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Justin J. Boutilier, BSc Steven C. Brooks, MD Alyf Janmohamed Adam Byers, MDEM Jason E. Buick, MSc Cathy Zhan, MSc Angela P. Schoellig, PhD Sheldon Cheskes, MD Laurie J. Morrison, MD Timothy C. Y. Chan. (2017). “Optimizing a Drone Network to Deliver Automated External Defibrillators”. add link | Justin J. Boutilier, BSc Steven C. Brooks, MD Alyf Janmohamed Adam Byers, MDEM Jason E. Buick, MSc Cathy Zhan, MSc Angela P. Schoellig, PhD Sheldon Cheskes, MD Laurie J. Morrison, MD Timothy C. Y. Chan. (2017). “Optimizing a Drone Network to Deliver Automated External Defibrillators”. add link | ||
===Summary=== | ====Summary==== | ||
This paper focuses on a model for AED delivering drones. The goal of this model is to determine whether a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. The aim of the drones is to arrive 1, 2 or 3 minutes in advance of 911 arrival, the model calculates how many drones and bases are necessary for multiple cities. | This paper focuses on a model for AED delivering drones. The goal of this model is to determine whether a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. The aim of the drones is to arrive 1, 2 or 3 minutes in advance of 911 arrival, the model calculates how many drones and bases are necessary for multiple cities. | ||
Latest revision as of 14:08, 21 March 2018
Optimizing a Drone Network to Deliver Automated External Defibrillators
Justin J. Boutilier, BSc Steven C. Brooks, MD Alyf Janmohamed Adam Byers, MDEM Jason E. Buick, MSc Cathy Zhan, MSc Angela P. Schoellig, PhD Sheldon Cheskes, MD Laurie J. Morrison, MD Timothy C. Y. Chan. (2017). “Optimizing a Drone Network to Deliver Automated External Defibrillators”. add link
Summary
This paper focuses on a model for AED delivering drones. The goal of this model is to determine whether a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. The aim of the drones is to arrive 1, 2 or 3 minutes in advance of 911 arrival, the model calculates how many drones and bases are necessary for multiple cities.