Choosing the optimal positioning of Emergency Medical Services (EMS) base stations is needed to provide timely assistance in emergency conditions. In rural countries, this is obtained through a tiered system, where ambulances take charge of patients from specific gathering centres, and then take them to the hospitals. Here, a dynamic programming technique based on Dijkstra's algorithm has been devised to optimally allocate EMS to different base stations, based on location and travelling times for the paths leading to gathering centres and hospitals. The system, implemented in Java, has been tested on in-silico data simulating different scenarios of network connectivity, and validated against experimental data of EMS calls managed from the national EMS in Sierra Leone in 2021. The system allows to predict the average travel times to reach hospital facilities as a function of the number of ambulances and Base stations used.
Guarino, G., Bernabucci, I., Bibbo, D., Caviglia, M., Jambai, A.A., Putoto, G., et al. (2022). A Data-Based System for the Optimization of Emergency Medical Services Allocation in Rural Countries. In Proceedings - IEEE Symposium on Computers and Communications (pp.1-4). Institute of Electrical and Electronics Engineers Inc. [10.1109/ISCC55528.2022.9912928].
A Data-Based System for the Optimization of Emergency Medical Services Allocation in Rural Countries
Bernabucci I.;Bibbo D.;Schmid M.
2022-01-01
Abstract
Choosing the optimal positioning of Emergency Medical Services (EMS) base stations is needed to provide timely assistance in emergency conditions. In rural countries, this is obtained through a tiered system, where ambulances take charge of patients from specific gathering centres, and then take them to the hospitals. Here, a dynamic programming technique based on Dijkstra's algorithm has been devised to optimally allocate EMS to different base stations, based on location and travelling times for the paths leading to gathering centres and hospitals. The system, implemented in Java, has been tested on in-silico data simulating different scenarios of network connectivity, and validated against experimental data of EMS calls managed from the national EMS in Sierra Leone in 2021. The system allows to predict the average travel times to reach hospital facilities as a function of the number of ambulances and Base stations used.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
