Prescient Profiling – AI Driven Volunteer Selection within a Volunteer Notification System

Jesko Elsner (), Philipp Meisen, Daniel Ewert, Daniel Schilberg and Sabina Jeschke
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Jesko Elsner: RWTH Aachen University, IMA/ZLW & IfU
Philipp Meisen: RWTH Aachen University, IMA/ZLW & IfU
Daniel Ewert: RWTH Aachen University, IMA/ZLW & IfU
Daniel Schilberg: RWTH Aachen University, IMA/ZLW & IfU
Sabina Jeschke: RWTH Aachen University, IMA/ZLW & IfU

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2013/2014, 2014, pp 597-607 from Springer

Abstract: Abstract A volunteer notification system (VNS) is a promising approach to integrate laypersons into emergency medical services (EMS). In case of a medical emergency, a VNS will alarm those potential helpers who can arrive on scene fast enough to provide the most urgent measures until the professional helpers arrive at the victim. Whereas the basic requirements and criteria of a VNS have been discussed in recent publications, this paper will focus on the actual volunteer selection process and the underlying concept of Prescient Profiling. By using concepts of artificial intelligence, the available data is processed in order to generate an abstract digital representation of a volunteer and further enhanced to produce individual user profiles. These profiles will enable predictions on future decisions and the identification of behavioral patterns within the pool of volunteers. The goal is to provide an efficient algorithm for determining a highly sophisticated set of relevant volunteers for an ongoing medical emergency.

Keywords: Volunteer Notification System; First Responder; Emergency Medical Services; Profiling; Artificial Intelligence (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-08816-7_46

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DOI: 10.1007/978-3-319-08816-7_46

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