Xin, X., Keoh, S. L. , Sevegnani, M. and Saerbeck, M. (2020) Dynamic Probabilistic Model Checking for Sensor Validation in Industry 4.0 Applications. In: IEEE International Conference on Smart Internet of Things (IEEE SmartIoT 2020), Beijing, China, 14-16 Aug 2020, ISBN 9781728165158 (doi: 10.1109/SmartIoT49966.2020.00016)
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218761.pdf - Accepted Version 9MB |
Abstract
Industry 4.0 adopts Internet of Things (IoT) and service-oriented architectures to integrate Cyber-Physical Systems and Enterprise Planning into manufacturing operations. This kind of integration consists of a combination of connected sensors and run-time control algorithms. Consequential control decisions are driven by sensor-generated data. Hence, the trustworthiness of the sensor network readings is increasingly crucial to guarantee the performance and the quality of a manufacturing task. However, existing methodologies to test such systems often do not scale to the complexity and dynamic nature of today’s sensor networks. This paper proposes a novel run-time verification framework combining sensor-level fault detection and system-level probabilistic model checking. This framework can rigorously quantify the trustworthiness of sensor readings, hence enabling formal reasoning for system failure prediction. We evaluated our approach on an industrial turn-mill machine equipped with a sensor network to monitor its main components continuously. The results indicate that the proposed verification framework involving the quantified sensor’s trustworthiness enhances the accuracy of the system failure prediction.
| Item Type: | Conference Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Keoh, Dr Sye Loong and Sevegnani, Dr Michele |
| Authors: | Xin, X., Keoh, S. L., Sevegnani, M., and Saerbeck, M. |
| College/School: | College of Science and Engineering > School of Computing Science |
| ISBN: | 9781728165158 |
| Copyright Holders: | Copyright © IEEE |
| First Published: | First published in Proceedings of 2020 IEEE International Conference on Smart Internet of Things (SmartIoT) |
| Publisher Policy: | Reproduced according to the copyright policy of the publisher |
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