Project Overview: Fitness Tracker Using MATLAB
This project aims to design a basic fitness tracker system using MATLAB to simulate, process, and analyze user activity data. The system collects simulated sensor inputs such as accelerometer readings (X, Y, Z axes), GPS location (latitude and longitude), and speed. These data are organized into a structured table for easy processing.
The raw data undergoes a preprocessing stage that includes removing invalid entries (like NaN values or negative speeds), normalizing and smoothing accelerometer signals, and scaling the speed values to a standard range. After cleaning, the program calculates two key fitness features: the total distance traveled using the Haversine formula and the total number of steps taken by analyzing acceleration magnitude.
To add intelligence, the system also includes a simple linear regression model that predicts future steps based on historical step data. This predictive feature demonstrates the potential for adding AI-based components to enhance the tracker’s usefulness for long-term activity monitoring.
Overall, this project simulates a simplified but functional fitness tracking application that can be expanded with real sensor data or integrated into wearable devices for practical use.
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