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Article

Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study

1
Centre for Automation and Robotics (CSIC–UPM), Spanish National Research Council, Arganda del Rey, 28500 Madrid, Spain
2
Faculty of Production Engineering, Warsaw University of Technology, 02-524 Warsaw, Poland
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(19), 2252; https://doi.org/10.3390/rs11192252
Received: 26 July 2019 / Revised: 21 September 2019 / Accepted: 25 September 2019 / Published: 27 September 2019
(This article belongs to the Section Engineering Remote Sensing)
Nowadays, reliability of sensors is one of the most important challenges for widespread application of Internet-of-things data in key emerging fields such as the automotive and manufacturing sectors. This paper presents a brief review of the main research and innovation actions at the European level, as well as some on-going research related to sensor reliability in cyber-physical systems (CPS). The research reported in this paper is also focused on the design of a procedure for evaluating the reliability of Internet-of-Things sensors in a cyber-physical system. The results of a case study of sensor reliability assessment in an autonomous driving scenario for the automotive sector are also shown. A co-simulation framework is designed in order to enable real-time interaction between virtual and real sensors. The case study consists of an IoT LiDAR-based collaborative map in order to assess the CPS-based co-simulation framework. Specifically, the sensor chosen is the Ibeo Lux 4-layer LiDAR sensor with IoT added capabilities. The modeling library for predicting error with machine learning methods is implemented at a local level, and a self-learning-procedure for decision-making based on Q-learning runs at a global level. The study supporting the experimental evaluation of the co-simulation framework is presented using simulated and real data. The results demonstrate the effectiveness of the proposed method for increasing sensor reliability in cyber-physical systems using Internet-of-Things data. View Full-Text
Keywords: Cyber-Physical Systems; reliability assessment; Internet-of-Things; LiDAR sensor; driving assistance; obstacle recognition; reinforcement learning; Artificial Intelligence-based modelling Cyber-Physical Systems; reliability assessment; Internet-of-Things; LiDAR sensor; driving assistance; obstacle recognition; reinforcement learning; Artificial Intelligence-based modelling
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MDPI and ACS Style

Castaño, F.; Strzelczak, S.; Villalonga, A.; Haber, R.E.; Kossakowska, J. Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study. Remote Sens. 2019, 11, 2252. https://doi.org/10.3390/rs11192252

AMA Style

Castaño F, Strzelczak S, Villalonga A, Haber RE, Kossakowska J. Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study. Remote Sensing. 2019; 11(19):2252. https://doi.org/10.3390/rs11192252

Chicago/Turabian Style

Castaño, Fernando, Stanisław Strzelczak, Alberto Villalonga, Rodolfo E. Haber, and Joanna Kossakowska. 2019. "Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study" Remote Sensing 11, no. 19: 2252. https://doi.org/10.3390/rs11192252

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