• DocumentCode
    130356
  • Title

    A framework for Dynamic Analytical Risk Management at the emergency scene. From tribal to top down in the risk management maturity model

  • Author

    Krasuski, Adam

  • Author_Institution
    Main Sch. of Fire Service, Warsaw, Poland
  • fYear
    2014
  • fDate
    7-10 Sept. 2014
  • Firstpage
    323
  • Lastpage
    330
  • Abstract
    We present a framework designed for the risk management at the emergency scene. The system that implements the framework is focused on supporting an Incident Commander during the fire and rescue actions. The system is able to assess and manage the risks with the use of sensory data, ontology modelling and reasoning techniques from AI domain. Within the framework we propose the novel approaches for perceiving and modelling the emergency scene, for reasoning, for assessing the state and the relations among the objects at the scene, for assessing the risk mitigation and for communicating the risks to the Incident Commander.
  • Keywords
    emergency management; fires; inference mechanisms; ontologies (artificial intelligence); risk management; AI domain; dynamic analytical risk management; emergency scene; fire actions; incident commander; ontology modelling; reasoning techniques; rescue actions; risk assessment; risk management maturity model; risk mitigation; sensory data; Approximation methods; Cognition; Fires; Integrated circuit modeling; Ontologies; Risk management; Decision Support; Domain Ontology; Fire Service; Risk Management; Sensory Data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on
  • Conference_Location
    Warsaw
  • Type

    conf

  • DOI
    10.15439/2014F371
  • Filename
    6933032