# Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study
## 2 Reliability of Sensors in Cyber-Physicals Systems. A Brief State-of-the-Art Review  
Reliability of sensors has become not only the main focus of on-going worldwide research, but also the priority of research and innovation actions (RIA) supported by Horizon 2020 Programme. For the sake of giving only a brief overview, Table 1 summarizes some of the most challenging projects targeting sensor reliability, funded mainly by Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking [25] in the last five years. It is clearly shown that the reliability of sensors and remote sensing systems is a key enabling step towards massive utilization of sensor networks in all application fields from manufacturing up to maritime and aeronautic applications. About twenty thousand scientific reports have considered reliability as the cornerstone of the main works [6; 37]. The assessment of the sensor's reliability in a classification problem based on the transferable belief model was presented in [38], whereas the Dempster-Shafer theory of belief functions was the foundation for a framework in another seminal paper [11]. The reliability of leap motion sensor in static and dynamic tracking was analyzed in [39], with not-very-promising expectations due to limited sensory space and inconsistent sampling frequency. Special attention has been received by wireless sensor networks, considering a measure of reliability using a probabilistic graph [40], packet delivery mechanism for guaranteeing quality of service [41] and adaptive and cross-layer framework for reliable and energy-efficient data collection [42]. Some methods for improving reliability in data transmission and localization by combining particle and finite impulse response filtering [43] and a new routing protocol [44] have recently been reported. The reader may find an interesting review of reliability assessment of wireless sensor network for industrial applications in [45]. Cyber-physical systems pose more scientific and technical challenges due to the need for conjunctive approaches for evaluating sensor reliability using Internet-of-Things data [46; 47]. A pioneering work suggested a method called Loss Inference based on Passive Measurement (LIPM) to \begin{table}
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**Horizon 2020 Initiative** & **Main Sensors** & **Application Field** & **Reference** \\ \hline RobustSENSE: Reliable, Secure, Trustable Sensors. For automated driving & Laser scanners, position, Virtual sensors & Automotive & [PERSON] et al. [26] \\  & Microphones, force, & & \\ IoSense: Flexible FE/BE Sensor Pilot Line & pressure, gas, camera, & Manufacturing, automotive, energy, & [PERSON] et al. [27] \\  & for the Internet of Everything & LiDAR, accelerometer, & & \\ SECREDAS: Cyber Security for Cross & Cameras, position, & & \\ Domain Reliable Dependable Automated Systems & ultrasounds, LiDAR, pressure & & \\ I-MECH: Intelligent Motion Control Platform for Smart Mechatronic Systems & Position, vision, force & & \\ PRYSTINE: Programmable Systems for Intelligence in Automobiles & Camera, LiDAR, & & \\ Power2 Power: Providing next-generation silicon-based power solutions in transport and machinery for significant & Temperature, PZT, radar, current, voltage, accelerometers & Manufacturing, energy, industrial machinery & [PERSON] et al. [33] \\  & decarbonisation in the next decade & & \\ NeXOS: Next Generation Web-Enabled Sensors for the Monitoring of a Changing Ocean & optics, passive acoustics sensors, detectors & & \\ ReMAP: Integrated Fleet Management solution aimed at replacing fixed-interval inspections with adaptive condition-based interventions & Piezo-electric, acoustic emission, optical-fibber & Aeronautic & [PERSON] et al. [36] \\ \hline \hline \end{tabular}
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Table 1: Research and innovation actions in sensor reliability supported by H2020 Programme in the last five years. compute the link loss performance in digital ecosystems with plenty of distributed data sensors [48].