The Titan Control Center for Industrial DevOps analytics research
The Titan Control Center for Industrial DevOps analytics research
The Titan Control Center is a software platform supporting research on industrial big data analytics. Building upon a scalable and extensible architecture, the Titan Control Center analyzes and visualizes data streams from Internet of Things sensors in industrial production. It performs different types of aggregations, correlation, forecasting, and anomaly detection to provide deeper insights into industrial production data for enabling Industrial DevOps. Furthermore, the Titan Control Center is used in research for implementing and evaluating novel approaches on multi-dimensional sensor data stream aggregation, as a reference platform for benchmarking scalability in modular analytics software, and for research on analyzing industrial energy consumption.
Big data, Extensibility, Industrial DevOps, Internet of Things, Scalability, Stream analytics
Henning, Sören
e09ef4ea-8a2f-4d11-903b-db51d6371fcb
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
1 February 2021
Henning, Sören
e09ef4ea-8a2f-4d11-903b-db51d6371fcb
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Henning, Sören and Hasselbring, Wilhelm
(2021)
The Titan Control Center for Industrial DevOps analytics research.
Software Impacts, 7, [100050].
(doi:10.1016/j.simpa.2020.100050).
Abstract
The Titan Control Center is a software platform supporting research on industrial big data analytics. Building upon a scalable and extensible architecture, the Titan Control Center analyzes and visualizes data streams from Internet of Things sensors in industrial production. It performs different types of aggregations, correlation, forecasting, and anomaly detection to provide deeper insights into industrial production data for enabling Industrial DevOps. Furthermore, the Titan Control Center is used in research for implementing and evaluating novel approaches on multi-dimensional sensor data stream aggregation, as a reference platform for benchmarking scalability in modular analytics software, and for research on analyzing industrial energy consumption.
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Published date: 1 February 2021
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© 2020 The Author(s)
Keywords:
Big data, Extensibility, Industrial DevOps, Internet of Things, Scalability, Stream analytics
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Local EPrints ID: 488883
URI: http://eprints.soton.ac.uk/id/eprint/488883
PURE UUID: 813a3d10-ded2-4766-b48b-8be94ab5d12c
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Date deposited: 09 Apr 2024 10:03
Last modified: 10 Apr 2024 02:15
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Author:
Sören Henning
Author:
Wilhelm Hasselbring
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