A fitness technology company partnered with a third-party hardware manufacturer to build a proprietary wearable exercise device, then needed an iOS app to pair with it. We built the BLE-connected application that turns accelerometer, gyroscope, and heart rate data into real-time feedback, personalized dashboards, and AI-driven workout recommendations.
Talk to Us About Your Wearable AppA fitness technology company building a proprietary wearable exercise device with a third-party hardware manufacturer
iOS application development, BLE connectivity, sensor data processing, and ML-driven workout recommendations
iOS, Bluetooth Low Energy, on-device sensor processing, machine learning
Delivered
The client did not provide platform metrics for this engagement, so results are described in capability terms rather than a count-up stat grid.
The custom hardware had no standard communication protocol to build against, so reliable connectivity had to be established before any app functionality could be layered on top.
The custom hardware required extensive R&D to establish BLE connectivity, a timeline made tighter by delays in receiving hardware from the client.
Biometric and motion data from accelerometers, gyroscopes, and heart rate monitors arrived in diverse, non-standard formats that had to be normalized before processing.
Raw sensor readings needed filtering and cross-validation to keep exercise metrics accurate across a range of movements.
The app had to support two hardware devices connected at once without disrupting data quality or transmission speed.
The build pairs mobile development with real-time sensor processing and on-device machine learning.
The app pairs with the wearable over BLE for fast connection and real-time data transmission between the device and the user's smartphone. Connectivity had to be built from the ground up against custom hardware with no standard protocol to reference.
Algorithms filter sensor noise and cross-validate readings across accelerometer, gyroscope, and heart rate inputs so exercise metrics stay accurate, even with diverse, non-standard data formats coming from the custom hardware.
Personalized dashboards, customizable widgets, and progress-tracking graphs give users a clear view of workout performance over time, replacing the feedback-free tracking the previous setup left them with.
Machine learning models analyze each user's past exercise data to generate personalized workout recommendations and goal-setting guidance, connecting raw sensor data to actionable next steps.
Talk to us about what a BLE-connected exercise tracking app looks like for your product.
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