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2019-11-21 - Article/Dans un journal avec peer-review - Anglais - 9 page(s)

Debauche Olivier , Mahmoudi Said , Manneback Pierre , Assila Abdessamad, "Fog IoT for Health: A new Architecture for Patients and Elderly Monitoring" in Procedia Computer Science, 160, 289-297

  • Edition : Elsevier, Amsterdam (Netherlands)
  • Codes CREF : Sciences agronomiques (DI3600), Informatique générale (DI1162)
  • Unités de recherche UMONS : Informatique (F114)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech), Institut NUMEDIART pour les Technologies des Arts Numériques (Numédiart)
Texte intégral :

Abstract(s) :

(Anglais) The important increase of the elderly population and their desire to conduct an independent life, even when having medical diseases related to their age, requires the development of new technologies to ensure optimal living comfort for this population. In addition, another category of people, those who are patients with life-threatening problems, may benefit from preventive medical monitoring. In this paper, we present a Fog IoT Cloud-Based Health Monitoring System by using physiological and environmental signals allowing to provide contextual information in terms of Daily Living Activities. Our system enables healthcare providers to follow up health state and behavioral changes of elderly or alone people. Moreover, our system provides a monitoring rehabilitation and recovery processes of patients. Our Fog-IoT architecture consists of a wireless sensor network, a local gateway for data stored locally and quickly, and a Lambda cloud architecture for data processing and storage. The originality of our work resides in the graphical monitoring of new and recent patient data at local smart gateway level. This checkup gives the opportunity to the medical staff quick access to the data, and allows them to validate automatically the observed anomalies. Finally, if a telematic break occurs, the gateway continues to accumulate the data while conducting their analysis. Anonymized data are sent periodically from Smart Gateways to the cloud for archiving and for checkup by medical staff who follow up with patients.

Identifiants :
  • DOI : 10.1016/j.procs.2019.11.087