Bike monitoring

Introduction

We developed this project with the aim of establishing communication between sensors and a server using LoRa (Long Range) technology. Given this challenge, we decided to design a bike monitoring system using a stationary bike as the core element. We chose this project because the 2024 Paris Olympics generated significant interest in sports and fitness, making it a timely and relevant topic.

This project was carried out as part of our fourth-year engineering studies at UniLaSalle, a engineering school specializing in environmental sciences, digital technologies, and sustainable development. As students in this academic program, we had the opportunity to apply our knowledge in embedded systems, IoT communication, and data processing to develop a concrete and innovative solution. This project not only allowed us to deepen our technical skills but also to work in a structured engineering approach, from concept development to implementation and testing. You can find more informations on UniLaSalle on this website: http://www.unilasalle-amiens.fr/.

System Overview

This system utilizes various sensors to monitor key metrics, such as heart rate (bpm), body temperature, and the user’s speed. To measure the speed, we employed magnets to create a makeshift "tour counter." These sensor data are transmitted via the Sodaq board to our Ktor server, where they are stored in a database, with each data point being associated with a specific user. To enable users to track their progress, an application is available that communicates with the server to provide a visual representation of their data.

For a detailed overview of the project's functionality, you can watch the promotional video below.

Sensors

The data collection and communication are handled by two boards. The first, the Arduino Leonardo, is responsible for acquiring measurements such as heart rate (bpm), body temperature, and bike speed. These readings are displayed on an LCD screen and then transmitted to the Sodaq board, which sends the data via LoRa to the server using The Things Network.

Software

For the server-side and mobile application, we chose Kotlin as the development language. The application is designed to be compatible with both iOS and Android, ensuring broad accessibility for users. Upon accessing the app, users must either create a new account or log in to an existing one. Once logged in, data tracking is fully automated, offering a seamless experience.

For a detailed overview of the app's functionality, you can visit our GitHub repository for the source code.

Future Enhancements

This project has a wide range of potential areas for evolution. One primary area for improvement is enabling users to send customized workout programs from the app to the bike via LoRa. Additionally, the app could be extended to support other sports, such as running or swimming, providing even more versatility. The possibilities are vast, and we encourage further exploration and innovation.

Acknowledgments

We would like to express our gratitude to UniLaSalle Amiens for providing the opportunity to work on such exciting projects and apply the knowledge gained during our studies. We also wish to thank Mr. DAILLY, Mr. LETOCART, and Mr. Caron for their invaluable guidance and support throughout the duration of this project.

Video