A cloud–edge reference architecture for intertwining health digital domains
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2026-01
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<jats:p> <jats:bold>Objective:</jats:bold> 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. <jats:bold>Methods:</jats:bold> 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. <jats:bold>Results:</jats:bold> 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. <jats:bold>Conclusion:</jats:bold> 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. </jats:p>
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Tramontano, Adriano, Oscar Tamburis, Giulio Perillo, Guido Iaccarino, Arriel Benis and Mario Magliulo (2026). A cloud–edge reference architecture for intertwining health digital domains. Health Informatics Journal, 32(1). 10.1177/14604582251383803 Retrieved from https://hdl.handle.net/10161/34177.
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Arriel Benis
Dr. Arriel Benis is a researcher and educator working at the intersection of medical informatics, digital health, and artificial intelligence, advancing health systems and biomedical engineering innovation. His work leverages AI, data science, and knowledge management to improve health-related decision-making at the individual, population, and public health levels.
His research focuses on developing data-driven healthcare solutions that enhance patient care, optimize clinical processes, and promote sustainable systems. Dr. Benis has engineered (a) clinical decision support systems with direct patient and healthcare partitioners impact such as ADHD, PTSD, and diabetes patient management and health communication, (b) MIMO -the Medical Informatics and Digital Health Multilingual Ontology- integrating more than 3500 terms and concepts across 30+ languages, actively deployed in healthcare organizations for AI-powered training and international projects support, (c) smart home and smart city health monitoring approach from a One Health viewpoint. Dr. Benis is a pioneer of the One Digital Health framework, which strategically links digital health innovation with environmental monitoring.
His past academic positions include serving as a department head and track director in biomedical and health informatics. He holds various leadership roles in the international medical informatics community, is a fellow of the International Academy for Health Sciences Informatics, and is the Editor-in-Chief of JMIR Medical Informatics. Dr. Benis is committed to training the next generation of innovators in digital health and medical informatics.
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