Abstract: The goal of this article is to introduce a plastic architecture of a survey system dedicated to any kind of geographical area that requires to be observed. The principle of this architecture is to allow to change dynamically the set of sensors that is used to monitor the area and also to provide an analyze system able to deal with this unstable set of sensors. Based on Event-Driven Architecture (EDA) technology, such a system does not provide new features compared with traditional set of static sensors connected through cables to dozens of bulbs lighting when a predefined subset of measures is not in the expected range. However, the introduced architecture provides a completely agile and dynamic system of measurement where neither the network of sensors nor the system of measure interpretation is static.

Abstract: The Automated Remote Triage and Emergency Management Information System (ARTEMIS) project seeks to provide situational awareness to all level of commands in order to increase patient survival rate during emergencies. By moving the burden of triage off of the medic and into an automated system, more time will be able to be spent on casualty care rather than assessment. Continual monitoring of responders and casualties will alert medics of critical changes in a patient's health that might normally have gone undetected after a patient is initially triaged. ARTEMIS employs a network of embedded sensors worn by responders and casualties to gather the data required for greater situational awareness and to relay the data back to appropriate levels of command both on the field and in remote locations.

Abstract: Our goal is to develop an Early Warning System for an engineering system with a special interest in applying this to a material recovery facility. This on-going research points out that there is no clear definition of what Early Warning Systems are. A literature search for Early Warning Systems identifies hundred of thousands hits (Buchanan-Smith, 1999; Davies, Buchanan-Smith, Lambert, 1991). Almost all of the references had to do with financial systems for third world countries, tracking the destructive nature of violent conflicts that led to human suffering, or systems for syndromic surveillance. The goal of our research, and of this paper, is to define a framework for creating a specification that can be considered as the basis for the development of any Early Warning System-specifically for engineering systems. Therefore, we will describe Early Warning Systems and its requirements and specifications. Based on specification patterns, we have developed an abstract model of an Early Warning System; and developed an IDEF0 model of a material recovery facility that provides the framework for specifying an Early Warning System. The Early Warning System is then specified using information modeling.

Abstract: In every disaster and crisis, incident time is the enemy, and getting accurate information about the scope, extent, and impact of the disaster is critical to creating and orchestrating an effective disaster response and recovery effort. Decision Support Systems for disaster and crisis situations need to solve the problem of facilitating the broad variety of sensors available today. This includes the research domain of the Internet of Things and data coming from social media. All this data needs to be aggregated and fused, the semantics of the data needs to be understood and the results must be presented to the decision makers in an accessible way. Furthermore, the interaction and integration with risk and crisis management systems are necessary for a better analysis of the situation and faster reaction times. This paper provides an insight into the sensor to decision chain and proposes solutions and technologies for each step.

Abstract: Building collapses often happen unexpectedly and suddenly. Consequently, people are often buried under the debris. What follows is a complicated search by first responders, which is characterized by time pressure and danger. In the research project SORTIE, a modular and UAV-based technical system is being developed to support the first responders in their search efforts. During the first phase of this project, an extensive requirements analysis was conducted with the involvement of end users. This ensures that the developed technology meets the requirements for later use under realistic circumstance. The project consortium has good experience with this operational approach and is in close cooperation with end users who are part of the consortium. In addition to a comprehensive understanding of building collapses and prevailing conditions, the technical partners were also able to identify requirements that they might not have discovered without the involvement of end users and the appropriate methods.

Abstract: Disasters often lead to other kinds of disasters, forming multi-hazards such as landslides, which may be caused by earthquakes, rainfalls, water erosion, among other reasons. Effective detection and management of multihazards cannot rely only on one information source. In this paper, we evaluate a landslide detection system LITMUS, which combines multiple physical sensors and social media to handle the inherent varied origins and composition of multi-hazards. LITMUS integrates near real-time data from USGS seismic network, NASA TRMM rainfall network, Twitter, YouTube, and Instagram. The landslide detection process consists of several stages of social media filtering and integration with physical sensor data, with a final ranking of relevance by integrated signal strength. Applying LITMUS to data collected in October 2013, we analyzed and filtered 34.5k tweets, 2.5k video descriptions and 1.6k image captions containing landslide keywords followed by integration with physical sources based on a Bayesian model strategy. It resulted in detection of all 11 landslides reported by USGS and 31 more landslides unreported by USGS. An illustrative example is provided to demonstrate how LITMUS' functionality can be used to determine landslides related to the recent Typhoon Haiyan.

Abstract: In this paper we describe the approach adopted and experiences gained during a project to develop a general architecture that aims to harness advanced sensor, modelling and Grid technologies to assist emergency responders in tackling emergencies (specifically fire emergencies). Here we focus on the command and control aspects of this architecture, and in particular, on a query-based approach that has been adopted to allow end users to interact with available models of physical and other phenomena. The development of this has provided a number of insights about the use of such models, which along with the approach itself, should be of interest to any considering similar applications.

Abstract: This paper reports on a qualitative study exploring personal crises that emerge during transitions. Personal crises, like crises caused by natural disasters, often lead to new behaviors and opportunities for technology appropriation and design. Through interviews with 14 military veterans re-integrating into civilian society, we find that the veterans' transitions involve several impediments related to translation work--the process through which people make sense of the conflicting rules and norms between former and present social realities. We developed guidelines for the design of new wearable devices that can aid veterans in the translation process by proposing a six-fold schema of design criteria for wearables--detection, nudging, portability/proximity, inconspicuousness, connectivity, and reflection--to empower veterans in managing personal crises, fostering resilience, and creating normalcy. Finally, we develop the concept of identity creep to explicate these translation-breakdowns.

Abstract: Using sensors to collect data at emergency incident sites can facilitate analysis of the logistic operations. This can be used to improve planning and preparedness for new operations. Furthermore, real-time information from the sensors can serve as operational decision support. In this work in progress, we investigate the requirements on the sensors, and on the sensor data, to facilitate such an analysis. Through observations of exercises, the potential of using sensors for data collection is explored, and the requirements are considered. The results show that the potential benefits are significant, especially for tracking patients, and understanding the interaction between the response actors. However, the sensors need to be quite advanced in order to capture the necessary data.

Abstract: Designing mHealth applications for mental health interventions has largely focused on education and patient self-management. Next generation applications must take on more complex tasks, including sensor-based detection of crisis events, search for individualized early warning signs, and support for crisis intervention. This project examines approaches to integrating multiple worn sensors to detect mental health crisis events in US military veterans. Our work has highlighted several practical and theoretical problems with applying technology to evaluation crises in human system, which are often subtle and difficult to detect, as compared to technological or natural crisis events. Humans often do not recognize when they are in crisis and under-report crises to prevent reputational damage. The current project explores preliminary use of the E4 Empatica wristband to characterize acute aggression using a combination of veteran self-report data on anger, professional actors simulating aggressive events, and preliminary efforts to discriminate between crisis data and early warning sign data.