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Author: Fadi El-Hassan

Affiliation: College of Engineering, Al Ain University, Al Ain, Abu Dhabi, U.A.E.

ISBN: 978-989-758-403-9

ISSN: 2184-4380

Keyword(s): Smart Emergency, Prehospital Management, Algorithmic State Machine, Internet of Things, Embedded Systems, Health Emergency Management.

Abstract: In emergency cases related to massive accidents, environmental disasters, and war time, health professionals face considerable challenges due to the high number of patients who are in need of emergency treatment. Research works attempt to propose effective in-hospital and pre-hospital smart emergency systems to reduce the mortality rate among the patients who desperately wait to receive appropriate care. This paper presents a model of a timely prehospital emergency management system that can be implemented as an interface to an Internet of Things (IoT) environment. This work presents the necessary stages for prehospital emergency environments, where many factors may make the timely management of emergency systems very difficult. The proposed model is based on an Algorithmic State Machine (ASM) that can be implemented in either hardware or software, providing an embedded system interface for IoT. Moreover, this paper provides a timing analysis for either a single emergency event or mul tiple simultaneous emergency events. Embedded systems’ developers can use the proposed model to produce an appropriate prehospital smart emergency solution. (More)

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Paper citation in several formats:
El-Hassan, F. (2020). Algorithmic State Machine Design for Timely Health Emergency Management in an IoT Environment.In Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-403-9, ISSN 2184-4380, pages 150-156. DOI: 10.5220/0009183301500156

@conference{sensornets20,
author={Fadi T. El{-}Hassan.},
title={Algorithmic State Machine Design for Timely Health Emergency Management in an IoT Environment},
booktitle={Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2020},
pages={150-156},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009183301500156},
isbn={978-989-758-403-9},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Algorithmic State Machine Design for Timely Health Emergency Management in an IoT Environment
SN - 978-989-758-403-9
AU - El-Hassan, F.
PY - 2020
SP - 150
EP - 156
DO - 10.5220/0009183301500156

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