Cyber-Secure IoT and Machine Learning Framework for Optimal Emergency Ambulance Allocation

Cyber-Secure IoT and Machine Learning Framework for Optimal Emergency Ambulance Allocation

Optimizing ambulance deployment is a critical task in emergency medical services (EMS), as it directly affects patient outcomes and system efficiency. This study proposes a cyber-secure, machine learning-based framework for predicting region-specific ambulance allocation and response times across So...

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Bibliographic Details
Main Authors: Jonghyuk Kim, Sewoong Hwang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
Subjects:
ambulance deployment
machine learning
response time prediction
IoT integration
simulation
cybersecurity
Online Access:https://www.mdpi.com/2076-3417/15/13/7156
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