@inproceedings{baig-etal-2022-drivingbeacon,
    title = "{D}riving{B}eacon: Driving Behaviour Change Support System Considering Mobile Use and Geo-information",
    author = "Baig, Jawwad  and
      Chen, Guanyi  and
      Lin, Chenghua  and
      Reiter, Ehud",
    editor = "Krahmer, Emiel  and
      McCoy, Kathy  and
      Reiter, Ehud",
    booktitle = "Proceedings of the First Workshop on Natural Language Generation in Healthcare",
    month = jul,
    year = "2022",
    address = "Waterville, Maine, USA and virtual meeting",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.nlg4health-1.1",
    pages = "1--8",
    abstract = "Natural Language Generation has been proved to be effective and efficient in constructing health behaviour change support systems. We are working on DrivingBeacon, a behaviour change support system that uses telematics data from mobile phone sensors to generate weekly data-to-text feedback reports to vehicle drivers. The system makes use of a wealth of information such as mobile phone use while driving, geo-information, speeding, rush hour driving to generate the feedback. We present results from a real-world evaluation where 8 drivers in UK used DrivingBeacon for 4 weeks. Results are promising but not conclusive.",
}