Search

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.

Current urban mobility trends go beyond infrastructure investments and integrating new technologies, reflecting new user requirements and regulations, and the increasingly rigorous and sustainable governance. Designing an urban mobility system and assessing its sustainability require a flexible holistic approach considering the complete life cycle of the system and interdependencies between its components. This paper proposes a novel methodological framework based on system engineering tools, aimed at helping public authorities designing and deploying new urban projects, accounting for the entire life cycle of the mobility system, evolving requirements of users, and sustainability. The main goal is to validate the proposed framework by simulations. A realistic case study employing the new framework showed its advantages, consisting of solving problems in a manner comparable to other methodologies, but adding flexibility in managing different data inaccessible to urban managers before allowing for defining effective urban mobility policies.

International audience; In order to face an increasing economic competition, industrial manufacturers wish to reduce the time and cost of product development. Furthermore, up-to-date products are more and more integrated, and must be assembled, disassembled or maintained under potentially very strong geometric constraints. In the context of Industry 4.0, manufacturers are therefore expressing the desire to validate all the tasks related to their products lifecycles, from design stage on, by simulation using a digital mock-up, and before building the physical prototypes. A key issue is then to find a trajectory, a movement, to show the feasibility of the simulated scenarios. Automatic path planning algorithms, developed by the robotics community from the 1980s on, have been widely used for this purpose. In this paper, we intend to improve the relevance of the trajectories proposed by such algorithms and the associated computation times. To do so, we consider: a) the use of path planning algorithms or of combinations of these; b) the involvement for the environment modelling of data with a higher abstraction level than the purely geometric data traditionally used; and c) the representation of the knowledgerelated to the task to be performed by using ontologies. The approaches developed and associated improvements of the state of the art are validated experimentally through the simulation of highly geometrically constrained manipulation tasks.

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.

The allocation of water resources between different users is a hard task for water managers because they must deal with conflicting objectives. The main objective is to obtain the most accurate distribution of the resource and the associated circulating flows through the system. This induces the need for a river basin optimization model that provides optimized results. This article presents a network flow optimization model to solve the water allocation problem in water resource systems. Managing a water system consists in providing water in the right proportion, at the right place and at the right time. Time expanded network allows to take into consideration the temporal dimension in the decision making. Since linear cost functions on arcs present many limitations and are not realistic, quadratic convex cost functions on arcs are considered here. The optimization algorithm developed herein extend the cycle canceling algorithm developed for linear cost functions. The methodology is applied to manage the three reservoirs of La Haute-Vilaine’s watershed located in the north west of France to protect a three vulnerable areas from flooding. The results obtained with the algorithm are compared to a reference scenario which consists in considering reservoirs transparent. The results show that the algorithm succeeds in managing the reservoir releases efficiently and keeps the flow rates below the vigilance flow in the vulnerable areas.

Purpose With the rising concern of safety, health and environmental performance, eco-labeled product and service are becoming more and more popular. However, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. The purpose of this paper is to propose a decision support platform aiming at further improvement and acceleration of the eco-labeling process in order to democratize a broader application and certification of eco-labels, also to consolidate the credibility and validity of eco-labels. Design/methodology/approach This decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to an official eco-label criteria documentation. Findings Through standard Resource Description Framework and Web Ontology Language ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other applications. A case study of laundry detergent eco-labeling process is also presented in this paper. Originality/value The authors present a reasoning methodology based on inference with Semantic Web Rule Language (SWRL) rules which allows decision making with explanation.

Flood is a natural phenomenon, usually sudden and a calamitous event with devastating consequences and serious effects on the society, the environment and the economy. Thus, more and more research efforts have been carried out and many solutions have been implemented in the aim to control their impact. In order to divert or block the excess water due to flooding, hydraulic structures such as retaining walls, retention ponds, dams, etc. are necessary and require the use of operation strategies to manage the complex water system. In this paper, a flood decrease strategy based on the graph theory is proposed in order to manage the control of the water storage and release from reservoirs along the river. This river-Tanks system is modeled by a dynamic network and the management problem is formulated as a minimum cost dynamic flow problem with some additional constraints. Then, this main problem is reduced into a set of low dimensional dynamic sub-problems, for which the dynamic network is extended into a static network solved using a heuristic method. Thereby this single commodity flow problem with additional constraints is modeled as a mixed integer linear program. Finally, the program is combined with a specialized hydraulic simulator to simulate the water transfer and the exchange between the reservoirs and the river. The proposed approach was applied on the Bastillac area and results obtained for a 100-year flood case are given, illustrating that the strategy ensures a weak downstream flow peak and a reduced impact.

International audience; The origins of water pollution are numerous, they cause alterations due to their high load of dissolved substances, micropollutants and toxic substances. Many studies have focused on the implementation of remediation measures for these types of pollution. In this work, the case of rivers subject to accidental pollution and the use of reservoirs for its remediation is studied. Two strategies are implemented: the storage of pollutants in the reservoirs and the dilution of pollutants by injecting in the river clear water from reservoirs. Both methods are applied to a river with one reservoir, and their impacts are studied for different flow levels.