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Process-Driven and Flow-Based Processing of Industrial Sensor Data

Kammerer, Klaus and Pryss, Rüdiger and Hoppenstedt, Burkhard and Sommer, Kevin and Reichert, Manfred (2020) Process-Driven and Flow-Based Processing of Industrial Sensor Data. Sensors, 20 (18). ISSN 1424-8220

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Official URL: https://www.mdpi.com/1424-8220/20/18/5245

Abstract

For machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, their integration into complex machines is promising for developing digital services for various scenarios. It is apparent that for components handling recorded data of these sensors they must usually deal with large amounts of data. In particular, the labeling of raw sensor data must be furthered by a technical solution. To deal with these data handling challenges in a generic way, a sensor processing pipeline (SPP) was developed, which provides effective methods to capture, process, store, and visualize raw sensor data based on a processing chain. Based on the example of a machine manufacturing company, the SPP approach is presented in this work. For the company involved, the approach has revealed promising results.

Item Type:Article
Subjects:DBIS Research > Publications
ID Code:1952
Deposited By: Klaus Kammerer
BibTex Export:BibTeX
Deposited On:28 Sep 2020 14:13
Last Modified:28 Sep 2020 14:13

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