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Journal Articles Journal of Low Power Electronics and Applications Year : 2022

Hardware Solutions for Low-Power Smart Edge Computing

Lucas Martin Wisniewski
Jean-Michel Bec
Guillaume Boguszewski


The edge computing paradigm for Internet-of-Things brings computing closer to data sources, such as environmental sensors and cameras, using connected smart devices. Over the last few years, research in this area has been both interesting and timely. Typical services like analysis, decision, and control, can be realized by edge computing nodes executing full-fledged algorithms. Traditionally, low-power smart edge devices have been realized using resource-constrained systems executing machine learning (ML) algorithms for identifying objects or features, making decisions, etc. Initially, this paper discusses recent advances in embedded systems that are devoted to energyefficient ML algorithm execution. A survey of the mainstream embedded computing devices for low-power IoT and edge computing is then presented. Finally, CYSmart is introduced as an innovative smart edge computing system. Two operational use cases are presented to illustrate its power efficiency.
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Dates and versions

lirmm-03939490 , version 1 (14-01-2023)





Lucas Martin Wisniewski, Jean-Michel Bec, Guillaume Boguszewski, Abdoulaye Gamatié. Hardware Solutions for Low-Power Smart Edge Computing. Journal of Low Power Electronics and Applications, 2022, 12 (4), pp.61. ⟨10.3390/jlpea12040061⟩. ⟨lirmm-03939490⟩
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