Optimizing the Telemedicine Services and Health Informatics From System Identification of the Risk Level in Peruvian Northwestern Cities

dc.contributor.authorNieto-Chaupis, Huber
dc.date.accessioned2018-12-17T03:07:59Z
dc.date.accessioned2022-04-04T16:25:28Z
dc.date.available2018-12-17T03:07:59Z
dc.date.available2022-04-04T16:25:28Z
dc.date.issued2018-09
dc.description.abstractWe use the so-called nonlinear system identification methodology to model the level of risk in those Peruvian Peri urban zones along the northwestern cities and which are under an imminent thread of being flooded due to climate changes. In this paper we evaluate the prospective role of the eHealth services which might be relevant in the sense of providing effective assistance in times of flooding particularly in those vulnerable human groups. To this end we use a mathematical formalism that identifies the system to extract the main system parameters of the system for a subsequent usage of them in the modeling of Telemedicine services and eHealth dynamics. We present some simulations of how these electronic services can be useful to attenuate critic consequences. This paper evaluates the fact of deploying ehealth services in areas of risk in the city of Piura.en_US
dc.description.countryPeruen
dc.description.institutionUniversidad de Ciencias y Humanidadesen
dc.description.trackSoftware Engineering, Telecommunications, Cybersecurity and Computational toolsen
dc.identifier.isbn978-0-9993443-1-6
dc.identifier.issn2414-6390
dc.identifier.otherhttp://laccei.org/LACCEI2018-Lima/meta/FP395.html
dc.identifier.urihttp://dx.doi.org/10.18687/LACCEI2018.1.1.395
dc.identifier.urihttp://axces.info/handle/10.18687/2018102_395
dc.journal.referatopeerReview
dc.language.isoEnglishen_US
dc.publisherLACCEI Inc.en_US
dc.rightsLACCEI License
dc.rights.urihttps://laccei.org/blog/copyright-laccei-papers/
dc.subjectSystem Identificationen_US
dc.subjectFloodingen_US
dc.subjectHealth Informaticsen_US
dc.titleOptimizing the Telemedicine Services and Health Informatics From System Identification of the Risk Level in Peruvian Northwestern Cities
dc.typeArticleen_US

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