Overview of smart sensors based on machine learning

With the rapid development of machine learning, intelligent models created by machine learning algorithms are gradually becoming the core part of new sensor data analysis. The paper firstly introduces the background of intelligent sensors that support machine learning, briefly describes the construction of intelligent models and the generation, verification and testing process of data sets, then lists the application of intelligent sensors based on machine learning, finally points out the current problems and challenges of intelligent sensors based on machine learning and puts forward feasible solutions to provide valuable academic reference for relevant researchers.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-03-01
DOI
https://doi.org/10.16157/j.issn.0258-7998.245715
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Overview of smart sensors based on machine learning

SHILAP Revista de lepidopterología
Air Quality Monitoring and Forecasting
article

Overview of smart sensors based on machine learning

article en

Abstract

With the rapid development of machine learning, intelligent models created by machine learning algorithms are gradually becoming the core part of new sensor data analysis. The paper firstly introduces the background of intelligent sensors that support machine learning, briefly describes the construction of intelligent models and the generation, verification and testing process of data sets, then lists the application of intelligent sensors based on machine learning, finally points out the current problems and challenges of intelligent sensors based on machine learning and puts forward feasible solutions to provide valuable academic reference for relevant researchers.

SHILAP Revista de lepidopterología
Petroleum University of Technology (IR), China University of Petroleum, Beijing (CN), Ministry of Natural Resources (RW), Haier Group (China) (CN), Ocean University of China (CN)
Openalex Percentile: Top 57%
Air Quality Monitoring and Forecasting
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