Abstract
Understanding the movement of people constrained by process is of practical importance. It may enable process improvements and more accurate provision of space in buildings (such as hospitals, laboratories and airports) and thus contribute to making safer and more efficient built environments. We present an empirical study of the movement of nurses working at a neonatal intensive care unit (NICU) within a UK hospital. The aim of this study is to model the mobility of individuals within a process constrained built environment. Our objective is to create a model that recreates room occupancy distributions – this implies that we require a room transition model that predicts a person’s next destination as well as a dwell time model that predicts how long a person will stay in a room. This class of situation is of theoretical and practical significance because nurses’ movements are driven by sequences of purposeful activity that are spatially, logically and temporally constrained i.e. process constrained. We used Ekahau Wi-Fi location tracking tags to collect room transitions of 10 day-shift nurses within a NICU for a period of 28 days. We use this dataset to evaluate four proposed models of room transition: (1) random model; (2) an occupancy and distance model; (3) an attractiveness model; (4) a Markov model. We evaluate the models’ goodness-of-fit by comparing our empirical dataset with model predictions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
C. Bishop, Pattern Recognition and Machine Learning (Springer, New York, 2006)
A. Johansson, D. Helbing, Analysis of empirical trajectory data of pedestrians, in Pedestrian and Evacuation Dynamics 2008, ed. by W.W.F. Klingsch, C. Rogsch, A. Schadschneider, M. Schreckenberg (Springer, Berlin/Heidelberg, 2010), pp. 203–214. doi:10.1007/978-3-642-04504-2_15
B. Maury, J. Venel, Handling of contacts in crowd motion simulations, in Traffic and Granular Flow 07, ed. by C. Appert-Rolland, F. Chevoir, P. Gondret, S. Lassarre, J.P. Lebacque M. Schreckenberg (Springer, Berlin/Heidelberg, 2009), pp. 171–180. doi:10.1007/978-3-540-77074-9_15
J.A. Nelder, R. Mead, A simplex method for function minimization. Comput. J. 7(4), 308–313 (1965). doi:10.1093/comjnl/7.4.308
S. Paris, D. Lefebvre, S. Donikian, Simulem: introducing goal oriented behaviours in crowd simulation, in Pedestrian and Evacuation Dynamics 2008, ed. by W.W.F. Klingsch, C. Rogsch, A. Schadschneider, M. Schreckenberg (Springer, Berlin/Heidelberg, 2010). pp. 479–490. doi:10.1007/978-3-642-04504-2_40
A. Seyfried, B. Steffen, A. Winkens, T. Rupprecht, M. Boltes, W. Klingsch, Empirical data for pedestrian flow through bottlenecks, in Traffic and Granular Flow 07, ed. by C. Appert-Rolland, F. Chevoir, P. Gondret, S. Lassarre, J.P. Lebacque, M. Schreckenberg (Springer, Berlin/Heidelberg, 2009), pp. 189–199. doi:10.1007/978-3-540-77074-9_17
V. Tabak, B. Vries, J. Dijkstra, Rfid technology applied for validation of an office simulation model, in Pedestrian and Evacuation Dynamics 2008, ed. by W.W.F. Klingsch, C. Rogsch A. Schadschneider, M. Schreckenberg (Springer, Berlin/Heidelberg, 2010), pp. 269–275. doi:10.1007/978-3-642-04504-2_23
Acknowledgements
This work is supported by the Systems Centre, the EPSRC funded Industrial Doctorate Centre in Systems (Grant EP/G037353/1), and Buro Happold.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Greenwood, D., Sharma, S., Johansson, A. (2015). Mobility Modelling in a Process Constrained Environment: Modelling the Movements of Nurses in a Neonatal Intensive Care Unit. In: Chraibi, M., Boltes, M., Schadschneider, A., Seyfried, A. (eds) Traffic and Granular Flow '13. Springer, Cham. https://doi.org/10.1007/978-3-319-10629-8_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-10629-8_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10628-1
Online ISBN: 978-3-319-10629-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)