ML-powered Performance Analytics Tennis App
Highlights
Refactoring wearable MVP app for fault-free data processing
Amplitude monitoring tool integration
Vitals data transfer from wearables to a mobile app
Companion mobile app for reporting
Germany
- 3 months
Turn the MVP into a feature-rich ML-powered system
After the MVP was developed, the customer started looking for a reliable partner to turn it into a comprehensive system. The main criterion imposed by the client was machine learning development proficiency as he was manually running a self-developed ML algorithm at that moment. The potential contractor was also to be well-versed in mobility solutions and backend development, as well as UI/UX design, and Symfa appeared to be a complete match.
Seamless data transfer for enhanced stats accuracy
There was no clearly defined list of features at the initial development stage, and the scope was iteratively clarified and refined during project execution.
Initially the application implied direct metadata transfer from watchOS to a data file, which resulted in a huge number of duplications. To fix the issue, we refactored the code and ensured clean and filtered data transfer to the phone.
Two standalone apps for data collection and visualization
Work Done
Requirements definition
User stories writing
Code review
Code refactoring
UI/UX design
Functional testing
Integration with Amplitude monitoring tool
WatchOS App Capabilities
Integration with iOS app
Metadata processing
Heart rate widget
iOS App Capabilities
Localization to English and German
Sign up/in page
Profile/home page
Match start page
Overview stats and match analytics with filters & swiping functionality
Social media stats sharing button
Technologies
Workout strategy definition through data analysis
The application visualizes gathered data, helps tennis coaches identify the athlete's weaker sides and fine-tune the workout strategy efficiently.
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