System-Level Power Consumption Modeling for Autonomy Estimation on Smart Connected Glasses

Autor: Arcaya Jordan, Alexis, Pegatoquet, Alain, Castagnetti, Andrea
Přispěvatelé: Laboratoire d'Electronique, Antennes et Télécommunications (LEAT), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Ellcie-Heathy, ANR-15-IDEX-0001,UCA JEDI,Idex UCA JEDI(2015)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: 13ème Colloque National du GDR SOC2
13ème Colloque National du GDR SOC2, Jun 2019, Montpellier, France
Popis: National audience; Wearable devices running sensor-based applications for human health, wellness and safety monitoring are increasinglyuseful, looking for early diagnoses of pathologies as well as for detection of risks. The Ellcie-Healthy start-up is developing smart connected glasses, a wearable device designed for e-Health and road safety applications. The main constraint on this devices is the imited amount of embedded energy for running applications, making necessary the study of the power consumption through a system level modeling approach for getting fast and accurate information useful for energy consumption optimization. In this paper, we propose to estimate the autonomy of these glasses using analytical power models based on the system activities. Those models are validated through experimental measurements on real scenarios. The lifetime of the smart glasses can be estimated for different system configurations with less than 10% error.
Databáze: OpenAIRE