Open Theses

We are pleased that you are interested in a thesis at the Department of Computer Science with a focus on Embedded Systems. Please inform yourself in advance which topic is suitable for you. Afterwards, please make an appointment for the first meeting with the respective supervisor by e-mail.

The make  an appointment in advance is not only a sign of good organization, but also a matter of courtesy: as a rule, the supervisors are rather reluctant when you show up in the office unannounced.

Your first contact email should include:

  • A meaningful subject.
  • Your request (Bachelor thesis / master thesis).
  • How you have become aware of the topic and your motivation to edit the topic (just about 2-3 sentences).
  • The completed questionnaire for prospective students for theses.
  • The request for an appointment for a personal conversation.

Gladly seen but not obligatory:

  • Transcript of Records
  • Overview of past projects

 

 

Visualization of Biofeedback Data using a Smart-Watches

Supervisor:  Dr. Gerold Hölzl

Student: -

Biofeedback is an established technique to gain greater awareness of many psychological functions primarily using instruments that provide information on the activity of those same systems, with the goal of being able to manipulate them at will.

A current ongoing research project investigates in the question how a Smart-Watch based biofeedback training system using HR, HRV and a derived Stress Indicator can be used by people at home to achieve a noticeable, long-term benefit from the training.

The Goal of this thesis is to investigate in creative approaches to visually represent the measurements on the watch face to quickly inform the user but not people who may spy on the device.


The developed Concepts have to be implemented on an Android based Smartwatch and evaluated using the departments Biofeedback Framework in a pilot study.

Requirements: Successful candidates will have a strong background in computer science, mobile and embedded systems, or comparable study programmes, and a high interest in playing with sensor and web technology and knowledge in distributed client/server based systems.

Web Based Real Time Data Sampling (System Development)

Supervisor:  Dr. Gerold Hölzl

Student: -

The analysis and interpretation of heterogeneous sensor data by using mathematical, statistical and pattern classification methodologies is a late-breaking research topic.

The collection of the sensor data itself is the most time consuming part of the workflow. The data has to be recorded and must be labelled to be analysed afterwards.

Goal of this work is the development of a Web based Framework that enables users to independently collect sensor data, to record a synchronized video as ground-truth, to label the collected sensor data, and finally to send the data to a server for later analysis.

Requirements: Successful candidates will have a strong background in computer science, mobile and embedded systems, or comparable study programmes, and a high interest in playing with sensor and web technology and knowledge in distributed client/server based systems.

Real-time Industrial Information Source Map (System Development)

Supervisor: Dr. Gerold Hölzl

Student: -

Being on the edge of Industry 4.0 with its vision of computerized manufacturing, many companies face the problem of not knowing which digital information is present and collectable in their factories.

To support them in their transition process to smart manufacturing, a tool to build a virtual plan of the factory with annotated information in terms of the information that can be captured from the sketched devices is needed.

Goal of this work is to define a Framework to build a digital information map with the possibility of integrating real time captured data from the sketched smart machines.

Requirements: Students must be interested in APP development, visualization and abstraction of sensor data, and modelling machine parameters for rule based notifications.

NFC and Sensor Fusion for Indoor Positioning

Supervisor: Dr. Gerold Hölzl

Student: -

Indoor Positioning is still a crucial issue for the success of a lot of smart home systems und additionally in smart manufacturing processes. Based on the identified location of people in households, setups of devices like lightning, heating, etc. can be performed automatically by the system.

Industrial available systems (like UbiSense) are extremely expensive and the effort to install them makes them unusable for home appliance.

Most algorithms are based on using the received signal strength indicators as a measure for the position, so users have to build a map for locations they want to identify. This is a very time consuming process.

NFC (Near Field Communication) is a new technology and a set of protocols that enable electronic devices to establish radio communication with each other by touching the devices together, or bringing them into proximity to a distance.

The Idea of the project is to use NFC enabled devices to build up a smart indoor positioning systems that can detect relevant positions of people, act accordingly, and is easily extendable and adaptable to the used context.

The goal of this project is to:

  • evaluate pros/cons of using NFC as indoor positioning technology.
  • compare different NFC enabled technologies: beacons vs. smartphones vs. wrist-worn smartwatches.
  • investigate in the achievable accuracy and runtime with NFC as indoor positioning technology.
  • Estimate the effort to setup NFC enabled indoor positioning systems.
  • Develop a demonstration setup and framework as a proof of concept for using NFC enabled technology to infer users' location as input data for smart home appliances.

Requirements: Students must be interested in APP development, visualization and abstraction of sensor data, and modelling machine parameters for rule based notifications.