An approach based on the ifcOWL ontology to support indoor navigation

González, Evelio J.; Piñeiro, J. D.; Toledo, Jonay; Arnay, Rafael; Sánchez, Leopoldo

doi:10.1016/j.eij.2020.02.008

Cited by 16 publications

(8 citation statements)

References 41 publications

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“…Each level can only refer to the information resources of the same and lower levels, but not those of the upper level, to ensure the stability of the information description. IFC could define new classes as subclasses of existing classes from which the new classes inherit their properties [60].…”

Section: Ifc Datamentioning

confidence: 99%

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Integration of Industry Foundation Classes and Ontology: Data, Applications, Modes, Challenges, and Opportunities

Jia,

Ma,

Zhang

2024

Buildings

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Industry Foundation Classes (IFCs), as the most recognized data schema for Building Information Modeling (BIM), are increasingly combined with ontology to facilitate data interoperability across the whole lifecycle in the Architecture, Engineering, Construction, and Facility Management (AEC/FM). This paper conducts a bibliometric analysis of 122 papers from the perspective of data, model, and application to summarize the modes of IFC and ontology integration (IFCOI). This paper first analyzes the data and models of the integration from IFC data formats and ontology development models to the IfcOWL data model. Next, the application status is summed up from objective and phase dimensions, and four frequent applications with maturity are identified. Based on the aforementioned multi-dimensional analysis, three integration modes are summarized, taking into account various data interoperability requirements. Accordingly, ontology behaves as the representation of domain knowledge, an enrichment tool for IFC model semantics, and a linkage between IFC data and other heterogeneous data. Finally, this paper points out the challenges and opportunities for IFCOI in the data, domain ontology, and integration process and proposes a building lifecycle management model based on IFCOI.

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Section: Ifc Datamentioning

confidence: 99%

“…IFC data; BIM model; historical work records; real-time monitoring data [27,29,32,35,60,74,[78][79][80]82,101,103,104,113,116,123,124,137,146] Data principal…”

Section: Preconstruction Phasementioning

confidence: 99%

Integration of Industry Foundation Classes and Ontology: Data, Applications, Modes, Challenges, and Opportunities

Jia,

Ma,

Zhang

2024

Buildings

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“…The wheelchair is composed of a localization system based on encoder odometry and other sensors [ 17 ]. An algorithm based on BIM technology to indicate the destination of the intelligent wheelchair [ 18 ] and a system for obstacle avoidance and localization [ 19 ].…”

Section: Hardware Setupmentioning

confidence: 99%

Low Cost Magnetic Field Control for Disabled People

Acosta

Fariña

Toledo

et al. 2023

Sensors

Self Cite

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Our research presents a cost-effective navigation system for electric wheelchairs that utilizes the tongue as a human–machine interface (HMI) for disabled individuals. The user controls the movement of the wheelchair by wearing a small neodymium magnet on their tongue, which is held in place by a suction pad. The system uses low-cost electronics and sensors, including two electronic compasses, to detect the position of the magnet in the mouth. One compass estimates the magnet’s position while the other is used as a reference to compensate for static magnetic fields. A microcontroller processes the data using a computational algorithm that takes the mathematical formulations of the magnetic fields as input in real time. The system has been tested using real data to control an electric wheelchair, and it has been shown that a trained user can effectively use tongue movements as an interface for the wheelchair or a computer.

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“…Following Beetz's work in transforming IFC to an "ifcOWL" ontology, Terkaj and Šojić (2015) and Pauwels et al (2017) provide a more detailed conversion procedure. These efforts on developing ifcOWL keep the resulting OWL ontology as close as possible to the original EXPRESS schema of IFC (Pauwels et al, 2017) and have been used to build knowledge-based models for storing geometric information (Farias et al, 2018;González et al, 2021;Wagner et al, 2022). Different from ifcOWL, "OntoSTEP" from Krima et al (2009) serves a broader scope, based on which Barbau et al (2012) developed a plug-in for ontology editor Protégé.…”

Section: Related Workmentioning

confidence: 99%

A semantic similarity-based method to support the conversion from EXPRESS to OWL

Liu,

Jian,

Eckert

2023

AIEDAM

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Product data sharing is fundamental for collaborative product design and development. Although the STandard for Exchange of Product model data (STEP) enables this by providing a unified data definition and description, it lacks the ability to provide a more semantically enriched product data model. Many researchers suggest converting STEP models to ontology models and propose rules for mapping EXPRESS, the descriptive language of STEP, to Web Ontology Language (OWL). In most research, this mapping is a manual process which is time-consuming and prone to misunderstandings. To support this conversion, this research proposes an automatic method based on natural language processing techniques (NLP). The similarities of language elements in the reference manuals of EXPRESS and OWL have been analyzed in terms of three aspects: heading semantics, text semantics, and heading hierarchy. The paper focusses on translating between language elements, but the same approach has also been applied to the definition of the data models. Two forms of the semantic analysis with NLP are proposed: a Combination of Random Walks (RW) and Global Vectors for Word Representation (GloVe) for heading semantic similarity; and a Decoding-enhanced BERT with disentangled attention (DeBERTa) ensemble model for text semantic similarity. The evaluation shows the feasibility of the proposed method. The results not only cover most language elements mapped by current research, but also identify the mappings of the elements that have not been included. It also indicates the potential to identify the OWL segments for the EXPRESS declarations.

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An approach based on the ifcOWL ontology to support indoor navigation

Cited by 16 publications

References 41 publications

Integration of Industry Foundation Classes and Ontology: Data, Applications, Modes, Challenges, and Opportunities

Integration of Industry Foundation Classes and Ontology: Data, Applications, Modes, Challenges, and Opportunities

Low Cost Magnetic Field Control for Disabled People

A semantic similarity-based method to support the conversion from EXPRESS to OWL

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