INTELLECTUAL INFORMATION TECHNOLOGIES IN THE ACTIVITIES OF THE EMERGENCY RESCUE SERVICE

The paper considers the features of the use of intelligent information technologies in the process of the emergency rescue service of the enterprise. To improve the efficiency of the rescue services, it is necessary to carry out strategic planning and management, which would be designed to prevent the occurrence of an emergency (emergency). Effective subsystems of emergency proactive planning should not only predict the occurrence of possible emergencies, but also provide for appropriate preventive measures, and emphasis should be placed on eliminating the underlying causes, not the emerging consequences. The change of modes in the event of an emergency can be effectively implemented through the deployment of a technologically secured situational center. Decisions in emergency situations are made in various operational situations, including crisis, and in extremely limited time. Nevertheless, they must be taken in a timely manner, be as reasonable as possible, and ensure the fullest and most effective use of available opportunities. Decision-making processes can be based on the personal experience of participants in the management process. As you carry out your professional activity, experience is formed, which subsequently allows you to perform some tasks much faster and more efficiently. To gain experience, it is proposed to use a knowledge management system based on ontology. In order to ensure maximum awareness of the management of the situation, it is proposed to use the expert system of the situation center. (ES SC) The ES of the situational center of the authorities can significantly improve the efficiency of management processes and provides information support for strategic and tactical management decision-making. The ES should implement tools for a comprehensive and operational assessment of the state of the management object and situational analysis of the identified problems

Organizing for Emergencies - Issues in Wildfire Fighting in Croatia

Croatia’s accession to the European Union implies inevitable changes in the national emergency management system. New requirements for adjustment in accordance with the EU standards and practices also apply to the fire-services organization. Harmonious functioning of a large number of relatively autonomous organizations related to the National Protection and Rescue Directorate necessitates clear decision-making authority and coordination mechanisms as well as a high level of interoperability and core competencies development. This paper gives an overview of the Croatian fire protection organization along with its accompanying legislation, followed by an analysis of identified problems, especially those concerning fighting of wildfire. In our research a survey questionnaire comprised of Likert-scale items was used to assess the attitudes and experiences of trained fire department members. The respondents reported a relatively low evaluation of effectiveness and appropriateness of the following key fire service attributes: organizational structure, legislation and firefighting logistics support. From the obtained results guidelines can be drawn for possible redesign of the emergency management organization, especially those concerning the fire protection service

A predictive decision support system for coronavirus disease 2019 response management and medical logistic planning

Objective: Coronavirus disease 2019 demonstrated the inconsistencies in adequately responding to biological threats on a global scale due to a lack of powerful tools for assessing various factors in the formation of the epidemic situation and its forecasting. Decision support systems have a role in overcoming the challenges in health monitoring systems in light of current or future epidemic outbreaks. This paper focuses on some applied examples of logistic planning, a key service of the Earth Cognitive System for Coronavirus Disease 2019 project, here presented, evidencing the added value of artificial intelligence algorithms towards predictive hypotheses in tackling health emergencies. Methods: Earth Cognitive System for Coronavirus Disease 2019 is a decision support system designed to support healthcare institutions in monitoring, management and forecasting activities through artificial intelligence, social media analytics, geo- spatial analysis and satellite imaging. The monitoring, management and prediction of medical equipment logistic needs rely on machine learning to predict the regional risk classification colour codes, the emergency rooms attendances, and the fore- cast of regional medical supplies, synergically enhancing geospatial and temporal dimensions. Results: The overall performance of the regional risk colour code classifier yielded a high value of the macro-average F1-score (0.82) and an accuracy of 85%. The prediction of the emergency rooms attendances for the Lazio region yielded a very low root mean square error (<11 patients) and a high positive correlation with the actual values for the major hos- pitals of the Lazio region which admit about 90% of the region’s patients. The prediction of the medicinal purchases for the regions of Lazio and Piemonte has yielded a low root mean squared percentage error of 16%. Conclusions: Accurate forecasting of the evolution of new cases and drug utilisation enables the resulting excess demand throughout the supply chain to be managed more effectively. Forecasting during a pandemic becomes essential for effective government decision-making, managing supply chain resources, and for informing tough policy decisions

An Optimisation-based Framework for Complex Business Process: Healthcare Application

The Irish healthcare system is currently facing major pressures due to rising demand, caused by population growth, ageing and high expectations of service quality. This pressure on the Irish healthcare system creates a need for support from research institutions in dealing with decision areas such as resource allocation and performance measurement. While approaches such as modelling, simulation, multi-criteria decision analysis, performance management, and optimisation can – when applied skilfully – improve healthcare performance, they represent just one part of the solution. Accordingly, to achieve significant and sustainable performance, this research aims to develop a practical, yet effective, optimisation-based framework for managing complex processes in the healthcare domain. Through an extensive review of the literature on the aforementioned solution techniques, limitations of using each technique on its own are identified in order to define a practical integrated approach toward developing the proposed framework. During the framework validation phase, real-time strategies have to be optimised to solve Emergency Department performance issues in a major hospital. Results show a potential of significant reduction in patients average length of stay (i.e. 48% of average patient throughput time) whilst reducing the over-reliance on overstretched nursing resources, that resulted in an increase of staff utilisation between 7% and 10%. Given the high uncertainty in healthcare service demand, using the integrated framework allows decision makers to find optimal staff schedules that improve emergency department performance. The proposed optimum staff schedule reduces the average waiting time of patients by 57% and also contributes to reduce number of patients left without treatment to 8% instead of 17%. The developed framework has been implemented by the hospital partner with a high level of success

Physical, Economical, Infrastructural and Social Flood Risk -- Vulnerability Analyses in GIS

An exhaustive knowledge of flood risk, vulnerability and exposure in different spatial locations is essential for developing an effective flood mitigation strategy for a watershed. In the present study, a flood risk-vulnerability analysis is performed. All four components of flood vulnerability: (a) physical; (b) economic; (c) infrastructure and (d) social, are evaluated individually using a Geographic Information System (GIS) environment. The proposed methodology estimates the impact on infrastructure vulnerability due to inundation of critical facilities, emergency service stations, and road bridges. The components of vulnerability are combined to determine the overall vulnerability. The patterns of land use and soil type are considered as two major components of flood exposure. Flood hazard maps, overall vulnerability and exposure are used to finally compute the flood risk at different locations in the watershed. The proposed methodology is implemented to six major damage centers in the Upper Thames River watershed, located in south-western Ontario of Canada to assess the flood risk. A web-based information system is developed for systematic presentation of the flood risk, vulnerability and exposures by postal code regions or Forward Sortation Areas (FSAs). The system is designed to provide support for different users, i.e., general public, decision-makers and water management professionals. An interactive analysis tool is developed within the web-based information system to assist in evaluation of the flood risk in response to a change in land use pattern.https://ir.lib.uwo.ca/wrrr/1019/thumbnail.jp

Assessing the efficiency and the criticality of the elements belonging to a complex territorial system subject to natural hazards

International audienceThe effects of natural hazards can be mitigated by the use of proper "pre-event" interventions on "key" elements of the territory, that is on elements that are mostly vulnerable to a given catastrophic scenario and whose loss of functionality can cause damages on people, property and environment. In this respect, methodologies and tools should be studied to support decision makers in the analysis of a territory, in order to point out such elements. In this work, vulnerability is taken into account under two aspects: "physical vulnerability", which measures the propensity of a territorial element to suffer damage when subject to an external stress corresponding to the occurrence of a natural phenomenon; "functional vulnerability", which measures the propensity of a territorial element to suffer loss in functionality, even when that is caused by the loss of functionality of other territorial elements. In the proposed modeling approach, vulnerability is represented through the use of a graph-based formalization. A territorial system is represented as a complex set of elements or sub-systems. Such elements have differentiated and dedicated functions, and they may be functionally interconnected among them. In addition, vulnerability is defined through the use of two different variables, namely the criticality and the efficiency. Focusing the attention on the temporal phases corresponding to the occurrence of a calamitous event, the first one measures the service demand of an element, whereas the efficiency is a measure of the service that can be offered by such an element. The approach presented is largely independent from the natural risk considered. Besides, the tools introduced for the vulnerability analysis of the territorial system can also be used to formalize decision problems relevant to the location of the available resources for emergency management. A specific case study pertaining to the hydrological risk in the Val di Vara area (Italy) is presented

Integrated Management of Emergency Vehicle Fleet

The growing public concerns for safety and the advances in traffic management systems, that have made the availability of real-time traffic information a reality, have created an opportunity to build integrated decision support systems that can improve the coordination and sharing of information between agencies that are responsible for public safety and security and transportation agencies to provide more efficient Emergency Response Service. In an Emergency Response System, reduction of the duration of response time can yield substantial benefits. The response time plays a crucial role in minimizing the adverse impacts: fatalities and loss of property can be greatly reduced by reducing the response time for emergencies. In this dissertation, we have developed an integrated model that can assist emergency response fleet dispatchers in managing the fleet. This model can help reduce the response time and improve service level by specifically accounting for the following: Vehicle Deployment: given real-time information about the status of the emergency response fleet, traffic information and the status of emergency calls, select proper fleet assignment schemes that satisfy various operation requirements. Vehicle Routing: given real-time traffic information, provide real-time route guidance for drivers of dispatched vehicles. This goal is achieved by applying various shortest path algorithms into the solution procedure. Planning and Evaluation: given the status of the fleet and the frequency of emergency calls in various areas of a region, the model can help evaluate the performance of the current system and help plan for potential sites for the relocation of vehicles and allocate an appropriate fleet of vehicles to these sites. The vehicle deployment problem is formulated as an integer optimization problem. Since this problem has been shown to be NP-hard and because of the nature of emergency response, we developed heuristics which can provide quality solutions with short computational times. Several test algorithms are proposed to solve the emergency response vehicle deployment problem. Different methods for obtaining lower bounds for the value of objective function are analyzed in this dissertation. To evaluate the performance of the system under various scenarios, a simulation model is developed. The simulation system is calibrated based on real-world data. The results of simulation and analysis show the proposed system can effectively improve the emergency response service level. Application of this model in facility allocation illustrates its usage in other relevant operational scenarios

Urban flood simulation and integrated flood risk management

Climate change induces the probability of occurring natural disasters; e.g. floods, Sea Level Rise, Green House Gases. Flood is considered one of the most dangerous phenomena that tremendously and dramatically threatening the human being and environment worldwide. Rapid urban growth, demographic explosion, and unplanned land uses have exacerbated the problem of urban flooding, particularly in the cities of China. In addition to that, the concept of flood risk management and adaptation measures and strategies are still missed in the cities’ development future plans. The main objective of this Ph.D. dissertation is to investigate the flood risk analysis and assessment based on flood simulation and adaptive strategies for flood event through two case studies of Changsha city in south-central China. In case study I, fluvial flooding was considered on mesoscale and an MCA-based approach was proposed to assess the integrated flood risk of Changsha central city. HEC-RAS 1-D model was used to simulation the inundation characteristics for hazard analysis based on four risk dimensions: economic, social, environmental, and infrastructural risk. For infrastructural dimension, apart for direct damage on road segments, network analysis method was combined with inundation information and macroscopic traffic simulation to evaluate the impact on traffic volume as well as a decrease of road service level. Closeness centrality weighted with a travel time of pre- and after- flood was compared in order to measure the impact on urban accessibility. Integrated risk values were calculated using various weighting criteria sets. Sobol' indices were used as a tool of spatially-explicit global Uncertainty Analysis and Sensitivity Analysis (UA/SA) for damage models. In case study II, an agent-based modeling approach was proposed to simulate the emergency pluvial flood event caused by a short-time rainstorm in local areas of cities aiming at developing an interactive flood emergency management system capable of interpreting the risk and reduction strategy of the pluvial flood. The simulation integrated an inundation model with microscopic traffic simulation. It also reveals that all agents can benefit significantly from both engineering measures and the only pedestrian obtain relatively more benefits from risk warning with high awareness. The method provided potentials in studies on the adaptive emergency management and risk reduction, help both decision-makers and stakeholders to acquire deeper and comprehensive understanding of the flood risk. This Ph.D. study has investigated holistic methods and models’ selection in flood risk assessment and management to overcome data deficiency and to achieve the integration of different data. The results of the first case study reveal that the integrated methods have proved to be able to improved flood risk analysis and assessment especially for indirect damage of infrastructural system with network features. The global UA/SA based on Sobol' method and visualization with maps enable to gain the spatial distribution of uncertainty for various factors, the validation of damage models, and deeper and more comprehensive understanding of flood risk. Then based on the integrated risk assessment, functions of spatial planning in flood risk management were discussed, potentially providing guidance and support for decision-making. The results of the second case study denote that agent-based modeling and simulation can be effectively utilized for flood emergency management. Two scenarios focusing on specific risk reduction interventions were designed and compared. Engineering measures by improving capability of the drainage system and the surface permeability of waterlogging areas are the most effective means for damage mitigation. High public risk awareness still has great potential benefits of the in the event of emergencies, which can greatly enhance the effectiveness of the official warning. The agent-based modeling and simulation provided an effective method for analyzing the effectiveness of different strategies for reducing flood risk at the local scale and for supporting urban flood emergency management. The case studies also indicate the significance and necessity of establishing a platform and database to realize full sharing and synergies of spatial information resources for flood risk management, which is a vital issue to manage the urban flood risk and take effective measures correspondingly with responding to emergency extreme flood event. Keywords: urban flood; flood risk assessment; network analysis; flood simulation; flood risk managemen

How Cumulative Stress Affected the Lived Experience of Emergency Medical Service Workers after a Horrific Natural Disaster: Implications for Professional Counselors

On Monday, August 29, 2005 Hurricane Katrina made landfall along the Louisiana and Alabama coastlines. The storm was recorded by the Federal Emergency Management Agency (FEMA) as the greatest natural disaster to strike the United States. Emergency Medical Service (EMS) workers from around the nation were dispatched to the disaster area to aid in the recovery operation. A small squad of volunteers from a regional disaster response team was dispatched on October 2005 by FEMA to Hurricane Katrina disaster areas. The team, composed of 24 members, worked the disaster area six weeks after the initial impact. This delayed response provided me with opportunistic informants who could report the effects of cumulative stress reactions that occurred during and shortly after their response into that devastated region. This study was grounded in Critical Incident Stress Management Theory (CISM) developed by Jeff Michell. This inquiry utilized focus groups and key informant individual interviews as the primary source of data. In this research project, I used an interpretive approach to data collection and analysis. Open ended lines of inquiry were used. An analysis of responses indicated that severe disruptions occurred in each of the five components of CISM. These disruptions included early intervention treatments for EMS providers, exposure to critical incidents, provision of psychosocial support to rescuers in need, an opportunity for expression of thoughts and feelings, crisis education and assistance in the development of coping mechanisms. A theme of disturbance also emerged within this study\u27s subjects from interactions with administrative and political systems that were present in the Hurricane Katrina Recovery Area. Additionally, other factors such as the presence of Post Traumatic Stress Disorder symptoms, disturbance in relationships, reduced job satisfaction and existential dilemmas were reported by the subjects. Cumulative stress from disaster recovery work has gone unrecognized. This study suggests that professional counselors and the national EMS system must begin to address the affects of cumulative stress on emergency providers in a systemic way. The importance of understanding cultural issues, decentralization of decision making in a disaster and specialized treatment mental health treatment protocols for emergency workers must be developed

Event-Cloud Platform to Support Decision- Making in Emergency Management

The challenge of this paper is to underline the capability of an Event-Cloud Platform to support efficiently an emergency situation. We chose to focus on a nuclear crisis use case. The proposed approach consists in modeling the business processes of crisis response on the one hand, and in supporting the orchestration and execution of these processes by using an Event-Cloud Platform on the other hand. This paper shows how the use of Event-Cloud techniques can support crisis management stakeholders by automatizing non-value added tasks and by directing decision- makers on what really requires their capabilities of choice. If Event-Cloud technology is a very interesting and topical subject, very few research works have considered this to improve emergency management. This paper tries to fill this gap by considering and applying these technologies on a nuclear crisis use-case