TY - JOUR
T1 - Recent progress in low dimensional carbon nanomaterials sensors and their integration with artificial intelligence technologies
AU - Zhang, Yi
AU - Zhao, Lu Yu
AU - Li, Yu Tao
AU - Wang, Ye Liang
N1 - Publisher Copyright:
© 2025 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)
PY - 2025
Y1 - 2025
N2 - Carbon-based sensors based on low-dimensional carbon nanomaterials demonstrate broad application prospects in fields such as wearable devices and human–computer interaction, owing to the exceptional properties of carbon nanomaterials. Driven by advancements in artificial intelligence (AI) technology, these sensors are progressively evolving from single-function devices into intelligent systems. This article highlights five types of AI-oriented carbon-based sensors, discussing the integration and application of artificial intelligence with carbon-based sensing technology. To address challenges like insufficient external information acquisition capability and system redundancy caused by the separation of sensing and computation, we introduce the multimodal sensing system and the sensing-computation integrated architecture: the former enhances information dimensionality through collaborative perception of multiple physical signals, while the latter seamlessly integrates signal acquisition with intelligent processing. Ultimately, AI-empowered carbon-based sensing systems not only improve perception accuracy and processing efficiency but also establish the foundation for autonomous intelligent sensing systems, demonstrating substantial prospects for next-generation smart hardware.
AB - Carbon-based sensors based on low-dimensional carbon nanomaterials demonstrate broad application prospects in fields such as wearable devices and human–computer interaction, owing to the exceptional properties of carbon nanomaterials. Driven by advancements in artificial intelligence (AI) technology, these sensors are progressively evolving from single-function devices into intelligent systems. This article highlights five types of AI-oriented carbon-based sensors, discussing the integration and application of artificial intelligence with carbon-based sensing technology. To address challenges like insufficient external information acquisition capability and system redundancy caused by the separation of sensing and computation, we introduce the multimodal sensing system and the sensing-computation integrated architecture: the former enhances information dimensionality through collaborative perception of multiple physical signals, while the latter seamlessly integrates signal acquisition with intelligent processing. Ultimately, AI-empowered carbon-based sensing systems not only improve perception accuracy and processing efficiency but also establish the foundation for autonomous intelligent sensing systems, demonstrating substantial prospects for next-generation smart hardware.
KW - artificial intelligence
KW - carbon-based sensors
KW - multimodal sensing system
KW - sensing-computation integrated architecture
UR - https://www.scopus.com/pages/publications/105022416189
U2 - 10.3934/matersci.2025048
DO - 10.3934/matersci.2025048
M3 - Review article
AN - SCOPUS:105022416189
SN - 2372-0484
VL - 12
SP - 1041
EP - 1064
JO - AIMS Materials Science
JF - AIMS Materials Science
IS - 5
ER -