Abstract
Introduction: Today, Internet of Things applications offer new opportunities in all
domains like home automation, transportation, medical diagnosis, agriculture, etc. According to
McKinsey Global Institute research, IoT will cover a market share of over $11.1 trillion by 2025.
Moreover, Semantic web technology approaches are used in IoT applications so that machines
can understand and interpret sensor-collected data.
Method: Our proposed system uses a DHT11 sensor, NodeMCU for data collection, and Thing-
Speak cloud for data analysis and visualization. It utilizes the Protégé tool to develop semantic
data modelling using Ontology/RDF graphs and retrieval for future SPARQL queries.
Result: This patent approach ensures the optimal presentation of sensor data and the meaning of
data and controls the information for the Home Automation System. By semantic layer, we improved
integration, interoperability, discovery, and data analysis.
Conclusion: As far as applications are concerned, semantic technologies and IoT sensor data can
be transformed into a more valuable and practical format, enabling intelligent applications and
systems development across multiple fields, such as smart cities, industrial automation,
healthcare, and environmental monitoring.
Keywords:
IoT, ontology, RDF triple, SPARQL, NodeMCU, DHT11 sensor, ThingSpeak, protege, Apache Jena Fuseki.
Graphical Abstract
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