Intelligent Reasoning Rules for Home Energy Management (IRRHEM): Algeria Case Study

Saba, Djamel; Cheikhrouhou, Omar; Alhakami, Wajdi; Sahli, Youcef; Hadidi, Abdelkader; Hamam, Habib

doi:10.3390/app12041861

Cited by 9 publications

(5 citation statements)

References 36 publications

(37 reference statements)

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“…Ontology is a formal and explicit representation of information associated with a specific domain [15][16][17]. In medicine, ontology is interested in the genesis of medical entities: diseases, clinical signs, clinical syndromes, symptoms, lesions, biological anomalies, and radiological anomalies [18].…”

Section: Methods and Resultsmentioning

confidence: 99%

“…The reasoning is concerned with the exploitation of acquired knowledge to produce new knowledge, as it uses inference mechanisms that allow solving many problems [29]. Additionally, different reasoning mechanisms are used, depending on the objectives of the system to be prepared [16,17]: logical reasoning, inference by classification, filtering, inheritance, and rule-based reasoning (Table 5 and Appendix A).…”

Section: Intelligent Reasoningmentioning

confidence: 99%

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Development of an Ontology-Based Solution to Reduce the Spread of Viruses

et al. 2022

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With the sudden emergence of many dangerous viruses in recent years and with their rapid transmission and danger to individuals, most countries have adopted several strategies, such as closure and social distancing, to control the spread of the virus in the population. In parallel with all these precautions, scientific laboratories are working on developing the appropriate vaccine, which in many cases takes many years. Until then, it is necessary to resort to many solutions, including solutions that rely on information technologies and artificial intelligence (AI). In this context, this paper proposes a new solution based on the ontology and rules of intelligent reasoning. Initially, the virus environment is analyzed, followed by the extraction and editing of the main elements of the ontology using the “Protégé” software. In the last step, the proposed solution is tested, by choosing the city of Adrar in southwestern Algeria, which was particularly affected by COVID-19. Three scenarios were shown for different cases. The efficiency of the proposed solution was confirmed through the instructions it provides in the event of symptoms appearing in a person. In addition, this solution helps the competent authorities know the location and extent of the epidemic by informing the local communities.

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Section: Methods and Resultsmentioning

confidence: 99%

Section: Intelligent Reasoningmentioning

confidence: 99%

Development of an Ontology-Based Solution to Reduce the Spread of Viruses

et al. 2022

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“…Often, homeowners are unaware of the costs of some domestic energy wasting behaviours they involuntarily adopt, such as forgetting the windows open or leaving them open for too long a period of time. Therefore, monitoring in-home energy wasting in order to provide tenants immediate feedback can be a crucial feature for actuating an efficient energy wasting reduction in an IoT home automation system [32].…”

Section: Energy Conservation Monitoring Scenariomentioning

confidence: 99%

Supporting Smart Home Scenarios Using OWL and SWRL Rules

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Carbonaro

Boer

et al. 2022

Sensors

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Despite the pervasiveness of IoT domotic devices in the home automation landscape, their potential is still quite under-exploited due to the high heterogeneity and the scarce expressivity of the most commonly adopted scenario programming paradigms. The aim of this study is to show that Semantic Web technologies constitute a viable solution to tackle not only the interoperability issues, but also the overall programming complexity of modern IoT home automation scenarios. For this purpose, we developed a knowledge-based home automation system in which scenarios are the result of logical inferences over the IoT sensors data combined with formalised knowledge. In particular, we describe how the SWRL language can be employed to overcome the limitations of the well-known trigger-action paradigm. Through various experiments in three distinct scenarios, we demonstrated the feasibility of the proposed approach and its applicability in a standardised and validated context such as SAREF

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“…After consulting previous works, many contributions concern the optimization of HES [27]. These works have achieved very encouraging results, but they still require some development through the introduction (or removal) of concepts and the development of intelligent reasoning [28][29][30].…”

Section: Reuse Of Existing Ontologiesmentioning

confidence: 99%

Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems

et al. 2022

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This paper presents a proposal for the development of a new intelligent solution for the optimization of hybrid energy systems. This solution is of great importance for installers of hybrid energy systems, as it helps them obtain the best configuration of the hybrid energy system (efficient and less expensive). In this solution, it is sufficient to enter the name of the location of the hybrid energy system that we want to install; after that, the solution will show the name of the best technology from which the optimal configuration of this system can be obtained. To accomplish this goal, the study relied on the ontology approach for two reasons, one of which is related to the nature of hybrid systems, because it is characterized by a large amount of information that requires good structuring, and the second reason is the interaction of hybrid energy systems with the external environment (climate, site characteristics). Afterward, to develop the knowledge base of the ontology, many steps were followed, the first of which is related to a detailed study of the existing one and the extraction of the basic elements, such as the concepts and the relations between them, followed by the development of the rules of intelligent reasoning, which is an interaction between the elements of the ontology through which all possible cases are treated. The “Protégé” software was used to edit these elements and perform the simulation process to show the results of the developed solution. Finally, the paper includes a case study, and the results show the importance of the developed solution, and it is open to future developments.

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Intelligent Reasoning Rules for Home Energy Management (IRRHEM): Algeria Case Study

Cited by 9 publications

References 36 publications

Development of an Ontology-Based Solution to Reduce the Spread of Viruses

Development of an Ontology-Based Solution to Reduce the Spread of Viruses

Supporting Smart Home Scenarios Using OWL and SWRL Rules

Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems

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