Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/50536
Título: Intelligent systems using triboelectric, piezoelectric, and pyroelectric nanogenerators
Palavras-chave: Nanogenerators
Intelligent systems
Machine learning
Self-powered sensing
Artificial intelligence
Nanogeradores
Sistemas inteligentes
Aprendizado de máquina
Sensor autoalimentado
Inteligência artificial
Data do documento: 2022
Editor: Elsevier
Citação: ASKARI, H. et al. Intelligent systems using triboelectric, piezoelectric, and pyroelectric nanogenerators. Materials Today, [S.I.], v. 52, p. 188-206, Jan./Feb. 2022. DOI: https://doi.org/10.1016/j.mattod.2021.11.027.
Resumo: Recent advances in artificial intelligence, computer science, communication, sensing and actuation technologies have resulted in the development of several novel intelligent systems. At the same time, the emergence of nanogenerators has opened a new research avenue with the overarching goal of developing self-powered sensing systems. The concepts of self-powered sensing, based on nanogenerators and intelligent systems can be fused together to open a new area of interdisciplinary research. In this article, we aim to show how these two emerging technologies have been combined to develop self-powered intelligent sensing systems. We first focus on the main keywords in the area of nanogenerators. Keyword co-occurrence network graphs are generated based on the most used keywords in the area of nanogenerators to select key concepts that are directly connected to the concept of intelligent systems. Thus, a detailed review is provided on different intelligent self-powered sensing systems based on nanogenerators. We also discuss the challenges presented by combining intelligent systems and self-powered sensing. As most of intelligent devices rely on machine learning techniques, a comprehensive section is allocated to this topic to focus on its applications in nanogenerator-based devices.
URI: https://doi.org/10.1016/j.mattod.2021.11.027
http://repositorio.ufla.br/jspui/handle/1/50536
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