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Data and Process Science

Data and Process Science

Der Forschungsbereich Data and Process Science beschäftigt sich mit Zukunftsthemen in den Bereichen der Digitalisierung und der Zukunft der Arbeit inklusive Projekt- und Entwicklungsmanagement. Aber auch die Themenfelder der künstlichen Intelligenz, das maschinelle Lernen, Internet of Things (IoT), Data Mining sowie Predictive Statistics spielen eine große Rolle.

Publikationen

Philipp Niklas Rosenthal, Makki Ben Salem, Prof. Dr. Abdelmajid Khelil

Qualitative Comparison of Tools for Handling Unstructured IIoT Data

The Stuttgart Conference on Automotive Production (SCAP)

Prof. Dr. Maren Martens, Elisabeth Scheuchenpflug

A new trend in further education? The involvement of small and medium-sized enterprises in micro degrees on digitalization and sustainability

Research Notes on Data and Process Science

Ahmed Chebaane, Muhammad Kamran Arshad, Florian Burger, Prof. Dr. Abdelmajid Khelil

A Layered Strategy for Reducing Offloading Latency in Fog Computing

In Proc. of The 10th International Workshop on Internet of Things: Networking Applications and Technologies (IoTNAT)

Ahmed Chebaane, Makki Ben Salem, Bchira Ben Mabrouk, Prof. Dr. Abdelmajid Khelil

Effective Timing for Reserving Fog Computational Resources for Time-Sensitive Vehicular Applications

In Proc. of The 9th IEEE International Conference on Fog and Mobile Edge Computing (FMEC), 2024

Anna Schidek, Claudia Doering, Prof. Dr. Holger Timinger

Empirical Study on Data-based Tailoring in Project Management

33th IAMOT (International Association for Management of Technology), Porto, Portugal, 2024

Anna Schidek, Matthias Vieth, Harald Wehnes, Prof. Dr. Holger Timinger

Evaluation of a cross-university certification system in project management

33th IAMOT (International Association for Management of Technology), Porto, Portugal, 2024.

Makki Ben Salem, Abdalla Sino, Prof. Dr. Abdelmajid Khelil

Rule-based Automated Waste Detection for Industry 4.0

The 7th European Conference on Industrial Engineering and Operations Management (IEOM)

Verena Starflinger, Prof. Dr. Maren Martens

Best Practices of Circular Business Models – Benefits and Challenges (not only) for German Start-ups

Research Notes on Data and Process Science

Ulrich Ludolfinger, Prof. Dr. Maren Martens

An Autonomous Energy Management Concept for Sustainable Smart Cities

2023 IEEE European Technology and Engineering Management Summit (E-TEMS). Conference Proceedings.

Dominic Scholze, Abdullah Al-Khatib, Prof. Dr. Abdelmajid Khelil

Sensing Quality Driven Positioning and Orientation for LiDAR Sensors

2023 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)

Alle Publikationen

Mitglieder des Forschungsbereichs Data and Process Science