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Joint session between eSAME and S-Cube conference

Schedule : 16H00 – 17H20
Chairman : Michele Magno
Place : Amphi

Topic : This session will discuss about the new architecture and technology to lower device power consumption.

16H00 – 16H20 :
“Comparison of Power-Efficiency of Asthmatic Wheezing Wearable Sensor Architectures

Dinko Oletic and Vedran Bilas

University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia

Abstact : Power-requirements of a wireless wearable sensor for quantification of asthmatic wheezing in respiratory sounds, a typical symptom of chronic asthma, are analysed. Two converse sensor architectures are compared. One featuring processing-intensive on-board respiratory sound classification, and the other performing communication-intensive signal streaming, employing compressive sensing (CS) encoding for data-rate reduction, with signal reconstruction and classification performed on the peer mobile device. It is shown that lower total sensor power, ranging from 216 to 357 uW, may be obtained on the sensor streaming the CS encoded signal, operating at the compression rate higher than 2x. Total power-budget of 328 to 428 uW is shown required in the architecture with on-board processing.


16H20 – 16H40 : “Reconfigurable and Long-Range Wireless Sensor Node for Long Time Operation

Nabil Islam* , Fabien Ferrero² Leonardo Lizzi² , Christophe Danchesi* , and Stephane Boudaud*

* Abeeway, Sophia Antipolis France,,

² Université Cote d’azur, CNRS, LEAT, Batiment forum, Campus SophiaTech, 06903 Sophia Antipolis Cedex, France

Abstact : This paper presents a low-power wireless sensor node platform with long-range communication capabilities based on LoRa technology. A frequency reconfigurable antenna is integrated to compensate effects from the environment. The platform integrates an accelerometer and a temperature sensor and it can monitor and transmit the device activity and temperature during more than 7 years.


16H40 – 17H00 : “Comparative Analysis of Simulation and Real-world Energy Consumption for Battery-life Estimation of LowPower IoT (internet of things) deployment in Varying Environmental Conditions using Zolertia Z1 motes

Ashutosh Bandekar , Akshay Kotian, Ahmad Y Javaid

EECS Department, The University of Toledo, Toledo, Ohio, USA

Abstact : Battery life and power consumption have been a challenging real-world problem for the internet of things (IoT). IoT applications in biomedical, agriculture, ecosystem monitoring, wildlife management, etc., need an accurate estimation of average battery life based on the environment and application. In this paper, we opt for an experimental approach and use various types of real-world environmental conditions such as the presence of interferences and high-intensity lights, to determine the actual power consumption of IoT nodes with a new set of off-the-shelf AA batteries for each scenario. We took readings in each of these environments such as an indoor Basketball Court, an Auditorium, and a room (our lab) and to verify results in outdoor conditions we chose parking lot as one of the testing environments. Further analysis and experimentation were performed to get detailed results. Results were obtained using widely used Zolertia Z1 hardware motes arranged in a specific and consistent pattern. We have compared our experimental results with simulated results in the Cooja simulator.