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Code and data related to the research on how to give personalized real-time feedback to amateur cyclists on low-end devices, using Semantic Web technologies.

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Personalized real-time feedback for amateur cyclists on low-end devices

This repository contains code and data related to the research on how to give personalized real-time feedback to amateur cyclists on low-end devices, using Semantic Web technologies. This research is executed at the IDLab research group, by people from Ghent Universityimec.

Contents

The contents of this repository are related to two research publications.

Personalized real-time monitoring of amateur cyclists on low-end devices: proof-of-concept & performance evaluation (2018)

This paper has been presented in April 2018 at the Web Stream Processing workshop at The Web Conference 2018 and is available via this link. The paper presents a first proof-of-concept (PoC) of a system providing real-time personalized feedback to amateur cyclists using a Raspberry Pi. In this PoC, real-time feedback about the user's heart rate and heart rate training zones is given through a web application. The performance & scalability of this platform are evaluated on the Raspberry Pi.

The code and data related to the proof-of-concept and performance evaluation, are available in the poc-&-performance-evaluation folder.

Personalized real-time cycling feedback during amateur training: a virtual training demo (2019)

This paper has been accepted to the demo track of the Extended Semantic Web Conference (ESWC) 2019. This paper specifically focuses on the use case of an individual amateur cyclist that executes a training. The paper presents an architecture of a solution providing feedback to such a cyclists (based on the PoC presented in the previous publication), and demonstrates this solution with a tablet demo that allows a user to execute a virtual amateur cycling training.

The online demo page is available on this link. The demo data (cycling ontology, context data, C-SPARQL queries) is available in the virtual-training-app-demo folder.

CONAMO project

This research is largely conducted as a part of the imec ICON project CONAMO (CONtinuous Athlete MOnitoring). CONAMO is funded by imec, VLAIO, Rombit, Energy Lab and VRT.

Contact

The main contact person directly involved with this research is Mathias De Brouwer. In case of any remarks or questions, you can send an email to [email protected] or create a GitHub issue.

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Code and data related to the research on how to give personalized real-time feedback to amateur cyclists on low-end devices, using Semantic Web technologies.

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