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The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station.

The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced.

The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation.

The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

Emergency evacuation plans are often developed under the assumption that evacuees will use wayfinding strategies such as taking the shortest distance route to their nearest exit. The purpose of this paper is to analyze empirical data from a wildfire evacuation analyzed to determine whether evacuees took a shortest distance route to their nearest exit and to identify any alternate wayfinding strategies that they may have used.

The wildfire evacuation analysis presented in this paper is the outcome of a natural experiment. A post-fire online survey was conducted, which included an interactive map interface that allowed evacuees to identify the route that they took. The survey results were integrated with several additional data sets using a GIS. Network analysis was used to compare the routes selected by evacuees to their shortest distance routes, and statistical hypothesis testing was employed to identify the wayfinding strategies that may have been used.

The network analysis revealed that 31 percent of evacuees took a shortest distance route to their nearest exit. Hypothesis testing showed that evacuees selected routes that had significantly longer distances and travel times than the shortest distance routes, and indicated that factors such as the downhill slope percentage of routes and the elevation of exits may have impacted the wayfinding process.

This research is best regarded as a spatiotemporal snapshot of wayfinding behavior during a single wildfire evacuation, but could inspire additional research to establish more generalizable results.

This research may help emergency managers develop more effective wildfire evacuation plans.

This research presents an analysis of an original data set that contributes to the broader body of scientific knowledge on wayfinding and spatial behavior during emergency evacuations.

Because of the global increase of climate change effects, floods are becoming more frequent and severer, especially in urban areas of coastal cities and islands where floodplains have turned into buildings because of rapid urbanisation, leading to a higher risk of damages. Urban heritage areas should be highly considered in the time of evacuation because of the vulnerability of streets and buildings and limitations on taking counteractions. Given these limitations, this study aims to propose a network of potential evacuation routes based on spatial configuration analysis of the heritage areas.

Penang Island's heritage site, namely, George Town, located on the northwest coast of Malaysia, is chosen as the case study. By using an approach of spatial configuration analysis using space syntax techniques in addition to considering the potential starting points for evacuation and flood risk map of the area, this study analysed the area's street network values for evacuation function during flood crisis time.

Potential evacuation routes were identified for flood disasters in the George Town heritage area. Furthermore, the proposed evacuation routes were evaluated in terms of time for evacuation by metric step-depth analysis of space syntax.

A few studies have focused on practical guidelines for evacuation routes based on spatial configuration analysis, an important yet neglected approach in this regard, especially concerning urban island areas. This study can contribute to providing strategies to reduce vulnerability and casualties in urban heritage areas.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.

The development of urban underground complexes (UUCs) has great positive significance for improving urban safety. Therefore, it is necessary to identify the key factors of the people's behavior of evacuation route selection (BERS) for fire emergencies and UUCs’ development. This study aims to find out the factors affecting people's BERS in the evacuation process of UUCs.

This study aims to find out the factors affecting people's BERS in the evacuation process of UUCs. To achieve this goal, the authors conducted a field experiment in F City. Furthermore, the people's BERS are obtained by using a structural equation model and compared with the field test results.

The authors found that the key factors for people's BERS are lighting conditions, route distance, flow direction guidance and indication. The results of this study contribute to the safety field by providing key factors for fire emergencies. It can also be used to improve fire safety management, evacuation strategies and assist in the development of intelligent evacuation systems.

The results of this study contribute to the safety field by providing key factors for fire emergencies. It can also be used to improve fire safety management, evacuation strategies and assist in the development of intelligent evacuation systems.

The purpose of this paper is to formulate and solve a new emergency evacuation planning problem. This problem addresses the needs of both able and disabled persons who are evacuated from multiple pick-up locations and transported using a heterogeneous fleet of vehicles.

The problem is formulated using a mixed integer linear programming model and solved using a heuristic algorithm. The authors analyze the selected heuristic with respect to key parameters and use it to address theoretical and practical case studies.

Evacuating people with disabilities has a significant impact on total evacuation time, due to increased loading/unloading times. Additionally, increasing the number of large capacity vehicles adapted to transport individuals with disabilities benefits total evacuation time.

The mathematical model is of high complexity and it is not possible to obtain exact solutions in reasonable computational times. The efficiency of the heuristic has not been analyzed with respect to optimality.

Solving the problem by a heuristic provides a fast solution, a requirement in emergency evacuation cases, especially when the state of the theater of the emergency changes dynamically. The parametric analysis of the heuristic provides valuable insights in improving an emergency evacuation system.

Efficient population evacuation studied in this work may save lives. This is especially critical for disabled evacuees, the evacuation of whom requires longer operational times.

The authors consider a population that comprises able and disabled individuals, the latter with varying degrees of disability. The authors also consider a heterogeneous fleet of vehicles, which perform multiple trips during the evacuation process.

The purpose of this paper is to propose a theoretical framework of applying the Internet of Things (IoT) technologies to the intelligent evacuation protocol in libraries at emergency situations.

The authors conducted field investigations on eight libraries in Wuhan, China, analyzed the characteristics of crowd gathering in libraries and the problems of the libraries’ existing evacuation plans. Therefore, an IoT-based intelligent evacuation protocol in libraries was proposed. Its basic structure consisted of five components: the information base, the protocol base, the IoT sensors, the information fusion system and the intelligent evacuation protocol generation system. In the information fusion system, Dempster–Shafer (D-S) evidence theory was employed as the information fusion algorithm to fuse the multi-sensor information at multiple time points, so as to reduce the uncertainty of disaster prediction. The authors also conducted a case study on the Library L in Wuhan, China. A specific evacuation route was generated for a fire and the crowd evacuation was simulated by the software Patherfind.

The proposed IoT-based evacuation protocol has four distinguishing features: scenario corresponding, precise evacuation, dynamic correction and intelligent decision-making. The case study shows that the proposed protocol is feasible in practice, indicating that the IoT technologies have great potential to be successfully applied to the safety management in libraries.

The software and hardware requirements as well as the Internet network requirements of IoT technologies need to be further discussed.

The proposed IoT-based intelligent evacuation protocol can be widely used in libraries, which is one of the inspirations for the use of IoT technologies in modern constructers.

The application of IoT technologies in libraries is a brand-new topic that has drawn much attention in academia recently. The crowd safety management in libraries is of great significance, and there is little professional literature on it. This paper proposes an IoT-based intelligent evacuation protocol, aiming at improving the safety management in libraries at emergency situations.

The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions.

It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO.

This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment.

The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.

The aim of this study was to determine the number of shelters, specify some optimal paths among building blocks towards shelters, and assign population to shelters.

Imperialist competition algorithm (ICA) and particle swarm optimization (PSO) were used to optimize the objectives of this study.

The optimal value for PSO objective function was with the number of function evaluations (NFE) of 5300 and the optimal value of ICA objective function was with NFE of 1062. Repetition test for both algorithms showed that imperialist competition algorithm enjoys better stability and constancy and higher speed of convergence compared to particle swarm algorithm. This has been also shown in larger environments. 92% of the existing populations have access to shelters at a distance of less than600 meters. This means that evacuation from the building blocks to shelters takes less than 8 minutes. The average distance from a block (for example, a residential complex) to an optimal shelter is approximately273meters. The greatest risk of route and shelter has been 239 and 121, respectively.

To address these goals, four following objective functions were considered: a) minimization of the distance for getting all the people to shelters b) the lowest total risk of the discharge path c) minimization of the total time required to transfer people to shelters or hospitals if necessary, and d) the lowest total risk in shelters.

Over the recent decades, the frequency of so-called ‘natural’ disasters has increased significantly worldwide and resulted in escalating human and economic losses. Among them, the earthquake is one of the major concerns of the various stakeholders related to urban planning.

In addition, the maximum time of discharge from the helter to the hospital has been 17 minutes, which means the presence of good access to selected shelters.