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Date of Graduation

5-2026

Description

Personal fitness data is increasingly collected through mobile applications, yet most current systems store this information in centralized platforms that limit user control, long-term ownership, and data portability. This project addresses the question of whether a decentralized data model can be used to support everyday fitness tracking while preserving user autonomy and privacy. As individuals become more aware of how their health data is collected and shared, there is a growing need for systems that allow users to retain ownership of their personal information without sacrificing usability or functionality.This research presents SolidFit, an Android-based fitness tracking application designed around the Solid protocol and Personal Online Data Stores (Pods). SolidFit allows users to authenticate using a WebID and store workout records directly in their own decentralized storage rather than on a centralized server. The application supports creating, editing, viewing, and deleting workout entries, attaching images, and synchronizing data between local storage and the user’s Pod. The system integrates modern Android development tools, a secure authentication flow, and background data synchronization to ensure consistency across sessions and devices. Health-related inputs, such as heart rate and weight measurements, can also be recorded through supported system interfaces.The final system demonstrates that decentralized storage can be successfully integrated into a consumer-facing mobile application without significant usability tradeoffs. Testing shows that workout data is reliably created, synchronized, and retrieved from user-controlled storage, while maintaining offline functionality and graceful recovery when network access is unavailable. Media files associated with workouts are securely uploaded and retrieved as needed, and data conflicts between local and remote sources are resolved consistently.These results suggest that decentralized data architectures are a viable alternative for personal health applications. By giving users direct control over where and how their fitness data is stored, this approach reduces reliance on centralized platforms and lowers the risk of large-scale data misuse. Beyond fitness tracking, the methods demonstrated in this project can inform future research and development of privacy-preserving mobile applications in healthcare, wellness, and other domains where personal data sensitivity is high.

Publication Date

2026

Document Type

Book

Degree Name

Bachelor of Science in Computer Science

Degree Level

Undergraduate

Department

Electrical Engineering and Computer Science

Advisor/Mentor

Nelson, Alexander

Disciplines

Computer Sciences

Keywords

Health

SolidFit: A Decentralized Mobile Health-Tracking App Using Personal Online Data Stores (Pods)

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