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Smart city article details
| Title | Wheelshare: Crowd-Sensed Surface Classification For Accessible Routing |
|---|---|
| ID_Doc | 61725 |
| Authors | Edinger J.; Hofmann A.; Wachner A.; Becker C.; Raychoudhury V.; Krupitzer C. |
| Year | 2019 |
| Published | 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019 |
| DOI | http://dx.doi.org/10.1109/PERCOMW.2019.8730849 |
| Abstract | Accessible path routing for wheeled mobility is an important problem given the permanent and temporary obstacles in the built environment. Existing research works have focused on identifying several obstacles as well as facilities such as crosswalks with traffic signals using smartphone based sensing or crowd-sourcing and used those knowledge to generate accessible routes. In this work, we propose WheelShare which generates an accessible route through the best possible surface depending on user and wheelchair requirements. It is 1) scalable, as it uses crowd-sensing to collect voluminous data, 2) dynamic, as the data gets constantly updated, and 3) objective, as it uses an empirical and data-centric approach. © 2019 IEEE. |
| Author Keywords | accessibility; accessible routing; machine learning; smart cities |
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