2.3.3. Energy Reasoning Engine Model

This is the part of the system that generates conclusions and decisions from the available knowledge about the smart building, and plays an important role in implementing the proposed solution by discovering the causes and contexts of energy waste using a set of smart reasoning rules (presented in the next sections). The first step for this unit is to arrange the positions in descending order. The benefit of this arrangement lies in dealing with the most important and most wasted states of energy. It also provides measures to save energy and eliminate energy waste by using SWRL rules, where those rules are represented as conditional logic. Rulesets can also be managed and applied separately to other functions, and each parent clause association rule can be linked to a list of executable actions.

**Figure 2.** Architecture of IRRHEM.

2.3.4. Intelligent home Ontology Model

Ontology is one of the best tools for representing the field of knowledge, particularly in the management of energy in homes. Many works have been interested in this field, the most important of which are the works of Degha et al., most of which, in their entirety, suggest a structural framework for organizing smart building data [22]. It includes machine-interpretable definitions of the basic concepts of the smart building field and the relationships between them. These works include an important number of concepts, namely human, environment, services, devices, places and Context-Awareness. The ontology-based

formal context model can play a vital role in facilitating reasoning by representing the knowledge of the home energy domain. The Semantic Web Rules Language (SWRL) is used, where the rules are applied for different purposes; in addition, the Web Ontology Language (OWL) is used to represent concepts, properties, and relationships. The names of concepts and relationships taken from the ontology (described in detail in the Sections 2.4–2.6) are represented.
