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Master Thesis: Design and development of a privacy - aware and usable smartphone app for managing personal sensor data


Design and development of a privacy - aware and usable smartphone app for managing personal sensor data


Sales and the use of (consumer) wearables and fitness trackers are steadily increasing and vendors and platform operators are continuously offering new sensors and algorithms for determining meaningful activity data. While platforms and smartphone apps owned by vendors are often well integrated and feature-rich, there are specific concerns about the security,
protection, and use of sensitive health data. Based on the use case of a check-up during marathon preparation, a smartphone app is developed in this work, which displays the recorded activities of the user and visualizes them accordingly, but in which the user still retains control over the data. Activities should be securely shareable with third parties, such as sports physicians. Therefore, initially the requirements are determined, focusing on data protection and usability. Based on this, the React Native-based Android app is implemented, which is designed modularly to support devices from several manufacturers in the future. In addition, it is connected to an encryption platform (ENtRANCe) to securely share activity data. The evaluation is done using a Pluralistic Usability Walkthrough to ensure the app’s usability. In addition, the code quality shall be ensured in order to enable further development, extensibility, and maintainability of the application. The result consists of a structured, documented, extensible prototype with a good usability and all identified key requirements. Unimplemented requirements are limited to the integration of weather data and the input of manual health data for use in advanced calculations. An application following the targeted use case (data transmission to sports physician) is currently not possible for all recorded data due to the lack of accuracy of certain sensors. However, the prototype can be used already today for a target audience of privacy-aware users of fitness trackers.

Supervisor: Dirk Thatmann

Type:  Master Thesis

Duration: 6 months

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