456 research outputs found

    An automated lifeboat, manifesting embarkation system (ALMES): the utilization of RFID/NFC in passenger manifestation during ship evacuation

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    Personalized Alert Notifications and Evacuation Routes in Indoor Environments

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    The preparedness phase is crucial in the emergency management process for reaching an adequate level of readiness to react to potential threats and hazards. During this phase, emergency plans are developed to establish, among other procedures, evacuation and emergency escape routes. Information and Communication Technologies (ICT) can support and improve these procedures providing appropriate, updated and accessible information to all people in the affected zone. Current emergency management and evacuation systems do not adapt information to the context and the profile of each person, so messages received in the emergency might be useless. In this paper, we propose a set of criteria that ICT-based systems could achieve in order to avoid this problem adapting emergency alerts and evacuation routes to different situations and people. Moreover, in order to prove the applicability of such criteria, we define a mechanism that can be used as a complement of traditional evacuation systems to provide personalized alerts and evacuation routes to all kinds of people during emergency situations in working places. This mechanism is composed by three main components: CAP-ONES for notifying emergency alerts, NERES for defining emergency plans and generating personalized evacuation routes, and iNeres as the interface to receive and visualize these routes on smartphones. The usability and understandability of proposed interface has been assessed through a user study performed in a fire simulation in an indoor environment. This evaluation demonstrated that users considered iNeres easy to understand, to learn and to use, and they also found very innovative the idea to use smartphones as a support for escaping instead of static signals on walls and doors

    Information Systems for Supporting Fire Emergency Response

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    Despite recent work on information systems, many first responders in emergency situations are unable to develop sufficient understanding of the situation to enable them to make good decisions. The record of the UK Fire and Rescue Service (FRS) has been particularly poor in terms of providing the information systems support to the fire fighters decision-making during their work. There is very little work on identifying the specific information needs of different types of fire fighters. Consequently, this study has two main aims. The first is to identify the information requirements of several specific members of the FRS hierarchy that lead to better Situation Awareness. The second is to identify how such information should be presented. This study was based on extensive data collected in the FRS brigades of three counties and focused on large buildings having a high-risk of fire and four key fire fighter job roles: Incident Commander, Sector Commander, Breathing Apparatus Entry Control Officer and Breathing Apparatus Wearers. The requirements elicitation process was guided by a Cognitive Task Analysis (CTA) tool: Goal Directed Information Analysis (GDIA), which was developed specifically for this study. Initially appropriate scenarios were developed. Based on the scenarios, 44 semi-structured interviews were carried out in three different elicitation phases with both novice and experienced fire fighters. Together with field observations of fire simulation and training exercises, fire and rescue related documentation; a comprehensive set of information needs of fire fighters was identified. These were validated through two different stages via 34 brainstorming sessions with the participation of a number of subject-matter experts. To explore appropriate presentation methods of information, software mock-up was developed. This mock-up is made up of several human computer interfaces, which were evaluated via 19 walkthrough and workshop sessions, involving 22 potential end-users and 14 other related experts. As a result, many of the methods used in the mock-up were confirmed as useful and appropriate and several refinements proposed. The outcomes of this study include: 1) A set of GDI Diagrams showing goal related information needs for each of the job roles with the link to their decision-making needs, 2) A series of practical recommendations suitable for designing of human computer interfaces of fire emergency response information system, 3) Human computer interface mock-ups for an information system to enhance Situation Awareness of fire fighters and 4) A conceptual architecture for the underlying information system. In addition, this study also developed an enhanced cognitive task analysis tool capable of exploring the needs of emergency first responders. This thesis contributes to our understanding of how information systems could be designed to enhance the Situation Awareness of first responders in a fire emergency. These results will be of particular interest to practicing information systems designers and developers in the FRS in the UK and to the wider academic community

    Agent-Based Simulation and Analysis of Human Behavior towards Evacuation Time Reduction

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    Human factors play a significant part in the time taken to evacuate following an emergency. An agent-based simulation, using the Prometheus methodology (SEEP 1.5), has been developed to study the complex behavior of human (the ‘agents’) in high-rise buildings evacuations. In the case of hostel evacuations, simulation results show that pre-evacuation phase takes 60.4% of Total Evacuation Time (TET). The movement phase (including queuing time) only takes 39.6% of TET. From sensitivity analysis, it can be shown that a reduction in TET by 41.2% can be achieved by improving the recognition phase. Exit signs have been used as smart agents. Expanded Ant Colony Optimization (ACO) was used to determine the feasible evacuation routes. Both the ‘familiarity of environment’ wayfinding method, which is the most natural method, and the ACO wayfinding, have been simulated and comparisons made. In scenario 1, where there were no obstacles, both methods achieved the same TET. However, in scenario 2, where an obstacle was present, the TET for the ACO wayfinding method was 21.6% shorter than that for the ‘familiarity’ wayfinding method

    A holistic model of emergency evacuations in large, complex, public occupancy buildings

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    Evacuations are crucial for ensuring the safety of building occupants in the event of an emergency. In large, complex, public occupancy buildings (LCPOBs) these procedures are significantly more complex than the simple withdrawal of people from a building. This thesis has developed a novel, holistic, theoretical model of emergency evacuations in LCPOBs inspired by systems safety theory. LCPOBs are integral components of complex socio-technical systems, and therefore the model describes emergency evacuations as control actions initiated in order to return the building from an unsafe state to a safe state where occupants are not at risk of harm. The emergency evacuation process itself is comprised of four aspects - the movement (of building occupants), planning and management, environmental features, and evacuee behaviour. To demonstrate its utility and applicability, the model has been employed to examine various aspects of evacuation procedures in two example LCPOBs - airport terminals, and sports stadiums. The types of emergency events initiating evacuations in these buildings were identified through a novel hazard analysis procedure, which utilised online news articles to create events databases of previous evacuations. Security and terrorism events, false alarms, and fires were found to be the most common cause of evacuations in these buildings. The management of evacuations was explored through model-based systems engineering techniques, which identified the communication methods and responsibilities of staff members managing these events. Social media posts for an active shooting event were analysed using qualitative and machine learning methods to determine their utility for situational awareness. This data source is likely not informative for this purpose, as few posts detail occupant behaviours. Finally, an experimental study on pedestrian dynamics with movement devices was conducted, which determined that walking speeds during evacuations were unaffected by evacuees dragging luggage, but those pushing pushchairs and wheelchairs will walk significantly slower.Open Acces
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