SmartWatch Activity Simulator 🕰️

Hello and welcome to the SmartWatch Activity Simulator! This fun little test project simulates the data generation of a smartwatch's accelerometer and gyroscope. But that's not all; it also predicts human activity based on this data!

How it works:

1. SmartWatchSimulator.py: This file contains a class Smartwatch which can generate random accelerometer and gyroscope data, simulating the kind of data a real smartwatch might capture.

2. App.py: This is where the action happens! It uses the Smartwatch class to generate data and then predicts the activity using a simple heuristic. The results are printed out for you to see.

How to use:

1. Run the App.py script.
2. Watch the console! You'll see generated data from the smartwatch's sensors and then a prediction of the human activity based on that data.
3. It will keep running, generating a new prediction every second. If you want to stop, simply press CTRL + C or close the console.

Future Directions:

🚀 Machine Learning Integration: Instead of using simple heuristics, we can integrate a machine learning model to predict activities based on the data for even more accurate predictions!

🎨 GUI Implementation: A simple graphical user interface could be added to visualize the data and predictions in a more user-friendly manner.

🌍 Additional Sensors: We can simulate other sensors such as heart rate monitors or GPS to generate even richer datasets.

🕵️ Anomaly Detection: Beyond just predicting activities, we can detect unusual patterns in the data, potentially useful for health monitoring or fall detection.

Conclusion:

This project is ideal for anyone new to programming and wanting a sneak peek into how smartwatch data works or for those wanting to experiment with their own activity prediction algorithms.

Happy Coding! 🚀👩‍💻👨‍💻🎉