A cloud–edge reference architecture for intertwining health digital domains.

Objective: In the present work, LinkAll is introduced as a novel architectural model designed to enable real-time monitoring and cross-referential data analysis in remote monitoring systems across human, animal, and environmental health domains. LinkAll leverages Edge-Computing and Internet of Thing...

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Publicado en:Health Informatics Journal Vol. 32; no. 1; pp. 1 - 26
Autores principales: Tramontano, Adriano, Tamburis, Oscar, Perillo, Giulio, Iaccarino, Guido, Benis, Arriel, Magliulo, Mario
Formato: pictorial research tables/charts Journal Article
Publicado: Sage Publications Inc. Jan-Mar2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan-Mar2026
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      pub: Sage Publications Inc.
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        atl: A cloud–edge reference architecture for intertwining health digital domains.
      aug:
        au:
          Tramontano, Adriano
          Tamburis, Oscar
          Perillo, Giulio
          Iaccarino, Guido
          Benis, Arriel
          Magliulo, Mario
        affil: National Research Council of Italy, Institute of Biostructures and Bioimaging (IBB–CNR), Naples, Italy
      sug:
        subj:
          Computing Methodologies
          Cloud Computing
          Digital Health
          Systems Design
          Computer Communication Networks
          Telemetry Methods
          Data Collection Methods
          Computers and Computerization
          Software
          Programming Languages
          Security Measures
          Privacy and Confidentiality
          Data Security
          Funding Source
      ab: Objective: In the present work, LinkAll is introduced as a novel architectural model designed to enable real-time monitoring and cross-referential data analysis in remote monitoring systems across human, animal, and environmental health domains. LinkAll leverages Edge-Computing and Internet of Things principles to handle data collection, processing, and presentation from various sources. Methods: Two sibling systems were implemented to demonstrate its capability, one for monitoring urban greenery and the other for elderly home care. These systems were evaluated based on their ability to integrate with existing information systems, collect biophysical parameters, and ensure data cross-referencing. Results: Both systems demonstrate effective pluggability and cross-referenceability performances, meeting the stakeholders' requirements. LinkAll's ability to integrate diverse sensors and devices into existing infrastructures while providing real-time, machine-actionable insights, is also underscored. Conclusion: Pluggability, cross-referenceability, and compliance with FAIR principles make the architectural model introduced a robust solution for integrating human, animal, and environmental health monitoring systems, enhancing decision-making and contributing to One (Digital) Health's strategic goals.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
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        Journal Article
      ougenre: Article
    language: English
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