Back to Search Start Over

Prospects and Challenges of AI and Neural Network Algorithms in MEMS Microcantilever Biosensors.

Authors :
Wang, Jingjing
Xu, Baozheng
Shi, Libo
Zhu, Longyang
Wei, Xi
Source :
Processes; Aug2022, Vol. 10 Issue 8, p1658-1658, 25p
Publication Year :
2022

Abstract

This paper focuses on the use of AI in various MEMS (Micro-Electro-Mechanical System) biosensor types. Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into our daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a number of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active development of artificial intelligence (AI) and neural networks. As a result, this paper examines the fundamentals of the neural algorithm and goes into great detail on the fundamentals and uses of the principal component analysis approach. A neural algorithm application in Micro-Electro-Mechanical System microcantilever biosensors is anticipated through the associated application of the principal com-ponent analysis approach. Our investigation has more scientific study value, because there are currently no favorable reports on the market regarding the use of AI with Micro-Electro-Mechanical System microcantilever sensors. Focusing on AI and neural networks, this paper introduces Micro-Electro-Mechanical System biosensors using artificial intelligence, which greatly promotes the development of next-generation intelligent sensing systems, and the potential applications and prospects of neural networks in the field of microcantilever biosensors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22279717
Volume :
10
Issue :
8
Database :
Complementary Index
Journal :
Processes
Publication Type :
Academic Journal
Accession number :
158910897
Full Text :
https://doi.org/10.3390/pr10081658