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. 2023 Jan 18;20(3):1808.
doi: 10.3390/ijerph20031808.

A Smart Spatial Routing and Accessibility Analysis System for EMS Using Catchment Areas of Voronoi Spatial Model and Time-Based Dijkstra's Routing Algorithm

Abdullah Alamri  1
Affiliations

A Smart Spatial Routing and Accessibility Analysis System for EMS Using Catchment Areas of Voronoi Spatial Model and Time-Based Dijkstra's Routing Algorithm

Abdullah Alamri. Int J Environ Res Public Health. .

Abstract

The concept of a catchment area is often used to establish equitable access to essential services such as ambulance emergency medical services. In a time-sensitive environment, taking the wrong decision when there is a need for a short travel time can have serious consequences. In ambulance management, a mistaken dispatch which may result in the late arrival of an ambulance can lead to a life-and-death situation. In addition, finding the optimal route to reach the destination within a minimum amount of time is a significant problem. A spatial routing analysis based on travel times within the emergency services catchment area can quickly find the best routes to emergency points and may overcome this problem. In this study, a smart spatial routing and accessibility analysis system is proposed for EMS using catchment areas of the Voronoi spatial model and time-based Dijkstra's routing algorithm (TDRA) to support the route analysis of emergencies and to facilitate the dispatch of appropriate units that are able to respond within a reasonable time frame. Our simulation shows that the system can successfully predict and determine the nearest candidate ambulance unit within the catchment area and candidate ambulance services in the adjacent catchment area that has a minimum travel time to the demand point taking TDRA construction into account.

Keywords: dijkstra’s algorithm; public health emergency; spatial analysis; spatial database; voronoi diagram.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Emergency medical services catchment in Riyadh using Voronoi diagram.
Figure 2
Figure 2
Road infrastructure catchment using NVD.
Figure 3
Figure 3
Proposed system architecture.
Figure 4
Figure 4
A spatial Voronoi diagram showing the road network for three emergency zones.
Figure 5
Figure 5
Example of the nearest POIs (EMS) from n1.
Figure 6
Figure 6
Study area.
Figure 7
Figure 7
Locations of 30 EMS ambulance unit stations in Riyadh.
Figure 8
Figure 8
Catchment area of the emergency locations.
Figure 9
Figure 9
Catchment areas of Voronoi spatial model.
Figure 10
Figure 10
Candidate ambulance units within the catchment areas.
Figure 11
Figure 11
Ambulance emergency unit that has the minimum travel time.
Figure 12
Figure 12
Impact of the cost parameters on the total travel time with Dijkstra’s algorithm.
See this image and copyright information in PMC

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