A self-adaptive IoT architecture to support computational resource allocation in an e-health environment Extended Abstract – CTDSI/2025

Intelligent environments are complex interaction spaces between people, sensors, devices, and systems. Software Engineering must tackle the intrinsic characteristics of devices and sensors and complex interactions in intelligent environments to consolidate development practices. This work aims to present a self-adaptive IoT architecture in an intelligent environment and evaluate an information system developed based on the architecture. The proposal concerns how the architecture modules work to develop new information systems. The work was developed through a real-world case study in an intelligent e-health environment. The results showed how a self-adaptive architecture using artificial intelligence can support the development of an information system to manage intelligent e-health spaces.

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Published
2025-05-07
DOI
https://doi.org/10.5753/sbsi_estendido.2025.246755
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

A self-adaptive IoT architecture to support computational resource allocation in an e-health environment Extended Abstract – CTDSI/2025

Mateus G. do Nascimento, Mário A. R. Dantas, José David
IoT and Edge/Fog Computing
article

A self-adaptive IoT architecture to support computational resource allocation in an e-health environment Extended Abstract – CTDSI/2025

Mateus G. do Nascimento, Mário A. R. Dantas, José David
article en

Abstract

Intelligent environments are complex interaction spaces between people, sensors, devices, and systems. Software Engineering must tackle the intrinsic characteristics of devices and sensors and complex interactions in intelligent environments to consolidate development practices. This work aims to present a self-adaptive IoT architecture in an intelligent environment and evaluate an information system developed based on the architecture. The proposal concerns how the architecture modules work to develop new information systems. The work was developed through a real-world case study in an intelligent e-health environment. The results showed how a self-adaptive architecture using artificial intelligence can support the development of an information system to manage intelligent e-health spaces.

Universidade Federal de Juiz de Fora (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Petrobras, Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Universidade Federal de Juiz de Fora
Openalex Percentile: Top 91%
IoT and Edge/Fog Computing
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