SPeCECA: a smart pervasive chatbot for emergency case assistance based on cloud computing
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SPeCECA: a smart pervasive chatbot for emergency case assistance based on cloud computing Nourche`ne Ouerhani1,2 • Ahmed Maalel1,2 • Henda Ben Ghe´zela2 Received: 10 May 2019 / Revised: 30 June 2019 / Accepted: 20 November 2019 Ó Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract The terrible cost of injuries and sudden illnesses does have fatal consequences that exposes the limitations of the current prehospital processes in terms of time for emergency staff to arrive on scene and lack of first aid skills among the available incident witnesses. In this paper we aim at developing a smart pervasive chatbot for emergency case assistance based on cloud computing called SPeCECA that assists victims or incident witnesses to help avoiding deterioration of the subject’s condition and maintaining his/her physical integrity until the aid arrives, which could dramatically increase the victim’s survivability chances. Therefore, even a person with no first aid skills, can help the victim to survive by performing first aid support as suggested by the virtual assistant. Furthermore, thanks to its connectivity with the emergency medical service, trusted person(s), and the access to social media, SPeCECA has its own way of alarming the emergency case, in parallel, after having released the degree of the emergency situation’s severity. The proposed method is a mobile pervasive healthcare service in the form of a connected mobile application as a virtual assistant for the benefit of anyone facing an emergency case. The proposed chatbot allows an online human-bot interaction that supports different scenarios for every single emergency case. The design of the system is introduced by its six interdependent components: information preprocessing component (IPPC), natural language processing component (NLPC), context component (CC), information post-processing component (IPoPC), response generator component (RGC), and alert message constructor component (AMCC). Keywords Chatbot Emergency First aid Machine learning Pervasive health Smart health
1 Introduction Amongst the top 10 causes of death worldwide in 2016,1 more than 56% were due to injuries and sudden illnesses that could have been prevented if there was an immediate medical intervention.
& Nourche`ne Ouerhani [email protected] Ahmed Maalel [email protected] Henda Ben Ghe´zela [email protected] 1
Higher Institute of Applied Sciences and Technology, University of Sousse, 4003 Sousse, Tunisia
2
RIADI Laboratory, National School of Computer Sciences, University of Manouba, 2010 Manouba, Tunisia
Indeed, when an emergency case strikes, there is no time to start thinking how to react as immediate medical intervention is required. Usually, The obvious reaction in such a situation is to call the Emergency Medical Service (EMS). However, and especially during the rush hours or in bad weather conditions, the emergency medical equipment may waste a lot of time on the road and sear
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