Arquitetura Multicamadas para Coleta e Análise de Dados de Saúde em Tempo Real em Ambientes Externos, Integrando Fog Computing e Cloud Computing
Year: 2024
Type: conference-paper
Abstract: A multilayer architecture was developed for real-time health data collection and processing, optimized for outdoor environments with high population density and significant network interferences, integrating fog and cloud computing. With the increasing adoption of the Internet of Things (IoT) and Wireless Body Area Networks (WBANs) using smartbands, continuous health monitoring generates vast amounts of data that require efficient processing and reliable transmission. Traditional cloud-based solutions, while scalable, often face high latency and data integrity challenges in unstable network conditions. By leveraging fog computing, the developed architecture performs data preprocessing at the network edge, reducing dependency on cloud connectivity and enhancing system responsiveness. Real-world tests were conducted in complex environments such as football stadiums, beaches, and metro systems, with varying network conditions (5G, 4G, 3G). The architecture consistently achieved over 96% success in packet delivery and significantly reduced latency compared to cloud-only solutions. These results highlight the architecture’s resilience and effectiveness for real-time health monitoring, ensuring data integrity and low response times in high-density, interference-prone environments.
Institution: Universidade Federal de Juiz de Fora
Language: English
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4403389789