Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Smart Hospital Emergency System Via Mobile-based Requesting Services

Al-Khafajiy, M, Kolivand, H, Baker, T, Tully, D and Waraich, A (2019) Smart Hospital Emergency System Via Mobile-based Requesting Services. Multimedia Tools and Applications. ISSN 1380-7501

Al-khafajiy2019_Article_SmartHospitalEmergencySystem.pdf - Published Version
Available under License Creative Commons Attribution.

Download (4MB) | Preview


In recent years, the UK's emergency call and response has shown elements of great strain as of today. The strain on emergency call systems estimated by a 9 million calls (including both landline and mobile) made in 2014 alone. Coupled with an increasing population and cuts in government funding, this has resulted in lower percentages of emergency response vehicles at hand and longer response times. In this paper, we highlight the main challenges of emergency services and overview of previous solutions. In addition, we propose a new system call Smart Hospital Emergency System (SHES). The main aim of SHES is to save lives through improving communications between patient and emergency services. Utilising the latest of technologies and algorithms within SHES is aiming to increase emergency communication throughput, while reducing emergency call systems issues and making the process of emergency response more efficient. Utilising health data held within a personal smartphone, and internal tracked data (GPU, Accelerometer, Gyroscope etc.), SHES aims to process the mentioned data efficiently, and securely, through automatic communications with emergency services, ultimately reducing communication bottlenecks. Live video-streaming through real-time video communication protocols is also a focus of SHES to improve initial communi- cations between emergency services and patients. A prototype of this system has been developed. The system has been evaluated by a preliminary usability, reliability, and communication performance study.

Item Type: Article
Uncontrolled Keywords: 0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems, 0801 Artificial Intelligence and Image Processing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Computer Science & Mathematics
Publisher: Springer Verlag (Germany)
Date Deposited: 25 Jan 2019 11:22
Last Modified: 04 Sep 2021 09:47
URI: https://researchonline.ljmu.ac.uk/id/eprint/10022
View Item View Item