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Event Detection for Multivariate IIoT Sensor Data Streams (m/f/x)
Topic: "Event Detection for Multivariate IIoT Sensor Data Streams"
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With our headquarters in Dresden, we are strategically located in the largest center of microelectronic industries in Europe. As the capital of the German state of Saxony, Dresden is at the heart of “Silicon Saxony”, a term used to describe the region and its hundreds of microelectronics businesses.
Maintaining strong, collaborative relationships with local manufacturing companies and world-renowned universities (e.g. TU Dresden and HTW), Dresden is also the center of our R&D activities.
In addition to its high density of outstanding research institutions, Dresden is also well known for its history, beautiful baroque architecture, and broad collection of fine arts.
}', 21='{type=list, value=[{id=31544187646, name='MScha'}]}', 22='{type=number, value=1}', 24='{type=string, value=Unser Hauptsitz befindet sich in Dresden, der Hauptstadt des deutschen Bundeslandes Sachsen. Dresden ist das Herzstück von „Silicon Saxony“, Sachsens größtem Hightechnetzwerk und Europas größtem Mikroelektronikstandort.
Wir pflegen enge Kooperationsbeziehungen zu lokalen Fertigungsunternehmen und zu weltweit anerkannten Universitäten der Region (z. B. TU Dresden und HTW), wodurch Dresden das Zentrum unserer F&E-Aktivitäten ist.
Neben seiner hohen Dichte an herausragenden Forschungseinrichtungen ist Dresden auch für seine Geschichte, seine wunderschöne Barockarchitektur und seine große Sammlung an bildender Kunst bekannt.
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Deutsche Version verfügbar / German version available
The reliable detection of transitions between appliance states in multivariate sensor signals is fundamental to the adoption of Machine Learning methods in industrial IoT. As state transition detection allows a discretization of appliance states, it precedes downstream categorization and integration. Thus, the detection of these transition events is key towards improved manufacturing decision intelligence solutions.
During this internship, the student will assess and extract a suitable set of event detection methods to cover typical sensor readings in iIoT. Next, she will implement these methods within a real-time streaming architecture. Along with that, requirements for a user interface approach to select appropriate methods in a semi supervised way shall be addressed.
Technologies: SQL, timescaledb, R, python, azure.