A scalable semantic framework for IoT healthcare applications

IoT-based systems for early epidemic detection have not been investigated yet in the research. The state-of-the art in sensor technology and activity recognition makes it possible to automatically detect activities of daily living (ADL). Semantic reasoning over ADLs can discover anomalies and sympto...

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Bibliographic Details
Published in:Journal of ambient intelligence and humanized computing 2023-05, Vol.14 (5), p.4883-4901
Main Authors: Zgheib, Rita, Kristiansen, Stein, Conchon, Emmanuel, Plageman, Thomas, Goebel, Vera, Bastide, Rémi
Format: Article
Language:English
Subjects:
Activities of daily living
Activity recognition
Artificial Intelligence
Chronic obstructive pulmonary disease
Computational Intelligence
Computer Aided Engineering
Computer Science
Data processing
Dementia
Ebola virus
Engineering
Epidemics
Food contamination & poisoning
Middleware
Older people
Ontology
Original Research
Real time
Reasoning
Robotics and Automation
Semantics
Sensors
Signs and symptoms
User Interfaces and Human Computer Interaction
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Summary:IoT-based systems for early epidemic detection have not been investigated yet in the research. The state-of-the art in sensor technology and activity recognition makes it possible to automatically detect activities of daily living (ADL). Semantic reasoning over ADLs can discover anomalies and symptoms for disorders, hence diseases and epidemics. However, semantic reasoning is computationally rather expensive and therefore unusable for real-time monitoring in large scale applications, like early epidemic detection. To overcome this limitation, this paper proposes a new scalable semantic framework based on several semantic reasoning techniques that are distributed over a semantic middleware. To reduce the number of events to process during the semantic reasoning, a complex event processing (CEP) engine is used to detect abnormal events in ADL and to generate the associated symptom indicators. To demonstrate real-time detection and scalability, the proposed framework integrates a new extension of ADLSim, a discrete event simulator that simulates long-term sequences of ADL.
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-020-02136-2