A Conceptual Framework and a Suite of Tools to Support Crisis Management

This article aims at describing an approach to support crisis management. The main idea is to use an original vision of Big-Data to manage the question of collaboration issues in crisis response. On the one hand, this article introduces a general framework that structures the methodology applied in our approach. This framework includes several technical and business dimensions and embeds scientific results that are presented in this article or have been described in previous articles. On the other hand, the resulting implemented suite of tools is also presented with regards to the conceptual framework. Finally, in order to emphasize all the main features described in this article, both the framework and the suite of tools are illustrated and put into action through a scenario extracted from a real exercise

A Framework for Virtual Training in Crisis Context and a Focus on the Animation Component: The Gamemaster Workshop

Critical infrastructures, historical places, and sensitive buildings are vulnerable to crises, from natural to man-made disasters. Public institutions and practitioners have to train, before the occurrence of a major event, to be prepared to respond to the crisis. These sites are difficult to vacate just to perform exercises. To propose training adapted to the needs the trainer have to create an exercise dedicated to the aimed skills. Stakeholders responding to high-risk situations are asking for new ways to train and compensate for the weaknesses of existing training approaches. The research work presented in this paper concerns the design of immersive environments that can be used to create, implement and simulate crisis scenarios to improve collaborative training

A new emergency decision support system: the automatic interpretation and contextualisation of events to model a crisis situation in real-time

This paper studies, designs and implements a new type of emergency decision support system that aims to improve the decision-making of emergency managers in crisis situations by connecting them to new, multiple data sources. The system combines event-driven and model-driven architectures and is dedicated to crisis cells. After its implementation, the system is evaluated using a realistic crisis scenario, in terms of its user interfaces, its ability to interpret data in real time and its ability to manage the 4Vs of Big Data. The input events correspond to traffic measurements, water levels, water flows, water predictions and flow predictions made available by French official services. The main contributions of this study are: (i) the connection between a complex event processing engine and a graph database containing the model of the crisis situation and (ii) the continuous updating of a common operational picture for the benefit of emergency managers. This study could be used as a framework for future research works on decision support systems facing complex, evolving situations

Real-time data exploitation supported by model- and event-driven architecture to enhance situation awareness, application to crisis management

An effective crisis response requires up-to-date information. The crisis cell must reach for new, external, data sources. However, new data lead to new issues: their volume, veracity, variety or velocity cannot be managed by humans only, especially under high stress and time pressure. This paper proposes (i) a framework to enhance situation awareness while managing the 5Vs of Big Data, (ii) general principles to be followed and (iii) a new architecture implementing the proposed framework. The latter merges event-driven and model-driven architectures. It has been tested on a realistic flood scenario set up by official French services

Synthesis and performance of a thermosetting resin: Acrylated epoxidized soybean oil curing with a rosin‐based acrylamide

A synthesized rosin‐based polymeric monomer, N‐dehydroabietic acrylamide (DHA‐AM), was introduced into an acrylated epoxidized soybean oil (AESO)/DHA‐AM system to afford a thermosetting resin through thermocuring. Different molar ratios of the thermosetting AESO/DHA‐AM samples were obtained through curing in the presence of an initiator, and the curing processes of the AESO/DHA‐AM systems were evaluated by differential scanning calorimetry. The structures and performances of the resulting thermosets were characterized by Fourier transform infrared spectroscopy, dynamic mechanical analysis, elemental analysis, thermogravimetric analysis, and contact angle (θ) analysis. The analyses showed that with increasing content of DHA‐AM introduced into the copolymer, the storage modulus, glass‐transition temperature, thermal stability, and θ values of the cured samples all increased. Moreover, the copolymers changed from hydrophilic materials to hydrophobic materials. The results also demonstrate that the rosin acid derivatives showed comparable properties to those of reported petroleum‐based rigid compounds for the preparation of soybean‐oil‐based thermosets. The presence of DHA‐AM moieties in the composite structures could expand the use of AESO into the development of heat‐resistant and hydrophobic materials. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 44545.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135053/1/app44545_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135053/2/app44545.pd

An AI framework and a metamodel for collaborative situations: Application to crisis management contexts

Identifying, designing, deploying and maintaining accurate collaborative networks of organizations (e.g. responders in a crisis situation) are key activities in nowadays ecosystems. However, there is a lack regarding formal approaches dedicated to characterize collaborative networks of organizations. Formal descriptions of collaborative situations, that could be used, transformed, computed and exploited would be of great benefit for the quality of such collaborative networks. This article presents a model‐based AI framework for describing collaborative situations and the associated formal metamodel dedicated to be instantiated to characterize collaborative situations in a very wide range of application domains. This metamodel (describing collaborative situation between organizations) is structured according to four complementary dimensions: the context (social, physical and geographical environment), the partners (the involved organizations, their capabilities resources and relations), the objectives (the aims of the network, the goals to be the achieved and the risks to avoid, etc.) and the behaviour (the collaborative processes to be implemented by the partners to achieve the objectives in the considered context). Besides, this metamodel can be extended for some precise application domains. This article focuses on this mechanism in the specific context of crisis management

Interprétation automatique de données hétérogènes pour la modélisation de situations collaboratives : application à la gestion de crise

The present work is applied to the field of French crisis management, and specifically to the crisis response phase which follows a major event, like a flood or an industrial accident. In the aftermath of the event, crisis cells are activated to prevent and deal with the consequences of the crisis. They face, in a hurry, many difficulties. The stakeholders are numerous, autonomous and heterogeneous, the coexistence of contingency plans favours contradictions and the interconnections of networks promotes cascading effects. These observations arise as the volume of data available continues to grow. They come, for example, from sensors, social media or volunteers on the crisis theatre. It is an occasion to design an information system able to collect the available data to interpret them and obtain information suited to the crisis cells. To succeed, it will have to manage the 4Vs of Big Data: the Volume, the Variety and Veracity of data and information, while following the dynamic (velocity) of the current crisis. Our literature review on the different parts of this architecture enables us to define such an information system able to (i) receive different types of events emitted from data sources both known and unknown, (ii) to use interpretation rules directly deduced from official business rules and (iii) to structure the information that will be used by the stake-holders. Its architecture is event-driven and coexists with the service oriented architecture of the software developed by the CGI laboratory. The implemented system has been tested on the scenario of a 1/100 per year flood elaborated by two French forecasting centres. The model describing the current crisis situation, deduced by the proposed information system, can be used to (i) deduce a crisis response process, (ii) to detect unexpected situations, and (iii) to update a COP suited to the decision-makers.Les travaux présentés dans ce manuscrit s’appliquent au domaine de la gestion de crise française, et notamment à la phase de réponse qui suit un évènement majeur, comme une crue ou un accident industriel. Suite à l’évènement, des cellules de crise sont activées pour prévenir et traiter les conséquences de la crise. Elles font face, dans l’urgence, à de nombreuses difficultés. Les parties-prenantes sont nombreuses, autonomes et hétérogènes, la coexistence de plans d’urgence engendre des contradictions et des effets en cascade se nourrissent des interconnexions entre réseaux. Ces constats arrivent alors que les données disponibles sur les réseaux informatiques ne cessent de se multiplier. Elles sont, par exemple, émises par des capteurs de mesures, sur des réseaux sociaux, ou par des bénévoles. Ces données sont l’occasion de concevoir un système d’information capable de les collecter pour les interpréter en un ensemble d’information formalisé, utilisable en cellule de crise. Pour réussir, les défis liés aux 4Vs du Big data doivent être relevés en limitant le Volume, unifiant (la Variété) et améliorant la Véracité des données et des informations manipulées, tout en suivant la dynamique (Vélocité) de la crise en cours. Nos états de l’art sur les différentes parties de l’architecture recherchée nous ont permis de définir un tel système d’information. Ce dernier est aujourd’hui capable de (i) recevoir plusieurs types d’évènements émis de sources de données connues ou inconnues, (ii) d’utiliser des règles d’interprétations directement déduites de règles métiers réelles et (iii) de formaliser l’ensemble des informations utiles aux parties-prenantes. Son architecture fait partie des architectures orientées évènements, et coexiste avec l’architecture orientée services du logiciel développé par le laboratoire Centre de Génie Industriel (CGI). Le système d’information ainsi implémenté a pu être éprouvé sur un scénario de crue majeure en Loire Moyenne, élaboré par deux Services de Prévision des Crues (SPC) français. Le modèle décrivant la situation de crise courante, obtenu par le système d’information proposé, peut être utilisé pour (i) déduire un processus de réponse à la crise, (ii) détecter des imprévus ou (iii) mettre à jour une représentation de la situation en cellule de crise