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Data visualisation: Cooperation Infrastructures


Marios Mouratidis

Raum: US-D 105
Telefon: +49 271 740-4535

Mobile: 0176 64130013


Short Description

Industry 4.0 is on everyone’s lips, many are talking about the advantages of digitalization. In the context of distributed labs and work places, the question arises how collaboration between interdisciplinary people and machines can be supported. Which data needs to be collected and evaluated? What are the concrete requirements of users? Can maintenance be automated? How can interdisciplinary communication be fostered? How can collaboration be enabled?

Core activities might involve either a technical or research focus:

Programming in Python (Django), C, front-end development, IoT, HTML5/CSS/JS, MqTT, Zigbee. Hacking a Prusa MK3S 3D printer.

An ethnographic and participatory research approach can be applied in order to find design implications and conceptualize a system.

#python #arduino #iot #3d-printing #cswc #participatory-design #ethnography #opendash #industry40 #octoprint


The team will work closely with the supervisor. Regular meetings to track progress and especially tackle issues will need to be scheduled. At the end of the project a project report (including a guide on how to use the system) and possible source code, assets need to be handed in. Collaboration with other project teams might serve helpful.


  • 1. Clarify student idea and the concrete outcome based on student expertise (mock-up and/or programming implementation)
  • 2. Workplan/Milestone planning
  • 3. Iterative design
  • 4. Continuous feedback from the supervisor
  • 5. Submission project report


This project can be adjusted to fit option A, B, or C depending on the level of difficulty and specific interest of the student(s). This project can start as Project A and be continued as B, C and also lead to a Master Thesis.