HIGHLIGHTS
- who: October and colleagues from the University at Buffalo, United States have published the paper: Editorial: Data sciences in transportation and transit systems, in the Journal: (JOURNAL)
- what: The study proposes the use of smart phones as crowdsourcing sensors (Azzoug and Kaewunruen, 2017). This study has clearly demonstrated the robustness of the machine_learning model for applications to both surface and underground trains.
- how: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
- future . . .
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