Semantic enrichment of sensor data: a case study in environmental health
Nenhuma Miniatura disponível
Data
2021-08-06
Autores
Título da Revista
ISSN da Revista
Título de Volume
Editor
Universidade Federal de Goiás
Resumo
Indoor Air Quality is crucial for human health, but over ninety percent of
people worldwide breathe air with pollutant levels that exceed the WHO limits,
which may trigger or worsen symptoms the longer one stays exposed. Studies
in the area face an inherent difficulty: the massive number of interconnected
elements and the effects on human health. However, IoT technologies like
sensors and actuators are helping the field address this problem by acquiring
and processing EH data to be used in automation and decision-making. Still,
although sensors deployment is relatively simple and feasible, raw data is
barely useless in practice, requiring preprocessing before usage and is highly
dynamic, meaning sensor data for Environmental Health (EH) should be
handled as data streams. Streams can be enriched with information such as
air quality indexes and associated with curated medical knowledge, improving
usage. IoT's regular data life cycle comprises acquisition, modeling, reasoning,
and distribution, so a first step to enable an IoT-based EH scenario is a shared
common representation for EH data acquired from sensors, which can be met
by Ontologies' expressiveness and reasoning support. The organization of the
fundamental processes of IoT-based EH systems into a reference architecture
can further support the development of such systems and a Reference
Architecture like RAISE, whose central idea is to structure general software
components into a reusable design solution for semantic enrichment of
healthcare data attain this task. That process comprises steps like acquisition,
modeling, extraction, preprocessing, semantic annotation, integration, and
storage of heterogeneous healthcare information. The problem addressed here
is the low number of validation research investigating semantic enrichment
and integration of EH data through ontologies and medical knowledge. This
work's objective was to elaborate on an instance of the RAISE architecture
that enriches sensor data for the EH domain, contributing with: Semantic
Enrichment of EH sensor-acquired data; The link between ontologies to
address the complete picture; and more.
Descrição
Palavras-chave
Citação
SILVA, L. F. M. Semantic enrichment of sensor data: a case study in environmental health. 2021. 109 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2021.