SBOnto: ONTOLOGY OF SMART BUILDING

Žáček, Martin; Janošek, Michal

doi:10.17654/ec017051101

Cited by 10 publications

(5 citation statements)

References 5 publications

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“…Other future work is extended the current dataset with information about more faults, in order to extend the capability of our system to diagnose a bigger number of faults. In addition, other future works will incorporate meta-learning approaches to autonomously update the knowledge models of the cycle or other sources of knowledge, such as the SBOnto [12,36] or the BOnSAI [37] ontologies, which describe the domain of knowledge in smart buildings. A final work will study the integration of the scheme with existing BMS standards aiming to optimize and effectively control the HVAC systems, which is an essential requirement of smart buildings.…”

Section: Resultsmentioning

confidence: 99%

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An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

Aguilar¹,

Ardila²,

Avendaño³

et al. 2020

Energies

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Early fault detection and diagnosis in heating, ventilation and air conditioning (HVAC) systems may reduce the damage of equipment, improving the reliability and safety of smart buildings, generating social and economic benefits. Data models for fault detection and diagnosis are increasingly used for extracting knowledge in the supervisory tasks. This article proposes an autonomic cycle of data analysis tasks (ACODAT) for the supervision of the building’s HVAC systems. Data analysis tasks incorporate data mining models for extracting knowledge from the system monitoring, analyzing abnormal situations and automatically identifying and taking corrective actions. This article shows a case study of a real building’s HVAC system, for the supervision with our ACODAT, where the HVAC subsystems have been installed over the years, providing a good example of a heterogeneous facility. The proposed supervisory functionality of the HVAC system is capable of detecting deviations, such as faults or gradual increment of energy consumption in similar working conditions. The case study shows this capability of the supervisory autonomic cycle, usually a key objective for smart buildings.

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Section: Resultsmentioning

confidence: 99%

“…But it is yet a hard task to get the perfect optimization of all systems. However, the automated supervision brings benefits, such as the maintenance cost reduction and the robustness against unpredictable perturbations [12].…”

Section: Smart Buildingsmentioning

confidence: 99%

An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

Aguilar¹,

Ardila²,

Avendaño³

et al. 2020

Energies

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“…The DogOnt ontology [89] describes different characteristics of smart environments such as location, capabilities, software interfaces, states, and composition. The Ontology of smart building (SBOnto) [90] intends to formalize knowledge in a smart building, including these main concepts: device, state, architecture, environment, furniture, and network. Finally, the Smart Applications REFerence (SAREF) [91] and its extensions aim to enable interoperability among IoT solutions developed by different appliance manufacturers.…”

Section: Schemas For Building Operations: Sensor Network Iot and Smentioning

confidence: 99%

“…Project Haystack 3 uses a custom text format to encode the schema. BASont [90] was one of the first academic efforts to model building automation systems for various use cases, including design, commissioning, operation, and refurbishment, using modular ontologies. Project Haystack 4 [93], under development at the time of this review, builds on its previous version and adds formal mechanisms for defining terms, a taxonomy, and an ontology on top of Project Haystack 3.…”

Section: Schemas For Building Operations: Commercial Building Automatmentioning

confidence: 99%

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

et al. 2021

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Digital and intelligent buildings are critical to realizing efficient building energy operations and a smart grid. With the increasing digitalization of processes throughout the life cycle of buildings, data exchanged between stakeholders and between building systems have grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent and hinders the development of energy-oriented applications that can be reused across buildings, limiting the scalability of innovative solutions. Addressing this challenge, our review paper systematically reviews metadata schemas and ontologies that are at the foundation of semantic interoperability necessary to move toward improved building energy operations. The review finds 40 schemas that span different phases of the building life cycle, most of which cover commercial building operations and, in particular, control and monitoring systems. The paper’s deeper review and analysis of five popular schemas identify several gaps in their ability to fully facilitate the work of a building modeler attempting to support three use cases: energy audits, automated fault detection and diagnosis, and optimal control. Our findings demonstrate that building modelers focused on energy use cases will find it difficult, labor intensive, and costly to create, sustain, and use semantic models with existing ontologies. This underscores the significant work still to be done to enable interoperable, usable, and maintainable building models. We make three recommendations for future work by the building modeling and energy communities: a centralized repository with a search engine for relevant schemas, the development of more use cases, and better harmonization and standardization of schemas in collaboration with industry to facilitate their adoption by stakeholders addressing varied energy-focused use cases.

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“…The BROT ontology is designed and structured based on a generic modelling approach, and therefore, it can be applied to any types of bridge construction (Hamdan and Kozak, 2019). Another example for such ontologies could be the Web ontology for smart buildings, also known as Ontology for Smart Building (SBOnto), proposed by Žáček and Janošek (2017) with the focus on formalising knowledge in smart buildings. However, BOT, OMG and BPO ontologies are specifically used to extend the ontology created in this paper, described in the following sections.…”

Section: Related Workmentioning

confidence: 99%

Application of semantic Web ontologies for the improvement of information exchange in existing buildings

Sadeghineko

Kumar

2021

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Purpose Facilitating the information exchange and interoperability between stakeholders during the life-cycle of an asset can be one of the fundamental necessities for developing an enhanced information exchange framework. Such a framework can also improve the successful accomplishment of building projects. This paper aims to use Semantic Web technologies for facilitating information exchange within existing building projects. Design/methodology/approach In real-world building projects, the construction industry’s information supply chain may initiate from near scratch when new building projects are started resulting in diverse data structures represented in unstructured data sources, like Excel spreadsheets and documents. Large-scale data generated throughout a building's life-cycle requires exchanging and processing during an asset's Operation and Maintenance (O&M) phase. Building information modelling (BIM) processes and related technologies can address some of the challenges and limitations of information exchange and interoperability within new building projects. However, the use of BIM in existing and retrofit assets has been hampered by the challenges surrounding the limitations of existing technologies. Findings The aim of this paper is twofold. Firstly, it briefly outlines the framework previously developed for generating semantically enriched 3D retrofit models. Secondly, a framework is proposed focussing on facilitating the information exchange and interoperability for existing buildings. Semantic Web technologies and standards, such as Web Ontology Language and existing AEC domain ontologies are used to enhance and improve the proposed framework. Originality/value The proposed framework is evaluated by implementing an example application and the Resource Description Framework data produced by the previously developed framework. The proposed approach makes a valuable contribution to the asset/facilities management (AM/FM) domain. It should be of interest to various FM practices for existing assets, such as the building information/knowledge management for design, construction and O&M stages of an asset’s life-cycle.

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SBOnto: ONTOLOGY OF SMART BUILDING

Cited by 10 publications

References 5 publications

An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

Application of semantic Web ontologies for the improvement of information exchange in existing buildings

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