Joint Self-Attention Mechanism and Residual Network for Automated Monitoring of Intelligent Sensor in Consumer Electronics

Zhong, Senming; Ali, Rahman

doi:10.1109/tce.2023.3320818

IEEE Trans. Consumer Electron.

2024

DOI: 10.1109/tce.2023.3320818

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Joint Self-Attention Mechanism and Residual Network for Automated Monitoring of Intelligent Sensor in Consumer Electronics

Senming Zhong,

Rahman Ali

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Cited by 3 publications

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Hong,

et al. 2024

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Guest Editorial of the Special Section on Consumer Electronics in the Era of the Internet of Everything (IoE) and Massive Data

Xia,

Hong,

et al. 2024

IEEE Trans. Consumer Electron.

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QuARCS: Quantum Anomaly Recognition and Caption Scoring Framework for Surveillance Videos

Mukherjee,

Hassija,

Chamola

2024

IEEE Trans. Consumer Electron.

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Multimodal Large Language Model-Based Fault Detection and Diagnosis in Context of Industry 4.0

Alsaif,

Albeshri,

Khemakhem

et al. 2024

Electronics

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In this paper, a novel multimodal large language model-based fault detection and diagnosis framework that addresses the limitations of traditional fault detection and diagnosis approaches is proposed. The proposed framework leverages the Generative Pre-trained Transformer-4-Preview model to improve its scalability, generalizability, and efficiency in handling complex systems and various fault scenarios. Moreover, synthetic datasets generated via large language models augment the knowledge base and enhance the accuracy of fault detection and diagnosis of imbalanced scenarios. In the framework, a hybrid architecture that integrates online and offline processing, combining real-time data streams with fine-tuned large language models for dynamic, accurate, and context-aware fault detection suited to industrial settings, particularly focusing on security concerns, is introduced. This comprehensive approach aims to address traditional fault detection and diagnosis challenges and advance the field toward more adaptive and efficient fault diagnosis systems. This paper presents a detailed literature review, including a detailed taxonomy of fault detection and diagnosis methods and their applications across various industrial domains. This study discusses case study results and model comparisons, exploring the implications for future developments in industrial fault detection and diagnosis systems within Industry 4.0 technologies.

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Joint Self-Attention Mechanism and Residual Network for Automated Monitoring of Intelligent Sensor in Consumer Electronics

Cited by 3 publications

References 29 publications

Guest Editorial of the Special Section on Consumer Electronics in the Era of the Internet of Everything (IoE) and Massive Data

Guest Editorial of the Special Section on Consumer Electronics in the Era of the Internet of Everything (IoE) and Massive Data

QuARCS: Quantum Anomaly Recognition and Caption Scoring Framework for Surveillance Videos

Multimodal Large Language Model-Based Fault Detection and Diagnosis in Context of Industry 4.0

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