Fire Emergency Evacuation Research Articles

Fire emergency management of large shopping malls: IoT-based evacuee tracking and dynamic path optimization

As urbanization accelerates and buildings become more complex, fire emergency evacuation has become increasingly challenging. Traditional evacuation plans often struggle with slow response times and suboptimal path planning in real-time dynamic and complex fire scenarios. To address these issues, this study proposes the IoT-based DWM-Evac model for fire emergency evacuation path planning. The model leverages IoT technology by using various sensors placed inside buildings to monitor fire incidents and spread in real-time, collecting critical data such as temperature, smoke concentration, and flame location. It integrates Dynamic Graph Neural Networks (DGNN), Whale Optimization Algorithm (WOA), and Markov Decision Process (MDP) to enhance path efficiency and safety. Experimental results indicate that the DWM-Evac model achieves an average evacuation time of 315 s in a virtual mall environment, 25 s shorter than traditional plans, with an average path length of 255 meters and a path safety score of 0.92, higher than the traditional plan’s 0.88. The application of IoT in fire emergency management not only improves response speed but also optimizes path planning, significantly enhancing personnel safety.

Optimizing fire emergency evacuation routes in underground coal mines: A lightweight network flow approach

In underground mine fires, the presence of smoke, toxic gasses, and high heat can significantly hinder the evacuees from identifying the optimal path to safety. This study presents a framework that couples a mine fire simulator software with a Ford-Fulkerson algorithm to model fire evacuations as a minimum-cost flow problem. The fire-induced risks are quantified based on the MSHA safety standards and a user-friendly FFA computes the evacuation routes. By accumulating the quantified effect of the risk exposure and updating the network depending on the mine conditions, different safe evacuation routes are identified. The algorithm is demonstrated through fire simulation data acquired from a model of the VentSim™ DESIGN software. Airflow quantity, air quality, heat, carbon monoxide concentration, and visibility obstruction are acquired from the simulations and processed through the proposed algorithm. Based on the distribution of the quantified hazards and the MSHA safety standards, the algorithm outputs optimal evacuation paths. The computed evacuation routes minimize the exposure to the fire-induced hazards while at the same time prioritize the shortest routes. The presented framework can be used for evaluating ventilation designs and emergency plans as well as in real-time self-evacuation in mine emergencies.

A Case Study on the Evacuation of People during a Fire in the Workshop of a Large Factory

A workshop, as a crowded place, is quite easy to cause serious casualties and economic losses once there is a fire. In this paper, Pathfinder software was used to simulate fire emergency evacuation in a workshop of a large factory with building structural symmetry. According to the simulation results, several obstacles to the evacuation were discovered and further analyzed. The results showed that the main factors affecting the evacuation were the width of exits, the distribution of occupants and the effective evacuation width of stairs. Among them, only changing the width of exits had little influence on shortening evacuation time. While changing the effective evacuation width of stairs could greatly relieve the evacuation pressure, every increase of 0.5 m in the width of the staircase could shorten the evacuation time by 30.0 s. Meanwhile, the larger the number of people in high-rise buildings, the longer the evacuation time was. Therefore, the means of restricting people from entering the high-rise buildings in batches could be used to prevent personnel from being evacuated in time when a fire incident occurs.

Field detection of indoor fire threat situation based on LSTM-Kriging network

Obtaining the fire development information quickly and accurately is an important part of indoor fire emergency evacuation and rescue. However, at present, buildings only use fire sensors to monitor whether a fire is occurring, and there is a lack of means to obtain real-time threat situation information on the development of fires. An LSTM-Kriging neural network model is proposed in this paper, which can quickly generate an indoor fire threat field using the temporal data of fire sensors when an indoor fire occurs. Firstly, the Kriging algorithm was improved by replacing the Euclidean distance used in the variational function with the nearest passable distance to obtain a more accurate representation of the indoor threat distribution trend, and combined it with the Long Short-Term Memory (LSTM) network to construct the LSTM-Kriging network. Secondly, indoor fire scenarios were constructed in PyroSim, and fire parameters were simulated randomly. After data augmentation, the indoor fire threat situation dataset was generated. Finally, the optimized LSTM-Kriging model was trained and compared with Transformer, LSTM, and Recurrent Neural Network (RNN) on the indoor fire hazardous situation dataset. The experimental results show that LSTM-Kriging is the most effective model compared with several models mentioned above and the prediction of threatening situation reaches an accuracy of 97.8 %, with an average computation time of 0.19s on the GPU, which can meet the requirement of real-time fire situation monitoring. The indoor fire threat situation field detection method proposed in this paper achieves intelligent indoor fire detection and improves the building fire safety.

Developing a Framework Leveraging Building Information Modelling to Validate Fire Emergency Evacuation

In fire emergency management, a delayed execution will cause a significant number of casualties. Conventional fire drills typically only identify a certain percentage of evacuation bottlenecks after the building has been constructed, which is hard to improve. This paper proposes an innovative framework to validate fire emergency evacuation at the early design stage. According to the experience and knowledge of fire emergency evacuation design, the proposed framework also introduces a seamless two-way information channel to embed fire emergency evacuation simulations into a BIM-based design environment. Several critical factors for fire evacuation have been reviewed in relevant domain knowledge, which is used to build virtual characters to test in experimental scenarios. The results are analyzed to validate fire emergency evacuation factors, and the feedback knowledge is stored as a knowledge model for further applications.

A building information modeling-based fire emergency evacuation simulation system for large infrastructures

During fire emergencies, people in large infrastructures are difficult to comprehend real-time fire dynamics and identify available evacuation routes, leading to lengthy evacuation time and unnecessary loss of life and property. This study aims to develop a fire emergency evacuation simulation system for large infrastructures. This system integrates the data from building information modeling platform, fire dynamics simulator, and evacuation simulation platform through customized developments. Real-time fire situation is transmitted to the evacuation simulation platform to assess the impact of dynamic fire spread on the evacuation of people. The behavioral and psychological characteristics of evacuees of different genders and age groups are considered in simulated evacuations. An algorithm for optimizing evacuation route planning is designed to improve the utilization of each evacuation exit and provide a visualization of evacuation routes. This proposed system was validated at a busy subway station in China. The evacuation efficiency increased by 12.87%. It is concluded that this system can provide real-time dynamic optimal evacuation route planning for enhanced emergency management.

A flame-retardant and conductive fabric-based triboelectric nanogenerator: Application in fire alarm and emergency evacuation

The fabrics commonly used in architectural decorative materials pose significant fire hazards due to their flammability and rapid fire spread. Moreover, the traditional fire-alarm systems may fail to function properly in complex fire environments owing to power supply disruptions. In this study, we developed a low-cost and eco-friendly flame-retardant conductive fabric-based triboelectric nanogenerator (FCF-TENG) by integrating flame-retardant conductive nylon fabric and polytetrafluoroethylene soaked cotton fabric. This nanogenerator exhibits excellent flame-retardant properties and remarkable energy-harvesting capabilities. The nylon fabric, treated with layer-by-layer self-assembly method, possesses outstanding self-extinguishing capability and melt-dripping resistance. Additionally, the electrical performance of FCF-TENG significantly improves, with a 10-fold boost in conductivity, and the open-circuit voltage increases by 84% to 92 V. Besides, by incorporating the rectifier circuit, the FCF-TENG is capable of completely charging a 1 μF capacitor within 30 s. Furthermore, the FCF-TENG was successfully applied as a self-powered sensor in the fire-alarm system and served as a safety exit indicator for evacuees and fire rescue. This work presents an effective and innovative application of multifunctional smart textiles for energy harvesting and self-powered sensing.

Indoor fire emergency evacuation path planning based on improved NavMesh algorithm

With the acceleration of urbanization, the frequency of building fire incidents has been increasing year by year. Therefore, rapid, efficient, and safe evacuation from buildings has become an urgent and important task. A construction fire escape path planning method based on an improved NavMesh algorithm is proposed in this paper. Firstly, by using the method of local updates in the navigation grid, redundant computation is reduced, and the update time of the improved algorithm is about 6.8% of that of the original algorithm, immediate generation of navigation is achieved. Secondly, the heuristic function of the pathfinding algorithm is improved, and a multi-exit path planning mechanism is proposed to achieve more efficient, which can quickly plan a safe evacuation path away from the spreading fire and smoke in the event of a fire. Finally, a new evaluation index called Navigation Grid Complexity (NGC) is proposed and demonstrated to measure the quality of navigation grids. The feasibility and effectiveness of the proposed method are validated through simulation experiments on actual building models, which can provide real-time, efficient, intelligent, and safe path planning for rapid evacuation of evacuees in the fire scene.

A real-time automatic fire emergency evacuation route selection model based on decision-making processes of pedestrians

After a fire occurs, it is imperative that people in danger evacuate as soon as possible. However, the current emergency plan based on the pre-established static exiting route is unable to considering the real-time fire scenario. In addition, the selection of evacuation routes significantly relies on the decision-maker's experiences. These issues seriously affect evacuation efficiency, decreasing the likelihood of survival. This paper developed an effective real-time evacuation guidance method that can automatically select the evacuation route in accordance with real-time fire scenarios. The model is established based on the on-policy learning algorithm SARSA (State–action–reward–state–action), an algorithm for learning a Markov decision process policy, which could mimic the decision-making of pedestrian behaviors in an emergency. In addition, two types of radar (exit radar and fire radar) are introduced into the SARSA algorithm to facilitate the wayfinding process, which formulated the so-called Radar-assisted SARSA (RSARSA). The results have shown that RSARSA can swiftly decide a safer evacuation route for pedestrians or crowd at arbitrary location. The convergence time of initial successful route planning is between 0.05 and 4.5 s under the tests in this paper. The evacuation route determined by this algorithm can well consider the fire, and timely avoid routes with potential dangerous. Moreover, RSARSA can flexibly respond to different fires under various heat release rates and development speeds. By applying this technology, fire evacuation can be guided by routes that are more attuned to the mindset of pedestrians. It can provide a good basis for route selection of crowd evacuation.

Knowledge Graph Construction to Facilitate Indoor Fire Emergency Evacuation

Indoor fire is a sudden and frequent disaster that severely threatens the safety of indoor people worldwide. Indoor fire emergency evacuation is crucial to reducing losses involving various objects and complex relations. However, traditional studies only rely on numerical simulation, which cannot provide adequate support for decision-making in indoor fire scenarios. The knowledge graph is a knowledge base that can fully utilize massive heterogeneous data to form a sound knowledge system; however, it has not been effectively applied in the fire emergency domain. This study is a preliminary attempt to construct a knowledge graph for indoor fire emergency evacuation. We constructed the indoor fire domain ontology and proposed a four-tuple knowledge representation model. A knowledge graph was constructed with 1852 nodes and 2364 relations from 25 indoor fire events. The proposed method was tested for the case study of Henan Pingdingshan ‘5.25’ Fire Accident in China. Results show that the proposed knowledge representation model and the corresponding knowledge graph can represent complicated indoor fire events and support indoor fire emergency evacuation.

Research and Application of Calibration Device for Fire Emergency Lighting Detector

In order to solve the problem of quantitative traceability of detection devices for fire emergency lighting and evacuation indication systems. Method analysis and research were conducted on parameters such as emergency switching time, emergency working time, DC charging voltage, DC discharge voltage, DC charging current, DC discharge current, environmental test temperature, and environmental test humidity. We searched for appropriate calibration methods for the technical characteristics of each parameter and designed a set of calibration devices for fire emergency lighting detectors. The test results show that the technical indicators of the calibration device can meet the traceability requirements of the fire emergency lighting and evacuation indication system.

Design for safety in metro station evacuation: a study of fire emergency evacuation behavior and simulation

PurposeMetro stations have become a crucial aspect of urban rail transportation, integrating facilities, equipment and pedestrians. Impractical physical layout designs and pedestrian psychology impact the effectiveness of an evacuation during a metro fire. Prior research on emergency evacuation has overlooked the complexity of metro stations and failed to adequately consider the physical heterogeneity of stations and pedestrian psychology. Therefore, this study aims to develop a comprehensive evacuation optimization strategy for metro stations by applying the concept of design for safety (DFS) to an emergency evacuation. This approach offers novel insights into the management of complex systems in metro stations during emergencies.Design/methodology/approachPhysical and social factors affecting evacuations are identified. Moreover, the social force model (SFM) is modified by combining the fire dynamics model (FDM) and considering pedestrians' impatience and panic psychology. Based on the Nanjing South Metro Station, a multiagent-based simulation (MABS) model is developed. Finally, based on DFS, optimization strategies for metro stations are suggested.FindingsThe most effective evacuation occurs when the width of the stairs is 3 meters and the transfer corridor is 14 meters. Additionally, a luggage disposal area should be set up. The exit strategy of the fewest evacuees is better than the nearest-exit strategy, and the staff in the metro station should guide pedestrians correctly.Originality/valuePrevious studies rarely consider metro stations as sociotechnical systems or apply DFS to proactively reduce evacuation risks. This study provides a new perspective on the evacuation framework of metro stations, which can guide the designers and managers of metro stations.

Fire Egress System Optimization of High-Rise Teaching Building Based on Simulation and Machine Learning

A fire egress system is one of the most critical aspects of fire emergency evacuation, which is the cornerstone technology of building fire safety. The high-rise teaching buildings on campus, where vast crowds of people gather, need to be qualified for rapid evacuation in the event of a fire especially. Conventional teaching building egress system design places more emphasis on individual elements (e.g., stairwells, evacuation doors, and evacuation walkways) rather than on their co-regulation as a whole. Furthermore, there are not enough holistic and effective optimal design strategies, which is because most of the existing studies rely on experiments or simulations and often suffer from a lack of sufficient data to fully reveal the interactions of individual variables. In this study, the co-effectiveness of stairwells, walkways, and room doors in reducing total evacuation time was investigated by simulation and machine learning. We selected a typical high-rise teaching building as an example and integrated two simulation software, Pyrosim and Pathfinder, to compare the available safe evacuation time (ASET) and required safe evacuation time (RSET). Then, a framework consisting of five factors—stair flight width (SFW), stairwell door width (SDW), corridor width (CW), room door width (RDW), and location of the downward stair flight (LDSF)—was established for the optimization through statistical analysis of big data obtained by the preferred machine learning algorithm. Results indicate that (1) By modifying just one factor (SFW), the total evacuation time (TET) can be reduced by at most 12.1%, with the mortality rate dropping from 26.5% to 9.5%; (2) although ASET could not be achieved either, among 4000 cases of multi-factor combinations, a maximum TET improvement degree, 29.5%, can be achieved for the evacuation optimization compared to baseline model, with a consequent reduction in mortality to 0.15%; (3) it shows that the emphasis of the egress system optimization is on the geometric features of the evacuation stairwell; furthermore, the multi-factor combination approaches have better compromised evacuation performances than the single-factor controlled schemes. The research results can be applied as rational design strategies to mitigate fire evacuation issues in high-rise teaching buildings and, in addition, the methodology suggested in this paper would be suitable to other building types.

Research on spatial information transmission efficiency and capability of safety evacuation signs

Fires in buildings are among the high-frequency disasters experienced in urban areas. Improving the efficiency of emergency evacuation during fires can effectively reduce casualties. Safety evacuation signs offer indispensable spatial direction information for emergency evacuation, and the spatial relationship between safety signs and evacuees affects response times as well as evacuation efficiency. The research presented in this paper took two kinds of safety evacuation signs—namely, hangtag-type and embedded—as the research object, and a simulation experiment and fire drill were designed to gauge the transfer efficiency and capability of the spatial direction information they conveyed. The results show that the space angle of the hangtag-type safety evacuation sign was inversely proportional to the transfer efficiency and capability of the spatial direction information, and a fire drill confirmed this conclusion. When the spatial angle of the embedded safety evacuation sign was 5° the transfer efficiency and capability of the spatial direction information increased, the participants in the fire drill took less time, on average, to escape, and a higher percentage chose unfamiliar exits. In addition, three-dimensional safety evacuation signs were designed on the basis of the research results, and their functional structure was improved, which can make fire emergency evacuation more efficient.

Study on the optimization for emergency evacuation scheme under fire in university building complex

The evacuation in the university building complex involving a variety of campus buildings and a high density of occupants is barely simulated, especially by considering the safety awareness of evacuees and the impact of measured stair evacuation speed. This paper simulates and optimizes the fire emergency evacuation scheme of a university building complex in Northwest China by using BIM technology and Pathfinder simulation evacuation software. The proposed evacuation optimization scheme of university building complex reduces the evacuation time by 15–20% compared with the original evacuation scheme of the university. Through the simulation, it is found that the evacuation time required for sleeping at night is the shortest, while the longest evacuation time is required during lunch, due to the dispersion of students. Therefore, in addition to considering the safety awareness of the evacuees and the measured evacuation speed of stairs, the corresponding campus evacuation plan should be formulated according to the distribution of buildings in the campus complex and the actual utilization in different periods, so as to avoid the safety exit congestion and being far away from the refuge, due to the dense population in a specific period of time. This study also provides a method for solving the problem of regional evacuation path planning.

Simulation of fire emergency evacuation in a large-passenger-flow subway station based on the on-site measured data of Shenzhen Metro

Abstract Because of its large capacity, high efficiency and energy savings, the subway has gradually become the primary mode of transportation for citizens. A high density of passengers exists within a large-passenger-flow subway station, and the number of casualties and injuries during a fire emergency is substantial. In this paper, Pathfinder software and on-site measured data of Pingzhou station in Shenzhen (China) were utilized to simulate a fire emergency evacuation in a large-passenger-flow subway station. The Required Safe Egress Time (RSET), number of passengers and flow rates of stairs and escalators were analysed for three fire evacuation scenarios: train fire, platform fire and hall fire. The evacuation time of the train fire, which was 1173 s, was the longest, and 3621 occupants needed to evacuate when the train was fully loaded. Occupants could not complete the evacuation within 6 mins in all three fire evacuation scenarios, which does not meet the current standard requirements and codes. By changing the number of passengers and the number of stairs for evacuation, the flow rate capacity and evacuation time were explored, which have reference values for safety management and emergency evacuation plan optimization during peak hours of subway operation.

Early design stage evaluation of architectural factors in fire emergency evacuation of the buildings using Pix2Pix and explainable XGBoost model

ABSTRACT As a critical factor in architectural design, emergency evacuation is influenced by numerous parameters. Designers utilize modelling software to evaluate their sketches after completion ofbasic design. However, no various alternatives of early design stages could be assessed via simulations, since it is a time-consuming procedure. In this study, deep-learning algorithms have been adapted for the assessment of the evacuation process at early design stages. The main methods applied include an image-to-image translation with a conditional GAN (Pix2Pix) and Extreme Gradient Boosting (XGBoost). The developed Pix2Pix model generates the heat maps of possible route congestions with a Structural Similarity Index (SSIM) of 0.89. Besides, the XGBoost model predicts the evacuation time with the mean absolute error (MAE) and R2 values of 36 s and 0.94, respectively. This method generates the results of intended analyses at high speed and is a reliable alternative for time-consuming evacuation simulations in early design stages.

Evacuation Simulation in a Cultural Asset Fire: Impact of Fire Emergency Evacuation Facilities for People with Disabilities on Evacuation Time

More cautious fire safety evacuation assessment and escape route assistance are required when people with disabilities encounter a fire hazard in a historical museum. This study uses the old Chiayi City Hall, which is mainly used for an exhibition space, as the example. The core of this study is the problem of fire evacuation that emerged after the historic building opened and was reused as a museum; it uses Pathfinder evacuation simulation software, discussing the difference between traditional and segregated evacuation and assuming the original evacuation, elevator emergency evacuation, and external ramp evaluation. There are three evacuation scenarios, and the number of accommodated people is set to 730, pursuant to the applicable law. Comparing the conditions of people with disabilities and ordinary members of the public during evacuation through the foregoing three scenarios, the overall evacuation time and survival rate of the original evacuation scenario are 440 s and 49.8%, respectively; and the overall evacuation time and survival rate of the barrier-free elevator emergency evacuation scenario are 332 s and 65.4%, respectively; the overall evacuation time and survival rate of the external ramp evaluation scenario are 320 s and 65.6%, respectively. The computer data analysis shows that the use of the external ramp evaluation gives people with disabilities the best evacuation time and survival rate because the architectural form of cultural heritage buildings is more fragile, specific, and fast-burning than that of ordinary buildings. As the global awareness of cultural asset preservation and revitalization is increasing, the evacuation of people with disabilities in the building in the case of fire is very important. The results of this study can be used as an emergency evacuation design recommendation for people with disabilities in the cultural assets through evacuation simulation analysis.

Status quo and challenges and future development of fire emergency evacuation research and application in built environment

Fire emergency evacuation study has been conducted for decades. In recent two decades, the fire emergency evacuation studies have been incorporating new technologies due to the high demands on efficient and safe evacuation for occupants who have various needs. The proposed fire emergency evacuation system from academic research and solutions from industry practices adopt different technologies to serve various evacuees. Therefore, this study conducts literature review to understand the status quo of current fire emergency evacuation research and practice. It shows that fire emergency evacuation studies mainly focus on the facility operation stage instead of design and construction stages. The facilities include residential buildings, education buildings, subways, shopping centers, etc. Three critical factors affect efficient and safe fire emergency evacuation in a built environment – facility physical features, fire characteristics, and human behavior. This study categories these new technologies, which are incorporated into the fire emergency evacuation research and practices within the recent two decades, into four groups: (1) Facility geometrical analysis, which includes the technologies such as BIM, GIS, VR and the combination of BIM/GIS/VR (2) Fire and smoke simulation, e.g. FDS and Pyrosim. The simulation output such as fire and smoke dynamics is incorporated into intelligent fire evacuation system (3) Crowd evacuation simulation software, e.g. Pathfinder, Massmotion; the output of simulation is used to develop personalized evacuation system (4) Indoor positioning system and mobile device/IoT technology to track and evacuate occupants intelligently. This study presents these new technologies used in the fire emergency evacuation systems and indicates that the development of an intelligent and personalized emergency evacuation system, which may track the evacuees in real time, is the future research trend.

Fire Emergency Evacuation from a School Building Using an Evolutionary Virtual Reality Platform

In the last few years, modern technologies such as numerical simulations, virtual and augmented reality, and agent-based models represented effective tools to study phenomena, which may not be experimentally reproduced due to costs, inherent hazards, or other constraints (e.g., fire or earthquake emergencies and evacuation from buildings). This paper shows how to integrate a virtual reality platform with numerical simulation tools to reproduce an evolutionary fire emergency scenario. It is computed in real time based on the building information model and a fluid dynamic software. A specific software was also used to simulate in real time the crowd dynamic in the virtual environment during the emergency evacuation process. To demonstrate the applicability of the proposed methodology, the emergency fire evacuation process for an existing school building is presented. The results show that the proposed virtual reality-based system can be employed for reproducing fire emergency scenarios. It can be used to help decision-makers to determine emergency plans and to help firefighters as a training tool to simulate emergency evacuation actions.