Ambulance integration model in smart city for health services

Smart city is a city built to create efficient, sustainable, fair and livable cities. Increasing the percentage of population survival in standard and emergency times or emergency medical services (EMS) is one of the main pillars of a smart city. This study develops previous research. The weakness of this model is that it needs to consider the dynamic travel time factor. The model only considers the fixed travel time between two locations, which may not represent the actual conditions on the highway. It is less flexible because it only finds one threshold value α for all λi. Researchers succeeded in developing a model to overcome the model weaknesses in (4) by adding new constraints that consider ambulance capacity and overcome the shortcomings of the model (5) by adding tighter limits on the value of α to minimize the difference between the values of λi and αλi. In addition, constraints can also be added to ensure that α is a realistic value and meets business requirements.

Authors

Publication Details

Journal
Bulletin of Electrical Engineering and Informatics
Published
2025-05-02
DOI
https://doi.org/10.11591/eei.v14i3.7202
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Ambulance integration model in smart city for health services

Erna Budhiarti Nababan, Muhammad Zarlis, Tulus Tulus, Rafiqa Dewi
Bulletin of Electrical Engineering and Informatics
IoT and Edge/Fog Computing
article

Ambulance integration model in smart city for health services

Erna Budhiarti Nababan, Muhammad Zarlis, Tulus Tulus, Rafiqa Dewi
article en

Abstract

Smart city is a city built to create efficient, sustainable, fair and livable cities. Increasing the percentage of population survival in standard and emergency times or emergency medical services (EMS) is one of the main pillars of a smart city. This study develops previous research. The weakness of this model is that it needs to consider the dynamic travel time factor. The model only considers the fixed travel time between two locations, which may not represent the actual conditions on the highway. It is less flexible because it only finds one threshold value α for all λi. Researchers succeeded in developing a model to overcome the model weaknesses in (4) by adding new constraints that consider ambulance capacity and overcome the shortcomings of the model (5) by adding tighter limits on the value of α to minimize the difference between the values of λi and αλi. In addition, constraints can also be added to ensure that α is a realistic value and meets business requirements.

Bulletin of Electrical Engineering and InformaticsVol. 14(3)
Openalex Percentile: Top 91%
IoT and Edge/Fog Computing
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