The MiStepCount App is designed to provide accurate step tracking through the use of advanced algorithms and machine learning. Here’s a breakdown of the key features and technologies:
C++ Signal Processing: Developed robust algorithms to analyze accelerometer data, improving step detection accuracy.
TensorFlow Lite Integration: Used machine learning to reduce false step counts by 40%, enhancing the app’s precision.
False Positive Reduction: Optimized the system to significantly lower false positives compared to other pedometer apps, ensuring a more reliable user experience.
This app showcases an effective combination of C++ and TensorFlow Lite to achieve superior performance in step tracking.
