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In light of the complexity of unfolding disasters, the diversity of rapidly evolving events, the enormous amount of generated information, and the huge pool of casualties, emergency responders (ERs) may be overwhelmed and in consequence poor decisions may be made. In fact, the possibility of transporting the wounded victims to one of several hospitals and the dynamic changes in healthcare resource availability make the decision process more complex. To tackle this problem, we propose a multicriteria decision support service, based on the Analytic Hierarchy Process (AHP) method, that aims to avoid overcrowding and outpacing the capacity of a hospital to effectively provide the best care to victims by finding out the most appropriate hospital that meets the victims’ needs. The proposed approach searches for the most appropriate healthcare institution that can effectively deal with the victims’ needs by considering the availability of the needed resources in the hospital, the victim’s wait time to receive the healthcare, and the transfer time that represents the hospital proximity to the disaster site. The evaluation and validation results showed that the assignment of hospitals was done successfully considering the needs of each victim and without overwhelming any single hospital.

Disaster response requires the cooperation of multiple emergency responder organizations (EROs). However, after‐action reports relating to large‐scale disasters identity communication difficulties among EROs as a major hindrance to collaboration. On the one hand, the use of two‐radio communication, based on multiple orthogonal frequencies and uneven coverage, has been shown to degrade inter‐organization communication. On the other hand, because they reflect different areas of expertise, EROs use differing terminologies, which are difficult to reconcile. These issues lead to ambiguities, misunderstandings, and inefficient exchange of data and information among those involved, which can impede the response process and slow decision making. We, therefore, hypothesize that promoting semantic interoperability across ERO information systems might improve information exchange among stakeholders and thereby allow a more coherent response to the disaster. We propose an ontology‐based messaging service on the basis of the Emergency Data Exchange Language (EDXL) standards. The parties involved will continue to use the terminologies to which they are accustomed, but the system will resolve inconsistencies and thereby enhance mutual understanding among EROs by ensuring semantic translation of the exchanged information. The evaluation of the semantic translation demonstrated the effectiveness and accuracy of the proposed service.

International audience; This work deals with the simulation of complex manipulation tasks in virtual environments. Validating such complex tasks, possibly to be performed under strong geometric constraints, requires considering task and path planning jointly. The contribution of this work focuses on using task-related information at the path planning level. We propose an ontology-based approach to a) model the 3D environment where the simulated task is executed, based on an original multi-level environment model involving higher abstraction level data than the purely geometric models traditionally used, and b) automatically define path planning queries for the primitive ctions of a task plan, together with task-related geometric constraints on these queries. This approach allows the improvement of the state of the art from two points of view. First, our joint task and path planning approach allows the improvement of path planning through better semantic control of the path planning process. Second, if compared to hard-coded geometric constraints, the proposed ontology-based approach introduces a more flexible ay of defining geometric constraints through an inference process, and can be adapted to different applications of manipulation tasks.

Managing complex disaster situations is a challenging task because of the large number of actors involved and the critical nature of the events themselves. In particular, the different terminologies and technical vocabularies that are being exchanged among Emergency Responders (ERs) may lead to misunderstandings. Maintaining a shared semantics for exchanged data is a major challenge. To help to overcome these issues, we elaborate a modular suite of ontologies called POLARISCO that formalizes the complex knowledge of the ERs. Such a shared vocabulary resolves inconsistent terminologies and promotes semantic interoperability among ERs. In this work, we discuss developing POLARISCO as an extension of Basic Formal Ontology (BFO) and the Common Core Ontologies (CCO). We conclude by presenting a real use-case to check the efficiency and applicability of the proposed ontology.

Mobile blood collection provides an opportunity for increasing the number of donors to the fact that the variety of locations facilitates the donation by reducing the distance traveled by donors. In that sense, blood transfusion service in collaboration with blood collection institutions, in order to meet demand, uses a mobile blood collection to maximize the amount of collected blood. However, the traditional blood collection process is non digitalized, which may limit decision-making in the choice of the best location of the mobile center, resource management, and the waiting time that sometimes is too long for donors. This paper addresses the mobile blood collection process by proposing its digitalization through a Cyber-Physical Social System (CPSS) inspired by the centric network approach. The objective of this CPSS is to make the mobile blood collection process more intuitive and set up a data-driven decision.

This chapter proposes Plateforme OperationnelLe d'Actualisation du Renseignement Interservices pour la Securite Civile (POLARISC), an ontology‐based operational emergency response (ER) system for smart cities. In addition, POLARISC offers a set of services for smart cities including alerting smart actors, the evacuation of victims, providing Emergency Detour Route and so on. The chapter illustrates the architecture of POLARISC as a whole system. POLARISC is mainly a software solution that plays the role of mediation between ERs. The modular ontology is the first ontology based on the Basic Formal Ontology (BFO) and Common Core Ontology (CCO) that aims to define the ERs knowledge. Once POLARISC ontology is done and the common operating platform is established, the cited smart cities services can be enabled.