The ever growing number of smart devices connected to the Internet of Things is giving users the chance to sense data from surrounding environment and act upon it. However, interpreting raw data coming from heterogeneous sensors and applying control algorithms to actuators is not a simple task for the common end-user who wants to create applications for smart environments. For these reasons, this work deals with the definition of a novel rule-based semantic architecture for the implementation of building automation applications in an IoT context. Sensor data are abstracted at a high semantic level related to the properties they are associated to and interactions with actuators are driven by high-level desired actions. Applications have the form of an Event- Condition-Action (ECA) rule and the layered architecture separates high-level semantic reasoning aspects from low-level execution details. The proposed architecture is also compared with main state-of-the-art solutions and some suitable technologies for its implementation are suggested.

A novel Rule-based Semantic Architecture for IoT Building Automation Systems

MAINETTI, LUCA;MIGHALI, VINCENZO;PATRONO, Luigi;RAMETTA, PIERCOSIMO
2015-01-01

Abstract

The ever growing number of smart devices connected to the Internet of Things is giving users the chance to sense data from surrounding environment and act upon it. However, interpreting raw data coming from heterogeneous sensors and applying control algorithms to actuators is not a simple task for the common end-user who wants to create applications for smart environments. For these reasons, this work deals with the definition of a novel rule-based semantic architecture for the implementation of building automation applications in an IoT context. Sensor data are abstracted at a high semantic level related to the properties they are associated to and interactions with actuators are driven by high-level desired actions. Applications have the form of an Event- Condition-Action (ECA) rule and the layered architecture separates high-level semantic reasoning aspects from low-level execution details. The proposed architecture is also compared with main state-of-the-art solutions and some suitable technologies for its implementation are suggested.
2015
978-953-290-055-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/394381
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