Ambulance Location for Service Coverage in an Urban-rural Area in Chiang Rai using Machine Learning

Ambulance response time is a critical factor in saving lives and is heavily influenced by ambulance placement strategies. Currently, Nang Lae Subdistrict is served by only one ambulance, yet the managing agency does not systematically analyze high-frequency accident zones or areas with frequent emergency calls. This oversight raises concerns about whether the current ambulance station provides optimal coverage. To address this, call data from all ambulance dispatches over four months (July–November 2023) were analyzed. The findings revealed 96 cases within a 5-kilometer radius of Nang Lae Subdistrict Municipality and 18 cases within a 10-kilometer radius. Cluster analysis was conducted to determine optimal ambulance placement, identifying two potential locations approximately 1.55 km apart. These results can inform strategic improvements in ambulance deployment, particularly during high-demand periods such as festivals, where accident rates surge and faster response times are crucial. Additionally, the study observed instances of ambulances servicing areas beyond their designated zones, suggesting a need for better resource allocation.

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Publication Details

Journal
Journal of Mobile Multimedia
Published
2025-10-03
DOI
https://doi.org/10.13052/jmm1550-4646.2152
Primary Topic
Facility Location and Emergency Management
Type
article
Field-Weighted Citation Impact
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article

Ambulance Location for Service Coverage in an Urban-rural Area in Chiang Rai using Machine Learning

Tosporn Arreeras, Sunida Tiwong, Krit Sittivangkul, Samatthachai Yamsa-ard
Journal of Mobile Multimedia
Facility Location and Emergency Management
article

Ambulance Location for Service Coverage in an Urban-rural Area in Chiang Rai using Machine Learning

Tosporn Arreeras, Sunida Tiwong, Krit Sittivangkul, Samatthachai Yamsa-ard
article en

Abstract

Ambulance response time is a critical factor in saving lives and is heavily influenced by ambulance placement strategies. Currently, Nang Lae Subdistrict is served by only one ambulance, yet the managing agency does not systematically analyze high-frequency accident zones or areas with frequent emergency calls. This oversight raises concerns about whether the current ambulance station provides optimal coverage. To address this, call data from all ambulance dispatches over four months (July–November 2023) were analyzed. The findings revealed 96 cases within a 5-kilometer radius of Nang Lae Subdistrict Municipality and 18 cases within a 10-kilometer radius. Cluster analysis was conducted to determine optimal ambulance placement, identifying two potential locations approximately 1.55 km apart. These results can inform strategic improvements in ambulance deployment, particularly during high-demand periods such as festivals, where accident rates surge and faster response times are crucial. Additionally, the study observed instances of ambulances servicing areas beyond their designated zones, suggesting a need for better resource allocation.

Journal of Mobile Multimedia
Mae Fah Luang University (TH)
Openalex Percentile: Top 68%
Facility Location and Emergency Management
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Ambulance Location for Service Coverage in an Urban-rural Area in Chiang Rai using Machine Learning — Tosporn Arreeras, Sunida Tiwong, et al. · Journal of Mobile Multimedia (2025) | TGRS Research Map | TGRS