activity
20152023
most citedThe Internet-of-Things Meets Business Process Management: A Manifesto

172 citations · 404 across the 23 of their papers we have counts for

collaborators
Showing 2020Show all

6 papers · 1 filter

cs.RO2020★ 17 cited

Robotic Process Automation -- A Systematic Literature Review and Assessment Framework

Judith Wewerka, Manfred Reichert

Robotic Process Automation (RPA) is the automation of rule-based routine processes to increase efficiency and to reduce costs. Due to the utmost importance of process automation in…

cs.DC2020★ 2 cited

Enacting Coordination Processes

Sebastian Steinau, Kevin Andrews, Manfred Reichert

With the rise of data-centric process management paradigms, interdependent processes, such as artifacts or object lifecycles, form a business process through their interactions. Co…

cs.RO2020★ 10 cited

A Fleet Learning Architecture for Enhanced Behavior Predictions during Challenging External Conditions

Florian Wirthmüller, Marvin Klimke, Julian Schlechtriemen +2

Already today, driver assistance systems help to make daily traffic more comfortable and safer. However, there are still situations that are quite rare but are hard to handle at th…

cs.LG2020★ 23 cited

CONDA-PM -- A Systematic Review and Framework for Concept Drift Analysis in Process Mining

Ghada Elkhawaga, Mervat Abuelkheir, Sherif I. Barakat +2

Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform…

cs.CV2020★ 18 cited

Towards Incorporating Contextual Knowledge into the Prediction of Driving Behavior

Florian Wirthmüller, Julian Schlechtriemen, Jochen Hipp +1

Predicting the behavior of surrounding traffic participants is crucial for advanced driver assistance systems and autonomous driving. Most researchers however do not consider conte…

cs.LG2020

Detecting Production Phases Based on Sensor Values using 1D-CNNs

Burkhard Hoppenstedt, Manfred Reichert, Ghada El-Khawaga +3

In the context of Industry 4.0, the knowledge extraction from sensor information plays an important role. Often, information gathered from sensor values reveals meaningful insights…