Advanced search
2 files | 1.48 MB Add to list

Demonstration of a stream reasoning platform on low-end devices to enable personalized real-time cycling feedback

Mathias De Brouwer (UGent) , Femke Ongenae (UGent) and Filip De Turck (UGent)
Author
Organization
Abstract
During amateur cycling training, analyzing sensor data in real-time would allow riders to receive immediate feedback on how they are performing, and adapt their training accordingly. In this paper, a solution with Semantic Web technologies is presented that gives such real-time personalized feedback, by integrating the data streams with domain knowledge, rider profiles {\&} other context data. This solution consists of a stream reasoning engine running on a low-end Raspberry Pi device, and a tablet app showing feedback based on the continuous query results. To demonstrate this in a static environment, a virtual training app is presented, allowing a user to simulate an amateur cycling training.
Keywords
Stream reasoning, Low-end devices, Real-time feedback, Personalization, Cycling

Downloads

  • 7558 i.pdf
    • full text (Accepted manuscript)
    • |
    • open access
    • |
    • PDF
    • |
    • 494.04 KB
  • (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 984.16 KB

Citation

Please use this url to cite or link to this publication:

MLA
De Brouwer, Mathias, et al. “Demonstration of a Stream Reasoning Platform on Low-End Devices to Enable Personalized Real-Time Cycling Feedback.” SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS, edited by Pascal Hitzler et al., vol. 11762, Springer, 2019, pp. 28–32, doi:10.1007/978-3-030-32327-1_6.
APA
De Brouwer, M., Ongenae, F., & De Turck, F. (2019). Demonstration of a stream reasoning platform on low-end devices to enable personalized real-time cycling feedback. In P. Hitzler, S. Kirrane, O. Hartig, V. de Boer, M.-E. Vidal, M. Maleshkova, … R. Verborgh (Eds.), SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS (Vol. 11762, pp. 28–32). Portoroz, Slovenia: Springer. https://doi.org/10.1007/978-3-030-32327-1_6
Chicago author-date
De Brouwer, Mathias, Femke Ongenae, and Filip De Turck. 2019. “Demonstration of a Stream Reasoning Platform on Low-End Devices to Enable Personalized Real-Time Cycling Feedback.” In SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS, edited by Pascal Hitzler, Sabrina Kirrane, Olaf Hartig, Victor de Boer, Maria-Esther Vidal, Maria Maleshkova, Stefan Schlobach, et al., 11762:28–32. Springer. https://doi.org/10.1007/978-3-030-32327-1_6.
Chicago author-date (all authors)
De Brouwer, Mathias, Femke Ongenae, and Filip De Turck. 2019. “Demonstration of a Stream Reasoning Platform on Low-End Devices to Enable Personalized Real-Time Cycling Feedback.” In SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS, ed by. Pascal Hitzler, Sabrina Kirrane, Olaf Hartig, Victor de Boer, Maria-Esther Vidal, Maria Maleshkova, Stefan Schlobach, Karl Hammar, Nelia Lasierra, Steffen Stadtmüller, Katja Hose, and Ruben Verborgh, 11762:28–32. Springer. doi:10.1007/978-3-030-32327-1_6.
Vancouver
1.
De Brouwer M, Ongenae F, De Turck F. Demonstration of a stream reasoning platform on low-end devices to enable personalized real-time cycling feedback. In: Hitzler P, Kirrane S, Hartig O, de Boer V, Vidal M-E, Maleshkova M, et al., editors. SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS. Springer; 2019. p. 28–32.
IEEE
[1]
M. De Brouwer, F. Ongenae, and F. De Turck, “Demonstration of a stream reasoning platform on low-end devices to enable personalized real-time cycling feedback,” in SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS, Portoroz, Slovenia, 2019, vol. 11762, pp. 28–32.
@inproceedings{8632572,
  abstract     = {During amateur cycling training, analyzing sensor data in real-time would allow riders to receive immediate feedback on how they are performing, and adapt their training accordingly. In this paper, a solution with Semantic Web technologies is presented that gives such real-time personalized feedback, by integrating the data streams with domain knowledge, rider profiles {\&} other context data. This solution consists of a stream reasoning engine running on a low-end Raspberry Pi device, and a tablet app showing feedback based on the continuous query results. To demonstrate this in a static environment, a virtual training app is presented, allowing a user to simulate an amateur cycling training.},
  author       = {De Brouwer, Mathias and Ongenae, Femke and De Turck, Filip},
  booktitle    = {SEMANTIC WEB: ESWC 2019 SATELLITE EVENTS},
  editor       = {Hitzler, Pascal and Kirrane, Sabrina and Hartig, Olaf and de Boer, Victor and Vidal, Maria-Esther and Maleshkova, Maria and Schlobach, Stefan and Hammar, Karl and Lasierra, Nelia and Stadtmüller, Steffen and Hose, Katja and Verborgh, Ruben},
  isbn         = {9783030323264},
  issn         = {0302-9743},
  keywords     = {Stream reasoning,Low-end devices,Real-time feedback,Personalization,Cycling},
  language     = {eng},
  location     = {Portoroz, Slovenia},
  pages        = {28--32},
  publisher    = {Springer},
  title        = {Demonstration of a stream reasoning platform on low-end devices to enable personalized real-time cycling feedback},
  url          = {http://dx.doi.org/10.1007/978-3-030-32327-1_6},
  volume       = {11762},
  year         = {2019},
}

Altmetric
View in Altmetric
Web of Science
Times cited: