Situation awareness modeling for emergency management on offshore platforms
| Autor: | Faisal Khan, Jennifer Smith, Brian Veitch, Syed Nasir Danial |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Situation awareness Exploit Computer science 02 engineering and technology computer.software_genre lcsh:QA75.5-76.95 Markov Logic Networks Application 0502 economics and business 0202 electrical engineering electronic engineering information engineering lcsh:Information theory Agent situation awareness Markov logic network Situation modeling Emergency management business.industry Repertoire 05 social sciences Situations Cognition lcsh:Q350-390 Risk analysis (engineering) Virtual machine Emergency evacuation 020201 artificial intelligence & image processing lcsh:Electronic computers. Computer science business computer 050203 business & management |
| Zdroj: | Human-Centric Computing and Information Sciences, Vol 9, Iss 1, Pp 1-26 (2019) |
| ISSN: | 2192-1962 |
| Popis: | Situation awareness is the first and most important step in emergency management. It is a dynamic step involving evolving conditions and environments. It is an area of active research. This study presents a Markov Logic Network to model SA focusing on fire accidents and emergency evacuation. The model has been trained using empirical data obtained from case studies. The case studies involved human participants who were trained for responding to emergencies involving fire and smoke using a virtual environment. The simulated (queried) and empirical findings are reasonably consistent. The proposed model enables implementing an agent that exploits environmental cues and cognitive states to determine the type of emergency currently being faced. Considering each emergency type as a situation, the model can be used to develop a repertoire of situations for agents so that the repertoire can act as an agent’s experience for later decision-making. |
| Databáze: | OpenAIRE |
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