A Risk Evaluation Framework in System Control Subject to Sensor Degradation and Failure

Sensor degradation and failure often undermine users’ confidence in adopting a new data-driven decision-making model, especially in risk-sensitive scenarios. A risk assessment framework tailored to classification algorithms is introduced to evaluate the decision-making risks arising from sensor degr...

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Published inSensors (Basel, Switzerland) Vol. 24; no. 5; p. 1550
Main Authors Yuan, Tangxiao, Xu, Weilin, Adjallah, Kondo Hloindo, Wang, Huifen, Liu, Linyan, Xu, Junshan
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 28.02.2024
MDPI
Subjects
Access control
Accuracy
Algorithms
Automatic Control Engineering
Big Data
black box
Case studies
Computer Science
Control systems
Data entry
Data processing
Decision making
Failure
Fault tolerance
framework
Modeling and Simulation
Probability
Rankings
Risk assessment
risk prediction
sensor failure
Sensors
Systems stability
Transportation industry
China
risk assessment
framework
sensor failure
black box
decision-making
risk prediction
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Summary:Sensor degradation and failure often undermine users’ confidence in adopting a new data-driven decision-making model, especially in risk-sensitive scenarios. A risk assessment framework tailored to classification algorithms is introduced to evaluate the decision-making risks arising from sensor degradation and failures in such scenarios. The framework encompasses various steps, including on-site fault-free data collection, sensor failure data collection, fault data generation, simulated data-driven decision-making, risk identification, quantitative risk assessment, and risk prediction. Leveraging this risk assessment framework, users can evaluate the potential risks of decision errors under the current data collection status. Before model adoption, ranking risk sensitivity to sensor data provides a basis for optimizing data collection. During the use of decision algorithms, considering the expected lifespan of sensors enables the prediction of potential risks the system might face, offering comprehensive information for sensor maintenance. This method has been validated through a case study involving an access control.
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This paper is an extended version of our paper published in “A Risk Evaluation Method Before Using a Black-box Model Considering Sensor Failure” presented at the 2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Dortmund, Germany, 7–9 September 2023.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24051550