OccuSpace: Towards a Robust Occupancy Prediction System for Activity Based Workplace. Rahaman, M. S., Pare, H., Liono, J., Salim, F. D., Ren, Y., Chan, J., Kudo, S., Rawling, T., & Sinickas, A. In IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019, Kyoto, Japan, March 11-15, 2019, pages 415–418, 2019. IEEE.
OccuSpace: Towards a Robust Occupancy Prediction System for Activity Based Workplace [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/percom/RahamanPLSRCKRS19,
  author    = {Mohammad Saiedur Rahaman and
               Harsh Pare and
               Jonathan Liono and
               Flora D. Salim and
               Yongli Ren and
               Jeffrey Chan and
               Shaw Kudo and
               Tim Rawling and
               Alex Sinickas},
  title     = {OccuSpace: Towards a Robust Occupancy Prediction System for Activity
               Based Workplace},
  booktitle = {{IEEE} International Conference on Pervasive Computing and Communications
               Workshops, PerCom Workshops 2019, Kyoto, Japan, March 11-15, 2019},
  pages     = {415--418},
  publisher = {{IEEE}},
  year      = {2019},
  url       = {https://doi.org/10.1109/PERCOMW.2019.8730762},
  doi       = {10.1109/PERCOMW.2019.8730762},
  timestamp = {Fri, 27 Dec 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/conf/percom/RahamanPLSRCKRS19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

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