Risk Prevention of Spreading Emerging Infectious Diseases Using a HybridCrowdsensing Paradigm, Optical Sensors, and Smartphone.

The risk of spreading diseases within (ad-hoc)crowds and the need to pervasively screen asymptomatic individuals to protect the population against emerging infectious diseases, request permanentcrowd surveillance., particularly in high-risk regions. Thecase of Ebola epidemic in West Africa in recent...

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Publicado en:Journal of Medical Systems Vol. 42; no. 5; pp. 1 - 2
Autor principal: Edoh, Thierry
Formato: research tables/charts Journal Article
Publicado: Springer Nature May2018
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
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        10.1007/s10916-018-0937-2
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        atl: Risk Prevention of Spreading Emerging Infectious Diseases Using a HybridCrowdsensing Paradigm, Optical Sensors, and Smartphone.
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        au: Edoh, Thierry
        affil: Technical University of Munich, Institut für Informatik / I1, Boltzmannstraße 3, D-85748 Garching b, Munich, Germany
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        subj:
          Mobile Applications
          Communicable Diseases Africa
          Crowdsourcing
          Wearable Sensors
          Internet of Things
          Body Temperature
          Systems Design
          Female
          Male
          Experimental Studies
          Africa
          Malaria
          Female
          Male
      ab: The risk of spreading diseases within (ad-hoc)crowds and the need to pervasively screen asymptomatic individuals to protect the population against emerging infectious diseases, request permanentcrowd surveillance., particularly in high-risk regions. Thecase of Ebola epidemic in West Africa in recent years has shown the need for pervasive screening. The trend today in diseases surveillance is consisting of epidemiological data collection about emerging infectious diseases using social media, wearable sensors systems, or mobile applications and data analysis. This approach presents various limitations. This paper proposes a novel approach for diseases monitoring and risk prevention of spreading infectious diseases. The proposed approach, aiming at overcoming the limitation of existing disease surveillance approaches, combines the hybrid crowdsensing paradigm with sensing individuals’ bio-signals using optical sensors for monitoring any risks of spreading emerging infectious diseases in any (ad-hoc) crowds. A proof-of-concept has been performed using a drone armed with a cat s60 smartphone featuring a Forward Looking Infra-Red (FLIR) camera. According to the results of the conducted experiment, the concept has the potential to improve the conventional epidemiological data collection. The measurement is reliable, and the recorded data are valid. The measurement error rates are about 8%.
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    language: English
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