Generic application driven situation awareness via ontological situation recognition

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Situation recognition and interpretation based on multisensor data is an important research challenge in the situation awareness field. Existing research has developed techniques concerned with accurate and reliable situation recognition via sensor driven detection of events in an environment. However, real world applications of situation awareness require perception of a situation's meaning, knowledge of expected changes and their relevance to environments inhabitants. Recognizing the significance and implications of situations in complex real world scenarios is challenging, but is essential for designing applications for real world environments. This paper presents a novel knowledge driven approach to situation awareness. Within it we extend established data driven methods of situation recognition by utilizing domain knowledge across the entire situation life cycle. We utilize ontologies for explicit representation of environmental and application context as well as situation modeling. We explore the link between low-level environment context and high-level application knowledge using a generic situation model. We exploit semantic reasoning to provide situation recognition and interpretation and demonstrate delivery of application oriented situation awareness in a smart environment. Finally, a case study-based scenario is utilized in order to demonstrate the system's operation.
LanguageEnglish
Title of host publicationUnknown Host Publication
Pages131-137
Number of pages7
DOIs
Publication statusE-pub ahead of print - 23 Jun 2016
Event2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA) - San Diego, CA
Duration: 23 Jun 2016 → …

Conference

Conference2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA)
Period23/06/16 → …

Fingerprint

Ontology
Life cycle
Semantics
Sensors

Keywords

  • Context awareness
  • knowledge representation
  • ontology
  • situation awareness

Cite this

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title = "Generic application driven situation awareness via ontological situation recognition",
abstract = "Situation recognition and interpretation based on multisensor data is an important research challenge in the situation awareness field. Existing research has developed techniques concerned with accurate and reliable situation recognition via sensor driven detection of events in an environment. However, real world applications of situation awareness require perception of a situation's meaning, knowledge of expected changes and their relevance to environments inhabitants. Recognizing the significance and implications of situations in complex real world scenarios is challenging, but is essential for designing applications for real world environments. This paper presents a novel knowledge driven approach to situation awareness. Within it we extend established data driven methods of situation recognition by utilizing domain knowledge across the entire situation life cycle. We utilize ontologies for explicit representation of environmental and application context as well as situation modeling. We explore the link between low-level environment context and high-level application knowledge using a generic situation model. We exploit semantic reasoning to provide situation recognition and interpretation and demonstrate delivery of application oriented situation awareness in a smart environment. Finally, a case study-based scenario is utilized in order to demonstrate the system's operation.",
keywords = "Context awareness, knowledge representation, ontology, situation awareness",
author = "Ryan Pearson and Mark Donnelly and Jun Liu and Leo Galway",
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}

Pearson, R, Donnelly, M, Liu, J & Galway, L 2016, Generic application driven situation awareness via ontological situation recognition. in Unknown Host Publication. pp. 131-137, 2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 23/06/16. https://doi.org/10.1109/COGSIMA.2016.7497800

Generic application driven situation awareness via ontological situation recognition. / Pearson, Ryan; Donnelly, Mark; Liu, Jun; Galway, Leo.

Unknown Host Publication. 2016. p. 131-137.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Situation recognition and interpretation based on multisensor data is an important research challenge in the situation awareness field. Existing research has developed techniques concerned with accurate and reliable situation recognition via sensor driven detection of events in an environment. However, real world applications of situation awareness require perception of a situation's meaning, knowledge of expected changes and their relevance to environments inhabitants. Recognizing the significance and implications of situations in complex real world scenarios is challenging, but is essential for designing applications for real world environments. This paper presents a novel knowledge driven approach to situation awareness. Within it we extend established data driven methods of situation recognition by utilizing domain knowledge across the entire situation life cycle. We utilize ontologies for explicit representation of environmental and application context as well as situation modeling. We explore the link between low-level environment context and high-level application knowledge using a generic situation model. We exploit semantic reasoning to provide situation recognition and interpretation and demonstrate delivery of application oriented situation awareness in a smart environment. Finally, a case study-based scenario is utilized in order to demonstrate the system's operation.

AB - Situation recognition and interpretation based on multisensor data is an important research challenge in the situation awareness field. Existing research has developed techniques concerned with accurate and reliable situation recognition via sensor driven detection of events in an environment. However, real world applications of situation awareness require perception of a situation's meaning, knowledge of expected changes and their relevance to environments inhabitants. Recognizing the significance and implications of situations in complex real world scenarios is challenging, but is essential for designing applications for real world environments. This paper presents a novel knowledge driven approach to situation awareness. Within it we extend established data driven methods of situation recognition by utilizing domain knowledge across the entire situation life cycle. We utilize ontologies for explicit representation of environmental and application context as well as situation modeling. We explore the link between low-level environment context and high-level application knowledge using a generic situation model. We exploit semantic reasoning to provide situation recognition and interpretation and demonstrate delivery of application oriented situation awareness in a smart environment. Finally, a case study-based scenario is utilized in order to demonstrate the system's operation.

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