Abstract
Electrically assisted bicycles (e-bikes or pedelecs) have recently become popular as a means of personal transportation, particularly in cities. Pedelecs allow people to combine their muscular strength in varying proportions with the assistance of an electric engine. One of the challenges here is to determine the cyclist preferences, capabilities, and the context situation around the e-bike and, based on these, to make recommendations to the cyclist and also to control the degree of electrical assistance provided. The Smart Space concept is used here for context formation. The concept involves creation of a real-time model of the physical space that aids decision making about electrical engine utilization for the particular situation and generates a recommendation for the cyclist. An ontology-based publish/subscribe mechanism is used for information sharing in Smart Space.
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Acknowledgments
The presented results are part of the research carried out within the project funded by grants ## 16-29-04349, 16-07-00462 of the Russian Foundation for Basic Research. The work was partially supported by Government of Russian Federation, Grant 08-08 and by SFI grant 16/IA/4610.
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Kashevnik, A. et al. (2018). Context-Based Cyclist Intelligent Support: An Approach to e-Bike Control Based on Smartphone Sensors. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2018 2018. Lecture Notes in Computer Science(), vol 11118. Springer, Cham. https://doi.org/10.1007/978-3-030-01168-0_2
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