EEPSA as a core ontology for energy efficiency and thermal comfort in buildings

Tracking #: 2076-3289

This paper is currently under review
Authors: 
Iker Esnaola-Gonzalez
Jesús Bermúdez1
Izaskun Fernandez
Aitor Arnaiz

Responsible editor: 
Guest Editors Sensors Observations 2018

Submission type: 
Full Paper
Abstract: 
Achieving a comfortable thermal situation within buildings with an efficient use of energy remains still an open challenge for most buildings. In this regard, IoT (Internet of Things) and KDD (Knowledge Discovery in Databases) processes may be combined to solve these problems, even though data analysts may feel overwhelmed by heterogeneity and volume of the data to be considered. Data analysts could benefit from an application assistant that supports them throughout the KDD process and aids them discovering which are the most relevant variables for the matter at hand, or informing about relationships among relevant data. In this article, the EEPSA (Energy Efficiency Prediction Semantic Assistant) ontology which supports such an assistant is presented. This ontology is developed on top of three ODPs (Ontology Design Patterns) which address weaknesses of existing proposals to represent features of interest and their respective qualities, as well as observations and actuations, the sensors and actuators that generate them, and the procedures used. The ontology is designed so that its customization to address similar problems in different types of buildings can be approached methodically. This feature is proved in a real-world poultry farm.
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