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Context-aware monitoring for IoT: an approach based on Agents, and Federated Learning

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Author(s):
Curasma, Herminio Paucar ; Estrella, Julio Cezar
Total Authors: 2
Document type: Journal article
Source: PROCEEDINGS OF12TH LATIN-AMERICAN SYMPOSIUM ON DEPENDABLE AND SECURE COMPUTING, LADC 2023; v. N/A, p. 2-pg., 2023-01-01.
Abstract

This paper proposes a software architecture model applied for context-aware monitoring of Smart Buildings(SB), and it works in two layers: Fog and Edge computing and uses the Multi-Agent System(MAS) and Federated Learning(FL). The objective of this architecture will allow context-aware monitoring and the capture of anomalies and offer specific functionalities that depend on the user roles. As a result, we modeled the complete software architecture considering Reactive, edge-fog computing, and MAS components, following the best practices from the literature and the 2413-IEEE standard. (AU)

FAPESP's process: 11/09524-7 - Development and evaluation of new computer technics to enable the provision of quality of service in SOA architectures
Grantee:Júlio Cézar Estrella
Support Opportunities: Regular Research Grants
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC