AI Agent-Driven Intelligent Catalog Framework: A Governance-Centered Approach for Cleaning and Normalization of Heterogeneous Industrial Sensor Data
Abstract
sensor data, complicating data cleaning and normalization. Existing algorithmcentric
methods often treat quality issues in isolation and lack unified governance. This
paper proposes a governance-centered framework for multi-source industrial sensor data.
We introduce an Intelligent Catalog as the semantic governance layer to standardize metadata
and achieve semantic alignment before numerical processing. Building upon this,
an AI Agent-driven mechanism dynamically orchestrates cleaning and normalization
strategies based on real-time data status and heterogeneous features. This framework
modularly integrates classical algorithms (e.g., PCA, KPCA, LSTM) without model dependency.
Experimental results on public IIoT datasets demonstrate that our framework
significantly outperforms baseline methods in normalization consistency, noise robustness,
and stability across heterogeneous data. By shifting from an algorithm-centered to a
governance-centered paradigm, this approach provides a scalable and adaptive solution
for complex industrial sensor data management.
Share and Cite
Dong, H.; Zhang, Y.; Chu, Y.; Zhou, H.; Lu, M.; Zhou, Z.; Zhou, X. AI Agent-Driven Intelligent Catalog Framework: A Governance-Centered Approach for Cleaning and Normalization of Heterogeneous Industrial Sensor Data. Sensors 2026, 26, 3589. https://doi.org/10.3390/s26113589
Dong H, Zhang Y, Chu Y, Zhou H, Lu M, Zhou Z, Zhou X. AI Agent-Driven Intelligent Catalog Framework: A Governance-Centered Approach for Cleaning and Normalization of Heterogeneous Industrial Sensor Data. Sensors. 2026; 26(11):3589. https://doi.org/10.3390/s26113589
Chicago/Turabian StyleDong, Hongyi, Yimeng Zhang, Yifan Chu, Hailing Zhou, Mingxin Lu, Zuojian Zhou, and Xiaoyang Zhou. 2026. "AI Agent-Driven Intelligent Catalog Framework: A Governance-Centered Approach for Cleaning and Normalization of Heterogeneous Industrial Sensor Data" Sensors 26, no. 11: 3589. https://doi.org/10.3390/s26113589
APA StyleDong, H., Zhang, Y., Chu, Y., Zhou, H., Lu, M., Zhou, Z., & Zhou, X. (2026). AI Agent-Driven Intelligent Catalog Framework: A Governance-Centered Approach for Cleaning and Normalization of Heterogeneous Industrial Sensor Data. Sensors, 26(11), 3589. https://doi.org/10.3390/s26113589
