of the energy consumption, the reduction of the link traffic and processing effort caused by such an adjustment results in a decreased energy consumption of the devices. For example, if anomalies in the monitored data are detected, the monitoring is performed with an increased granularity and more exhaustive processing. Further, not all data generated by the medical sensors needs to be transmitted during all times. Only if certain events are detected, the transmission of the complete data needs to be activated. In this paper, we present a novel approach for body-worn medical IoT devices. In particular, a generic, distributed architecture for the power-management of the whole system, which is based on dynamically switching services, is presented. We show that such an architecture can reduce the energy-consumption of medical sensors by up to 80 % in real-world measurements.
UR - http://www.scopus.com/inward/record.url?scp=85010022764&partnerID=8YFLogxK
U2 - 10.1109/PIMRC.2016.7794845
DO - 10.1109/PIMRC.2016.7794845
M3 - Conference contribution
AN - SCOPUS:85010022764
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
BT - 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016
Y2 - 4 September 2016 through 8 September 2016
ER -