Abstract: Warnings can help prevent damage and harm if they are issued timely and provide information that help responders and population to adequately prepare for the disaster to come. Today, there are many indicator and sensor systems that are designed to reduce disaster risks, or issue early warnings. In this paper we analyze the different systems in the light of the initial decisions that need to be made in the response to sudden onset disasters. We outline challenges of current practices and methods, and provide an agenda for future research.
To illustrate our approach, we present a case study of Typhoon Haiyan. Although meteorological services had issued warnings; relief goods were prepositioned; and responders predeployed, the delivery of aid was delayed in some of the worst hit regions. We argue for an integrated consideration of preparedness and response to provide adequate thresholds for early warning systems that focus on decision-makers needs.

Abstract: Over the last decade the number of operational incidents responded to, has the UK Fire and Rescue Service has diminished by approximately 40% (Knight, 2013). This reduction in incident number and consequential experiential learning opportunities has resulted in a deterioration of incident evaluation skills by the incident commanders. This paper will detail the application of the ?Introspect model? in conjunction with the use of XVR simulation software, within Oxfordshire Fire & Rescue Service (OFRS). The model has been applied in development sessions and during competence assessment over the last 6 years. In 2009, only 45% of those candidates assessed, demonstrated the desired level of competence, compared to over 70% in 2014. The ?Introspect model?focuses on the understanding of decision rationale, striving towards a state of unconscious competence within the crisis decision maker at the incident, to effectively compensate for the skill fade or inexperience, due to diminished incident exposure.

Abstract: Humanitarian Supply Chain Management serves as bridge between needs and aid provided. Flows of goods and information connect the field to headquarters, distribution to procurement, beneficiaries to donors. The problems of decision-making, information sharing and coordination can be studied with this special logistics focus. We present a Value Stream Mapping approach that provides a structure to analyze and understand the problems arising in practice, such as bottlenecks; waiting times; or misaligned procurement and distribution policies. We demonstrate our lean-management approach by using the ongoing Ebola Outbreak in West Africa as Case Study.

Abstract: Experimentation is an essential element to improve crisis management and to assess crisis management tools. Unfortunately, for the moment, real crisis management experimentations are episodic and generally focus on a specific geographical and/or thematic area. This is why the European DRIVER project aims to provide a test-bed platform where crisis management testing and experimentation can be carried out with a mix of live and simulated actions. To achieve this goal, simulation tools have to be identified, described and classified in order to (i) help the user to select tools and models based on the experimentation requirements and (ii) to allow the DRIVER platform to insure exchange information between simulated actions and live actions. This paper focuses on the taxonomy used to classify simulation tools relevant for crisis management. This taxonomy is divided into three main categories of characteristics: (i) business (type/topic of the simulation), (ii) legal (terms of use), (iii) technical (integration within the DRIVER platform and/or other crisis management (simulation) tools).

Abstract: This paper discusses the impact of different dimensions of risk perception on people?s decision to take protective measures against natural hazards. Initial basis of the analysis was the winter storm XAVER which affected huge parts of Northern Europe including Berlin, Germany on 5 December 2013. Preliminary results of a representative online survey within the Berlin population show that affective variables such as fear of severe weather and confidence in weather forecasts showed a significant effect on people?s decision to take protective action. Contrary, high experience of natural hazards did not necessarily lead to action.

Abstract: In this paper, we consider novel information sensemaking methods for search and rescue operations that combine principles of information fusion and collective intelligence in scalable solutions. We will elaborate on several approaches that originated in different areas of information integration, sensor data management, and multi-robot urban search and rescue missions.

Abstract: Despite intense research on decision-making in action, we still know little about when decision-makers rely on deliberate vs. intuitive decision-making in decision situations under complexity and uncertainty. This paper studies decision-making modes (deliberate vs. intuitive) in complex task environments contingent on perceived complexity, experience, and decision style preference. We find that relatively inexperienced decision-makers respond to increases in subjective complexity with an increase in deliberation and tend to follow their decision style preference. Experienced decision-makers are less guided by their decision preference and respond to increases in subjective complexity only minimally. Our paper contributes to a developing stream of research linking decision-making with intra-personal and environmental properties and fosters our understanding of the conditions under which decision-makers rely on intuitive vs. deliberate decision modes. In doing so, we go one step further towards a comprehensive theory of decision-making in action.

Abstract: The dynamically evolving environment of the post-disaster scene?where unpredictable scenarios and uncertain data are commonplace?can bring about considerable complexity into response tasks. The multiplicity and interdependence of approaches to undertaking these tasks may yield many decision alternatives, further complicating the response effort. Additionally, because emergencies are evolving, expectations regarding the post-disaster scene may not match those that are actually encountered. Plans compiled before the disaster may therefore be judged as inadequate, requiring personnel to adjust or even redefine them during the response activities. This paper outlines and illustrates one approach?drawing upon the paradigm of improvisation?for providing management-level response personnel with information and tools to support on-the-fly adaptation of emergency response plans. A case study illustrates the approach application.

Abstract: In case of indoor fire hazards, firefighters face difficulties at assessing the fire situation and evacuating trapped victim inside the building, especially when the fire is big, and the building is unknown to them. On the other hand, modern sensor technologies in smartphone are becoming more advanced, widespread, and can be exploited for helping the firefighting operation. This paper proposes using smartphones as a distributed sensing and computing platform, for supporting firefighters to conduct their mission. The developed solution is based on collecting sensor data from smartphones. A Bayesian network then uses this data to generate a picture of the fire and predict its development. The additional indoor positioning feature make this proposed solution a promising tool to make the firefighter intervention more efficient and fast in order to save more lives.

Abstract: The goal of this article is to introduce a platform (called Agility Service) that gathers and analyses data coming from both crisis response and crisis field by using the principles of Complex Event Processing. As a crisis situation is an unstable phenomenon (by nature or by effect of the applied response), the crisis response may be irrelevant after a while: lack of resources, arrival of a new stakeholder, unreached objectives, over-crisis, etc. Gathering data, analyze and aggregate it to deduce relevant information concerning the current crisis situation, and making this information available to the crisis cell to support decision making: these are the purposes of the described platform. A use case based on the Fukushima's nuclear accident is developed to illustrate the use of the developed prototype.

Abstract: Responding to a large-scale disaster such as an earthquake or hurricane is a collective problem. Human agents are increasingly collaborating with non-human agents (autonomous systems) in attempt to respond to a disaster. IntCris is a prototype intended to bring together interaction for human and non-human agents to aid the decision-making process by focusing on how to facilitate the “correct information to the correct agent” problem as well as encouraging new and agile behaviour. We focus on three categories of information: command, report and personal with a formal grammar to accompany the implementation. The requirements for the software were inspired by real life case studies from Hurricane Katrina, the Fukoshima Nuclear Disaster and Hurricane Sandy. The contribution of this work is to advance technology that brings together HAS (human and autonomous system interaction), in addition to enhancing collective intelligence.

Abstract: Simulator-based training is often more information-intensive and mentally overloading―both for the trainees
and for the exercise staff―than a corresponding live exercise would be. In particular, massive amounts of data
are produced from the simulation core, and these data are often too detailed, and too low-level to be of direct use
for the human eye. The present paper describes a decision support system aimed at helping exercise instructors
maintain an overview of how the exercise is progressing and how the trainees are performing. The paper describes our experience with implementing a real-time, low-key decision support system employing complex event processing, with focus on meeting the special technical challenges that are associated with the novel approach of implementing high-end, real-time processing on a low-power, 6-inch, mobile Android platform.