Swift personal emergency help facilitated by the mobile cloud

Alshareef, Hazzaa; Grigoraş, Dan

doi:10.1504/ijhpcn.2018.10015024

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…In fact, these kinds of emergency and mutual-assist apps are useful to professionals who have received first-aid training and are willing to assist strangers to receive first aid at fire stations. With regard to the satellite positioning system in the smartphone, a message is sent to emergency personnel near the patient's location and volunteers go to the rescue site according to satellite positioning [23]. This voluntary emergency ambulance network relies on extensive personnel support.…”

Section: Introductionmentioning

confidence: 99%

Mutual-Aid Mobile App for Emergency Care: Feasibility Study

et al. 2020

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Background Improving the quality of patient care through the use of mobile devices is one of the hot topics in the health care field. In unwanted situations like an accident, ambulances and rescuers often require a certain amount of time to arrive at the scene. Providing immediate cardiopulmonary resuscitation (CPR) to patients might improve survival. Objective The primary objective of this study was to evaluate the feasibility of an emergency and mutual-aid app model in Taiwan and to provide a reference for government policy. Methods A structured questionnaire was developed as a research tool. All questionnaires were designed according to the technology acceptance model, and a Likert scale was used to measure the degree of agreement or disagreement. Moreover, in-depth interviews were conducted with six experts from medical, legal, and mobile app departments. Each expert was interviewed once to discuss feasible countermeasures and suggestions. Statistical Package for the Social Sciences (SPSS version 19; IBM Corp, Armonk, New York) was used to perform all statistical analyses, including descriptive statistics, independent sample t-tests, variance analysis, and Pearson correlation analysis. Results We conducted this study between October 20, 2017, and November 10, 2017, at the Taipei Medical University Hospital. Questionnaires were distributed to medical personnel, visiting guests, family members, and volunteers. A total of 113 valid questionnaires were finally obtained after the exclusion of incomplete questionnaires. Cronbach α values for self-efficacy (perceived ease of use), use attitude (perceived usefulness), and use willingness and frequency were above .85, meeting the criterion of greater than .70. We observed that the reliability of each subquestion was acceptable and the values for use attitude (perceive usefulness) and use willingness and frequency were more than .90. Conclusions The findings suggest that perceived ease of use and perceived usefulness of the app model affect use willingness. However, perceived usefulness had an intermediary influence on use willingness. Experts in law, medical, and technology fields consider that an emergency and mutual-aid model can be implemented in Taiwan. Along with the development of an emergency and mutual-aid app model, we recommend an increase in the number of automated external defibrillators per region and promotion of correct knowledge about CPR in order to decrease morbidity and mortality.

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Section: Introductionmentioning

confidence: 99%

Mutual-Aid Mobile App for Emergency Care: Feasibility Study

et al. 2020

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Multi-service Cloud of Drones for Multi-purpose Applications

Alshareef

Grigoraş

2017

2017 16th International Symposium on Parallel and Distributed Computing (ISPDC)

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Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks

Benadda¹,

Belalem²

2020

International Journal of Software Science and Computational Intelligence

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Malaise and sleepiness behind the wheel are considered to be the leading causes of fatal highway accidents. With the body area networks (BANs), a continuous health monitoring of a driver can be performed without any constraint on his/her normal daily life activities. Many of the systems proposed in the literature are intended to prevent traffic accidents but without treating this kind of cause because difficult to highlight in an accident. This paper proposes “HAaaS,” a new vehicular cloud computing service based on BANs to detect, monitor, and manage driver malaise and provide a cooperation support for the driver rescue. The objective is to reduce the number of accidents, the material and human damage as the time and fuel lost in traffic jams. The proposed service has been validated by simulating real-world highway scenarios extracted from Oran city in Algeria. The results show that the service is efficient at a significant rate.

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Swift personal emergency help facilitated by the mobile cloud

Cited by 3 publications

References 33 publications

Mutual-Aid Mobile App for Emergency Care: Feasibility Study

Mutual-Aid Mobile App for Emergency Care: Feasibility Study

Multi-service Cloud of Drones for Multi-purpose Applications

Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks

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