392243 Embedded Machine-Learning (EML) (Pj) (SoSe 2024)

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This project is given in English and German.

This project is about realization of machine-learning methods in resource limited systems like IoT devices or the robot platform AMiRo. While heavy processing of such algorithms is often done externally, the method developed in this project shall be autonomous and self-sufficient. As a result, concepts must not only take quality into account, but also efficiency and feasibility with respect to the target platform.
Concrete tasks would be:
- Finding suitable methods in relation to the requirements of the target platform
- Programming of these methods in C
- Method evaluation

In diesem Projekt sollen Verfahren des Maschinellen Lernens auf ressourcenbeschränkten Systemen, wie z.B. IoT-Geräten oder dem Miniroboter AMiRo, umgesetzt werden. Während die damit verbundenen Berechnungen oftmals auf externe Dienste ausgelagert werden, soll das im Rahmen dieses Projekts entwickelte Verfahren eigenständig und unabhängig sein. Daher sind bei der Entwicklung nicht nur Qualität, sondern auch Effizienz und Umsetzbarkeit auf der Zielplattform wichtige Anforderungen.
Konkrete Aufgabenstellungen wären:
- Finden geeigneter Verfahren in Bezug auf die Anforderungen der Zielplattform
- Programmierung dieser Verfahren in C
- Evaluierung der Verfahren

Requirements for participation, required level

Teilnahmevoraussetzungen, notwendige Vorkenntnisse:
Knowledge/skills in machine-learning, C programming, robotics and software development in microcontrollers are beneficial.
Kentnisse in Machine-Learning, C-Programmierung, Robotik, und Softwareentwicklung auf Mikrocontrollern sind von Vorteil.

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  
by appointment n. V.   08.04.-19.07.2024

Subject assignments

Module Course Requirements  
39-M-Inf-P Projekt Projekt Ungraded examination
Student information
39-M-Inf-P1_NWI Projekt 1 Projekt 1 Ungraded examination
Student information
FH-BMPro-2043 Projekt Biomechatronik Projekt BioMechatronik Graded examination
Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.


On 16.10., the possible project topics for this semester will be distributed.
After that, you can contact the respective contact persons directly.

E-Learning Space

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Registered number: 0
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Address:
SS2024_392243@ekvv.uni-bielefeld.de
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If the reference number is used for several courses in the course of the semester, use the following alternative address to reach the participants of exactly this: VST_466955138@ekvv.uni-bielefeld.de
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Last update basic details/teaching staff:
Wednesday, April 10, 2024 
Last update times:
Wednesday, March 27, 2024 
Last update rooms:
Wednesday, March 27, 2024 
Type(s) / SWS (hours per week per semester)
Pj / 4
Department
Faculty of Technology
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466955138