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Sensor faults detection and classification using SVM with diverse features (2017)
Presentation / Conference Contribution
Jan, S. U., & Koo, I. S. (2017, October). Sensor faults detection and classification using SVM with diverse features. Presented at 2017 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea

Sensors in industrial systems fault frequently leading to serious consequences regarding cost and safety. The authors propose support vector machine-based classifier with diverse time- and frequency-domain feature models to detect and classify these... Read More about Sensor faults detection and classification using SVM with diverse features.

Sensor Fault Classification Based on Support Vector Machine and Statistical Time-Domain Features (2017)
Journal Article
Jan, S. U., Lee, Y.-D., Shin, J., & Koo, I. (2017). Sensor Fault Classification Based on Support Vector Machine and Statistical Time-Domain Features. IEEE Access, 5, 8682-8690. https://doi.org/10.1109/access.2017.2705644

This paper deals with the problem of fault detection and diagnosis in sensors considering erratic, drift, hard-over, spike, and stuck faults. The data set containing samples of the above mentioned fault signals was acquired as follows: normal data si... Read More about Sensor Fault Classification Based on Support Vector Machine and Statistical Time-Domain Features.

Application of Navigating System based on Bluetooth Smart (2017)
Journal Article
Lee, Y., Jan, S. U., & Koo, I. (2017). Application of Navigating System based on Bluetooth Smart. Journal of the Institute of Internet, Broadcasting and Communication, 17(1), 69-76. https://doi.org/10.7236/jiibc.2017.17.1.69

Bluetooth Low Energy (BLE), also known as Bluetooth Smart, has ultra-low power consumption; in fact, BLE-enabled devices can run on a single coin cell battery for several years. In addition, BLE can estimate the approximate distance between two devi... Read More about Application of Navigating System based on Bluetooth Smart.