README.md

AST-Monitor --- A wearable Raspberry Pi computer for cyclists

💻 Graphical User Interface • ⚙️ Hardware • 🖥️ Software • 📦 Installation • 📢 Deployment • 🚀 Examples • 🔑 License • 📄 Cite us • 📖 Further read • 🔗 Related packages • 📝 References • 🫂 Contributors

Welcome to AST-Monitor: Revolutionizing Sport Training Sessions! 🏋️‍♂️ This repository aims to introduce a low-cost, and efficient embedded device that can transform the way you monitor cycling training sessions. Allow us to present AST-Monitor.

To begin, we invite you to explore the paper that introduces the capabilities of AST-Monitor. Dive into the future of artificial sports trainers by reading this paper. 📄💡

• Free software: MIT license
• Python versions: 3.8.x, 3.9.x, 3.10.x, 3.11.x, 3.12.x
• Documentation: https://ast-monitor.readthedocs.io/en/latest
• Tested OS: Windows, Ubuntu, Fedora, Alpine, Arch, macOS. However, that does not mean it does not work on others

💻 Graphical User Interface

Basic data: Power at Your Fingertips 💪

The initial page of the AST-Monitor application presents essential parameters, providing real-time insights into an athlete's performance. Gain access to information such as the athlete's current speed and heart rate. After a training session, you'll also receive a comprehensive overview, including total distance covered, session duration, and total ascent conquered. 📱🚴‍♂️

Interactive map: Embark on a Visual Journey 🗺️🚀

As you navigate uncharted territories, this map reveals your precise location in real-time. And allows you to track your progress on the route in real time. 🌍🚴‍♂️🗺️

Interval training data: Unleash Your Inner Athlete 🏃‍♀️💪

Discover the duration of each phase, track your current heart rate, and marvel at the average heart rate achieved. But that's not all—brace yourself for the Digital Twin proposed heart rate and witness the thrilling difference between your current heart rate and the proposed target. Prepare to dominate your workouts with the AST-Monitor! 🏋️‍♀️

Interval training plan: Unleash the Potential 💯📝💥

Load up and embark on thrilling interval trainings that await you in the "AST-Monitor/development/trainings" folder. These trainings, meticulously crafted in the domain-specific language AST-TDL, are designed to take you to the next level. Once successfully loaded, witness the training plan come to life before your eyes. 🚀📋💥

⚙️ Hardware

Where Innovation Meets Performance ⚙️🔩💡

Prepare to be dazzled by the complete hardware setup featured in AST-Monitor.

Let's take a closer look at the components:

• A platform with fixing straps that securely attach to your bicycle, ensuring a seamless training experience. 🚲🔒
• The powerful Raspberry Pi 4 Model B micro-controller, powered by the dynamic Raspbian OS. 💻
• A five-inch LCD touchscreen display, allowing the interaction with AST-Monitor during the training. ✨🖥️
• Equipped with a USB ANT+ stick, AST-Monitor captures the heartbeat of your training, providing crucial data for your journey to greatness. 📡
• Adafruit's Ultimate GPS HAT module joins the lineup, empowering you with location information and paving the way for GPS integration (coming soon!). 🌐🛰️

But that's not all:

A Serial Peripheral Interface (SPI) protocol ensures seamless communication between the Raspberry Pi and the GPS peripheral, guaranteeing accurate and timely data. The screen display, connected using a physically shortened HDMI cable, ensures a sleek and compact design that doesn't compromise performance.

During the testing phase, the AST-Monitor prototype was powered by Trust's 5 VDC power bank, providing unparalleled endurance. While the current prototype may be a bit bulky, rest assured, our team is hard at work, exploring sleeker and more discreet solutions. 💪💦

For those who crave a glimpse inside AST-Monitor:

Welcome to the next stage of sports training. Welcome to AST-Monitor—your ultimate companion on the road to victory! 🌟🏆🚀

🖥️ Software

Dependencies 📦🔗

List of dependencies:

Package	Version	Platform
PyQt6	^5.15.6	All
matplotlib	^3.5.1	All
geopy	^2.2.0	All
openant	^1.2.0	All
pyqt-feedback-flow	^0.1.0	All
tcxreader	^0.4.1	All
sport-activities-features	^0.3.6	All

Additional note: adafruit-circuitpython-gps package must be installed in order to work with the GPS sensor:

$ pip install adafruit-circuitpython-gps

📦 Installation

Install AST-Monitor with pip:

$ pip install ast-monitor

In case you want to install directly from the source code, use:

$ git clone https://github.com/firefly-cpp/AST-Monitor.git
$ cd AST-Monitor
$ poetry build
$ python setup.py install

To install AST-Monitor on Fedora Linux, please use:

$ dnf install python3-ast-monitor

To install AST-Monitor on Alpine Linux, please use:

$ apk add py3-ast-monitor

To install AST-Monitor on Arch Linux, please use an AUR helper:

$ yay -Syyu python-ast-monitor

📢 Deployment

Our project was deployed on a Raspberry Pi device using Raspberry Pi OS.

The hardware configuration of AST-Monitor using Raspberry Pi OS is described in HARDWARE_CONFIGURATION.md.

🚀 Examples

Basic run

import os
import sys

from PyQt6 import QtWidgets

try:
    from ast_monitor.model import AST
except ModuleNotFoundError:
    sys.path.append('../')
    from ast_monitor.model import AST

# Paths to the files with heart rates and GPS data.
hr_data = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'sensor_data', 'hr.txt')
gps_data = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'sensor_data', 'gps.txt')
route_data = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'development', 'routes', 'route.json')

if __name__ == '__main__':
    app = QtWidgets.QApplication(sys.argv)
    window = AST(hr_data, gps_data, route_data)
    window.show()
    sys.exit(app.exec())

🔑 License

This package is distributed under the MIT License. This license can be found online at http://www.opensource.org/licenses/MIT.

Disclaimer

This framework is provided as-is, and there are no guarantees that it fits your purposes or that it is bug-free. Use it at your own risk!

📄 Cite us

Lukač, L., Fister Jr., I., Fister, I. "Digital Twin in Sport: From an Idea to Realization." Applied Sciences 12.24 (2022): 12741, DOI: 10.3390/app122412741.

📖 Further read

[1] Awesome Computational Intelligence in Sports

🔗 Related packages/frameworks

[1] sport-activities-features: A minimalistic toolbox for extracting features from sports activity files written in Python

[2] ast-tdl: Training Description Language for Artificial Sport Trainer

📝 References

Fister Jr, I., Fister, I., Iglesias, A., Galvez, A., Deb, S., & Fister, D. (2021). On deploying the Artificial Sport Trainer into practice. arXiv preprint arXiv:2109.13334.

Fister Jr, I., Salcedo-Sanz, S., Iglesias, A., Fister, D., Gálvez, A., & Fister, I. (2021). New Perspectives in the Development of the Artificial Sport Trainer. Applied Sciences, 11(23), 11452. DOI: 10.3390/app112311452

🫂 Contributors

Iztok Fister Jr. 🐛 📖 💻 🚧 🧑‍🏫 📦	luckyLukac 🐛 📖 💻 🎨	Oromion 📦	alenrajsp 🖋 💻 🚧 🐛	Tatookie 📖 🐛	rhododendrom 🎨	Sertonix 🐛
Tadej Lahovnik 📖 💻 🐛