Emergency Response Process Research Articles

Refinement-Based Hierarchical Modeling and Correctness Verification of Cross-Organization Collaborative Emergency Response Processes

When an emergency occurs, one of the important challenges is how to form an effective and timely response. An emergency disposal plan is usually organized as a series of emergency response processes manipulated by one emergency command center and several subordinate emergency organizations. Moreover, these subordinate organizations are usually geographically dispersed and need to collaborate with each other. In this case, designing and verifying such cross-organizational collaborative emergency response processes are complicated and time-consuming. To address this problem, we propose a hierarchical modeling and correctness verification approach. A general framework for hierarchical modeling and correctness verification of such processes is first introduced. Then, a top-level model and two kinds of bottom-level models (complex and simple bottom-level ones) are proposed to model such processes and collaboration patterns from different abstraction levels. Next, Petri net refinement operation is adopted to refine the top-level model by using its corresponding bottom-level models to obtain the refined model. Finally, the correctness of the refined model is verified based on reachability graph. A typical running case of cross-organization collaborative fire emergency response processes is given to validate our proposed method.

Reservoir dam operating risk dynamics modelling for safety control in the emergency response process

As revealed by the dam break accident investigation statistics, flawed organizational behavior determines the safety level of the reservoir dam. Its operating risk revolution process involves water, disaster, relief material dispatching, information interaction, and so on. The multiple information transferring mode and dynamic processes perform with the characteristics of the social-technical system, but little prior research on the risk causality can be found in such a view. The traditional risk analysis and assessment techniques based on linear accident model and the partial probability calculation cannot effectively satisfy the requirements for dam-break emergency decision-making in a dynamic and systematic way. Based on the system dynamics approach, this study proposed risk dynamics models aiming for risk interaction mechanisms involving organizational, human, and technical system factors leading to dam break. The models guided the development of a quantitative risk assessment tool to integrate relevant professional modules and data. The derived policy suggestions which guarantee the life and property of downstream residents can improve the abilities of dam operating management organization for more effective responses under emergency circumstances.

A probabilistic model of human error assessment for autonomous cargo ships focusing on human–autonomy collaboration

Despite the use of automation technology in the maritime industry, human errors are still the typical navigational risk influencing factors in autonomous ships with the third degree of autonomy. However, there is an urgent need for new human error probability assessment focusing on the autonomous cargo ships with human–autonomy collaboration. Hence, to assess these human errors during the emergency response process, a probabilistic model is proposed in this paper. Firstly, the risk factors are identified and classified by analysing the operational process of the Shore Control Centre (SCC). This is followed by the establishment of an event tree model delivered from human errors using Technique for Human Error Rate Prediction (THERP). Furthermore, Bayesian Networks (BNs) model is utilized for the three stages of perception, decision, and execution. Finally, the human errors probabilities are calculated for the mentioned three stages focusing on human–autonomy collaboration. Moreover, the importance of human error factors is quantified with sensitivity analysis, which can provide flexible references for the theoretical construction of the SCC and training of operators. The process was applied to assess the probabilities of human errors focusing on human–autonomy collaboration under the remote navigation mode of an autonomous cargo ship (test ship) in the city of Wuhan, China.

I1 Nursing Emergency Response Process for Suspected Opioid Overdose in Ambulatory Care: Increasing Naloxone Access

I1 Nursing Emergency Response Process for Suspected Opioid Overdose in Ambulatory Care: Increasing Naloxone Access

Challenges in Public Health Rapid Response Team Management.

The International Health Regulations (2005) dictate the need for states parties to establish capacity to respond promptly and effectively to public health risks. Public health rapid response teams (RRTs) can fulfill this need as a component of a larger public health emergency response infrastructure. However, lack of a standardized approach to establishing and managing RRTs can lead to substantial delays in effective response measures. As part of the Global Health Security Agenda, national governments have sought to develop and more formally institute their RRTs. RRT challenges were identified from 21 countries spanning 4 continents from 2016 to 2018 through direct observation of RRTs deployed during public health emergencies, discussions with RRT managers involved in outbreak response, and during formal RRT management training workshops. One major challenge identified is the development and maintenance of an RRT roster to ensure deployable surge staff identification, selection, and availability. Another challenge is ensuring that RRT members are trained and have the relevant competencies to be effective in the field. Finally, the lack of defined RRT standard operating procedures covering both nonemergency maintenance measures and the multistage emergency response processes required for RRT function can delay the RRT's response time and effectiveness. These findings highlight the importance of planning to preemptively address these challenges to ensure rapid and effective response measures, ultimately strengthening global health security.

Text Quality Analysis of Emergency Response Plans

Emergency response plans are regarded as effective guidance for natural disasters and these plans describe emergency response processes in natural language. More specifically, they are textual process descriptions and describe not only how all departments perform their own response tasks, but also how different departments interact with each other. Analyzing text quality of emergency response plans as a typical evaluation approach is an important concern in emergency responses. Because of the flexibility of natural language, emergency response plans normally contain unwanted ambiguities, and it is difficult to check consistency and completeness. Automatic text quality analysis of emergency response plans written in Chinese from the perspective of process descriptions is proposed in this paper. Firstly, three types of response tasks including message sending tasks, message receiving tasks and regular tasks are extracted through Bi-LSTM-CRF networks (a Conditional Random Fields network is combined with a Bidirectional Long Short-Term Memory network). Then, a series of text quality analysis rules associated with extracted response tasks are created. These rules focus on the progressive relationship of four levels of emergency responses, completeness of response tasks, ambiguity and redundancy of emergency response plans. Finally, real-world data is collected to validate the proposed approach, which consists of four types of emergency response plans of natural disasters including district, municipal, provincial and national emergency response plans. It is demonstrated that the proposed approach can be used to facilitate revisions and improvements of emergency response plans.

An artificial intelligence based crowdsensing solution for on-demand accident scene monitoring

Abstract Road traffic crashes have a devastating impact on societies by claiming more than 1.35 million lives each year and causing up to 50 million injuries. Improving the efficiency of emergency management systems constitutes a key measure to reduce road traffic deaths and injuries. In this work, we propose a comprehensive crowdsensing-based solution for the real-time collection and the analysis of accident scene intelligence as a means to improve the efficiency of the emergency response process and help reduce road fatalities. The solution leverages sensory, mobile, and web technologies for the real-time monitoring of accident scenes, and employs Artificial Intelligence for the automatic analysis of the accident scene data, to allow the automatic generation of accident intelligence reports. Police officers and rescue teams can use those reports for fast and accurate situational assessment and effective response to emergencies. The proposed system was fully implemented and its operation was successfully tested using a variety of scenarios. This work gives interesting insights into the possibility of leveraging crowdsensing and artificial intelligence for offering emergency situational awareness and improving the efficiency of emergency response operations.

Time dynamics of emergency response network for hazardous chemical accidents: A case study in China

Since currently hazardous chemical accidents occur frequently around the world, how to build up an effective emergency response network (ERN) for hazardous chemical accidents become an urgent issue. Given the truth that previous static ERN research could not reflect the dynamic interaction patterns among actors in emergency response process, this paper studied the emergency response network for hazardous chemical accidents from the perspective of temporal dynamics. Jiangsu Xiangshui 3.21 chemical plant explosion accident, a major hazardous chemical accident just happened in March 2019, was selected as a case in this paper. Based on the time slices of the accident emergency response process, the dynamic evolution of emergency response network, organization functions, and organization positions over time were analyzed by social network analysis (SNA). The results revealed the dynamics of emergency response network in the context of centralized administrative systems. Emergency response network became more decentralized over time, rather than centralized; central organization functions varied depending on the response needs in each period; and positions of participants in network changed as time passed. The results also showed that under the centralized administrative systems, public-sector organizations were the core of emergency response network; whilst non-profit organizations and private organizations were largely marginalized. A hybrid network with centralization and decentralization complement each other may be more effective. ERN for hazardous chemical accidents should be considered in a time-dynamic way and collaborations among public sector organizations, NPOs and private organizations should be paid more attention to improve the emergency response efficiency. These findings may expand knowledge for researchers and practitioners to understand emergency response network of hazardous chemical accidents from dynamic perspectives, having an important significance for reducing and controlling economic losses, social risks and environmental damage caused by hazardous chemical accidents.

Parallel Simulation Decision-Making Method for a Response to Unconventional Public Health Emergencies Based on the Scenario-Response Paradigm and Discrete Event System Theory.

Given the non-repeatability, complexity, and unpredictability of unconventional public health emergencies, building accurate models and making effective response decisions based only on traditional prediction-response decision-making methods are difficult. To solve this problem, under the scenario-response paradigm and theories on parallel emergency management and discrete event system (DES), the parallel simulation decision-making framework (PSDF), which includes the methods of abstract modeling, simulation operation, decision-making optimization, and parallel control, is proposed for unconventional public health emergency response processes. Furthermore, with the example of the severe acute respiratory syndrome (SARS) response process, the evolutionary scenarios that include infected patients and diagnostic processes are transformed into simulation processes. Then, the validity and operability of the DES-PSDF method proposed in this paper are verified by the results of a simulation experiment. The results demonstrated that, in the case of insufficient prior knowledge, effective parallel simulation models can be constructed and improved dynamically by multi-stage parallel controlling. Public health system bottlenecks and relevant effective response solutions can also be obtained by iterative simulation and optimizing decisions. To meet the urgent requirements of emergency response, the DES-PSDF method introduces a new response decision-making concept for unconventional public health emergencies.

Actantial Narrative Schema in Emergency Response Process Modeling for Aircraft Fires

Analyzing the emergency response process and time characteristics after aircraft fires is extremely important for airport safety. Due to nonprocess-related elements, the Petri net model of the emergency process is generally complex and difficult to revise and expand. In this study, the actantial model was used to analyze the semantic structure of emergency actions in the Petri net emergency process model, and the actantial-timed Petri net (A-TPN) hybrid model was proposed for problem solving. The emergency response process of aircraft fires was analyzed as a case study to explain the application steps of the A-TPN hybrid model. First, the types of elements should be divided into process-related elements and nonprocess-related elements. Process-related elements include status elements and narrative elements, which are equivalent to the places and transitions in the Petri net model. Second, the workflow constructed by the status and narrative elements is converted into a Petri net. An actantial model is used to analyze the semantic structure of emergency response action narratives. Third, according to the analysis of the actants of the helper and the opponent, emergency action time characteristics are considered to construct the A-TPN hybrid model and analyze the time performance of the emergency response process. In this way, an emergency response plan can be analyzed and promoted for smart development.

Resource Conflict Checking and Resolution Controller Design for Cross-Organization Emergency Response Processes

A group of geographically dispersed and logically collaborated emergency organizations are involved when emergency occurs. Two challenging issues are a reasonable emergency resource allocation mechanism and an efficient resource conflict checking and resolution control mechanism to ensure the conflict-free execution of global cross-organization emergency response processes. To address them, this paper proposes an approach to support emergency resource management including both intraorganization private resource management and cross-organization public resource management. The former has been fully discussed in our previous work using E-net. To cope with the latter, this paper presents a novel type of Petri net that is extended with both time and resource factors to model cross-organization emergency response processes. Then, according to the resource requirement analysis, their worst, delayed, and best cases are obtained. Next, emergency resource conflict checking and four conflict resolution strategies are proposed to resolve the detected resource conflicts for the delayed execution case. This paper shows how to use different resolution strategies to construct the conflict-free model by designing corresponding resolution controllers. Finally, their performance is evaluated by a fire emergency response example.

Smart hospital emergency system

In recent years, the UK’s emergency call and response has shown elements of great strain as of today. The strain on emergency call systems estimated by a 9 million calls (including both landline and mobile) made in 2014 alone. Coupled with an increasing population and cuts in government funding, this has resulted in lower percentages of emergency response vehicles at hand and longer response times. In this paper, we highlight the main challenges of emergency services and overview of previous solutions. In addition, we propose a new system call Smart Hospital Emergency System (SHES). The main aim of SHES is to save lives through improving communications between patient and emergency services. Utilising the latest of technologies and algorithms within SHES is aiming to increase emergency communication throughput, while reducing emergency call systems issues and making the process of emergency response more efficient. Utilising health data held within a personal smartphone, and internal tracked data (GPU, Accelerometer, Gyroscope etc.), SHES aims to process the mentioned data efficiently, and securely, through automatic communications with emergency services, ultimately reducing communication bottlenecks. Live video-streaming through real-time video communication protocols is also a focus of SHES to improve initial communications between emergency services and patients. A prototype of this system has been developed. The system has been evaluated by a preliminary usability, reliability, and communication performance study.

A Method of Emergent Event Evolution Reasoning Based on Ontology Cluster and Bayesian Network

Comprehensive real-time event information is critical to policymakers during emergency response and decision-making process. However, the development process of the emergent events has great uncertainty, and situational evolutions of emergencies are often difficult to use the fixed reasoning mode to attain. For this reason, this paper proposes a new method based on the ontology cluster for the evolution reasoning of emergency scenarios and extends the sematic web rule language to realize the scenario deduction, which can apply the Bayesian network to perform the conditional probability reasoning. A counterpart modeling and modifying of the Bayesian network optimization process is introduced. Besides, the probabilistic interpretation rules of atom components in context evolution are described with detailed query examples of emergency situation deducting and reasoning. The experimental results show that this approach is efficient in describing and capable of calculating the occurrence possibilities of the emergent events.

Emergencies situational modeling technology for territorial management support

A situational modeling technology of natural and technogenic emergencies is offered. This technology integrates the calculation methods of emergency assessment, methods of analytical processing and dynamic mapping controlled by the expert system. We developed the system model of information-analytical systems of management support of natural and technogenic safety describing informational resources structure, system functioning at the solution of various modeling problems. For the first time, a generic algorithm for assessing the consequences of dangerous situations is implemented. The features of different calculation methods use for assessing the consequences and dynamics of dangerous situations are shown. The spatial analysis is used for scales assessment, the forecast of event’s dynamics and formation of the available emergency forces. We use the knowledge base to form the list and priority of accident elimination tasks, protection actions and the resources requirement. The offered technology implements a comprehensive support security control of the territories. As the experience of situational modeling systems operation in the Krasnoyarsk region has shown, to improve the management of emergency response processes, it’s necessary to solve the problems of maintaining up-to-date operational monitoring data, characteristics of territories, facilities, infrastructure, as well as registers of rescue units, equipment and resources. We justified the need of iterative knowledge bases update of scenarios actions in dangerous situations by analysis of already occurred events.

Strategy of Emergency Response of Flood and Landslide Disaster in Pacitan Regency

Disaster emergency response is an important stage in the process of disaster management in which the action is performed while tackling natural disasters. The goal of the research is to describe the phenomenon of floods and landslides disasters as well as the efforts of emergency response in the event of a disaster in pacitan regency year 2017. Research conducted through a descriptive qualitative approach. Method of data collection with interviews, observation and documentation. As for the data analysis stage include data condensation, data presentation and the final stage, namely the withdrawal of the conclusion. The results showed flooding and landslides diasters in pacitan regency in the year 2017 including big disaster from a series of disasters that have occurred. These categories include national scale natural disaster because there are any victims and damage inflicted is large enough so that the various parties get involved in the handling of the disaster. The process of emergency response in the event of a disaster, led by komadan dandim 0801 military see as commander of the emergency response to natural disasters. Emergency response could be made in learning to cope with disasters that are better realized through disaster prevention and mitigation. Therefore, the overall infrastructure improvements that are vulnerable to disaster-affected and disaster-prone area mapping as well as awareness of stakeholders in the disaster prevention and mitigation very recommended to improve the ability of the community in the face of natural disasters.

A Strategy for Selecting Points of Interest on Mobile Devices for Emergency Situations


 
 
 The need to use mobile technology in urban emergency response processes has recently been identified, given the importance of having relevant information to make decisions in these scenarios. The data visualization on small mobile devices, such as PDAs or smartphones, is a critical aspect to make appropriate and on-time decisions. This criticality particularly occurs due to the small size of their screens to show geographical data. This article presents a strategy to select and display the most relevant “Points of Interest” on a digital map, according to the emergency influence area. This strategy was implemented on the MobileMap tool, and then it was evaluated through simulated emergency situations. Commanders of various Chilean Fire Companies participated in this evaluation.
 
 

Assessing the feasibility of marine oil spill contingency plans from an information perspective

This paper evaluates the feasibility of marine oil spill contingency plans (OSCPs) systematically from the perspective of information availability and accuracy. A conceptual model integrating the fundamental elements of contingency plans is introduced, and the relevant information flows for marine oil spill emergency response processes are identified. The Dempster–Shafer (D-S) reasoning approach was adopted to develop a series of models for assessing the information-related feasibility of contingency plans. The models were validated through a case study, which proved that simplifying information requirements and improving the availability and accuracy of key information are effective methods of improving the information-related feasibility of contingency plans. Such research issues as improving the availability and accuracy of information and obtaining experts’ subjective opinions require further investigation. The main contributions of this study are identifying the importance of information for implementing OSCPs and developing a well-structured analysis framework and an appropriate method for assessing the information-related feasibility of OSCPs.

Virtual training environments for major incident response planning in UK gas infrastructure

PurposeThis paper aims to evaluate a virtual training environment for testing UK gas pipeline emergency response plans.Design/methodology/approachInterviews, observations and desk research were used to identify current methods for testing plans. A virtual training environment was developed and evaluated with industry experts by using participatory design techniques. Key themes relating to both the current methods for testing plans and for a virtual training environment were identified using thematic analysis.FindingsImproved training performance, remote participation and evidence of decision testing are benefits a virtual training environment can bring to current practice. It is suggested that a virtual training environment can enhance, rather than replace, the current process of testing emergency response plans.Research limitations/implicationsAnalysis of the virtual training environment being used to test plans in a live context would give further ecological validity to the findings. A study of the prototype used to test plans for incidents involving sectors outside the gas industry would further validate the findings.Originality/valueThe application of a virtual training environment to facilitate testing plans and the decision-making processes for major incidents involving high-pressure gas pipelines and storage sites is yet to be documented. This paper contributes to the literature by documenting the decision-making process and evaluation of a virtual training environment for testing plans in this context.

A Package Reduction Approach To Modeling and Analysis of Cross-Organization Emergency Response Processes With Privacy Protected

The emergency disposals are usually charged by several geographically dispersed and logically collaborated emergency organizations. In addition, each emergency organization owns its private emergency response process and can operate independently. In this case, modeling such cross-organizational emergency response processes is really a challenging issue when considering: 1) effective collaboration and coordination among different emergency partners; and 2) reasonable privacy and security protection mechanism to maintain the sensitive information confidential and unseen by other involved partners. In this paper, we propose a package reduction-based privacy protection approach to facilitate the modeling. Specifically, a kind of workflow nets extended with time, resource, and message factors, called TRM_WF_nets for short, is first introduced to model cross-organization emergency response processes. Then, a three-layered framework is proposed to model cross-organization emergency response processes by taking into account their privacy protection and temporal performance evaluation. Next, a set of reduction rules are proposed to reduce the scale of a TRM_WF_net while keeping its external observable timing, message, and resource factors invariant. These reduction rules not only improve the efficiency of temporal performance evaluation but also protect the business privacy of each emergency organization during its collaboration and interaction with others. Finally, a real-life scenario of cross-organization fire emergency response processes is used to validate our proposed approaches.

Automatic Extraction of Emergency Response Process Models From Chinese Plans

Emergency plans can be regarded as the effective guidance of hazard emergency responses, and they include the textual descriptions of emergency response processes in terms of natural language. In this paper, we propose an approach to automatically extract emergency response process models from Chinese emergency plans. First, the emergency plan is represented as a text tree according to its layout markups and sentence-sequential relations. Then, process model elements, including four-level response condition formulas, executive roles, response tasks, and flow relations, are identified by rule-based approaches. Finally, an emergency response process tree is generated from both the text tree and extracted process model elements, and is transformed to an emergency response process that is modeled as business process modeling notation. Extensive experiments on real-world emergency plans demonstrate that the proposed approach is capable of extracting emergency response process models that are highly consistent with both the manually extracted models and the textual plans.