Firefighters Research Articles

Research on intervention strategies for fire rescue personnel’s competency frustration: EEG experimental validation

In order to accurately measure the level of competency frustration and what measures to take to alleviate the negative effects of competency frustration, 35 graduate students were selected to verify the effect of the frontal lobe α asymmetry (FAA) as a judgement of the competence frustration level using EEG experimental method. On this basis, through two stopwatch stopping experiments, 108 fire rescue personnel were selected to conduct the experiments to investigate the intervention effects of developmental feedback and compassion-focused therapy in turn. The results showed that frontal α asymmetry could be used as an EEG indicator for judging competency frustration, and the intervention method of compassion-focused therapy reduced the level of competency frustration of the subjects, while developmental feedback interventions did the opposite. The difference in the effects of the two intervention methods indicates that when intervening in competence frustration, it is easier to reduce the competency frustration by focusing on the subjects themselves than focusing on the completion of the task.

Prediction of fire danger index using a new machine learning based method to enhance power system resiliency against wildfires

AbstractWildfires, which can cause significant damage to power systems, are mostly inevitable and unpredictable. Fire danger indexes, such as the Forest Fire Danger Index (FFDI) and the Canadian Fire Weather Index (FWI), measure the potential wildfire danger at a given time and location. Thus, by predicting these fire danger indexes in advance, power system operators can obtain valuable insight into the potential wildfire risks and can better be prepared to tackle the wildfires. However, due to dependency on weather conditions, these indexes usually have volatile time series, which make their prediction complex. Taking these facts into account, this paper, unlike previous approaches that predict fire danger indexes based on climatological models, develops a machine learning‐based forecast process to predict these indexes using the relevant weather data and past performance. To do this, first, a volatility analysis approach is presented to analyse the volatility level of the time series data of a fire danger index. Afterwards, an effective machine learning‐based forecast methodology using a new deep feature selection model is proposed to predict fire danger indexes. The developed forecast methodology is tested on the real‐world data of FFDI and FWI and is compared with several popular alternative methods reported in the literature.

Analysis of Traffic Accidents with the Deployment of the Fire Rescue Service in the Regions of the Czech Republic

Analysis of Traffic Accidents with the Deployment of the Fire Rescue Service in the Regions of the Czech Republic

The Global Forest Fire Emissions Prediction System version 1.0

Abstract. The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that estimates biomass burning in near-real time for global air quality forecasting. The model uses a bottom-up approach, based on remotely sensed hotspot locations, and global databases linking burned area per hotspot to ecosystem-type classification at a 1 km resolution. Unlike other global fire emissions models, GFFEPS provides dynamic estimates of fuel consumption, fire behaviour and fire growth based on the Canadian Forest Fire Danger Rating System, plant phenology as calculated from daily global weather and burned-area estimates using near-real-time Visible Infrared Imaging Radiometer Suite (VIIRS) satellite-detected hotspots and historical burned-area statistics. Combining forecasts of daily fire weather and hourly meteorological conditions with a global land classification, GFFEPS produces fuel consumption and emission predictions in 3 h time steps (in contrast to non-dynamic models that use fixed consumption rates and require a collection of burned area to make post-burn estimates of emissions). GFFEPS has been designed for use in operational forecasting applications as well as historical simulations for which data are available. A study was conducted showing GFFEPS predictions through a 6-year period (2015–2020). Regional annual total smoke emissions, burned area and total fuel consumption per unit area as predicted by GFFEPS were generated to assess model performance over multiple years and regions. The model's fuel consumption per unit area results clearly distinguished regions dominated by grassland (Africa) from those dominated by forests (boreal regions) and showed high variability in regions affected by El Niño and deforestation. GFFEPS carbon emissions and burned area were then compared to other global wildfire emissions models, including the Global Fire Assimilation System (GFAS), the Global Fire Emissions Database (GFED4.1s) and the Fire INventory from NCAR (FINN 1.5 and 2.5). GFFEPS estimated values lower than GFAS and GFED (80 % and 74 %) and had values similar to FINN 1.5 (97 %). This was largely due to the impact of fuel moisture on consumption rates as captured by the dynamic weather modelling. Model evaluation efforts to date are described – an ongoing effort is underway to further validate the model, with further developments and improvements expected in the future.

The Mathematical Model Based on the Parameters of Simulation Results Predicts the Fire Extinguishing Resource Demand of Naval Fires

In recent years, due to the diversity of fire scenes in ports and ships, the problem of fire command is complicated. In the case of power failure, the original command platform and fire extinguishing system will not be able to be used normally, or the fire extinguishing resources carried by the ship when it is on fire cannot be used. In the traditional firefighting ability research, there is no clear measure of firefighting ability, resulting in inaccurate calculation results. By corresponding to the quantity and composition of resources for the study of fire extinguishing capability, the combination of the fire dynamics simulation software PyroSim2020 and a calculation model that converts its resources into the total amount and flow of fire extinguishing agent can be provided. Based on the analytic hierarchy process (AHP), a firefighting demand grade calculation and judgment model was established, which included five factors: fire scale, combustion material characteristics, foam extinguishing agent performance, firefighting object characteristics, and external factors. It concluded that the demand assignment values of each index element were 2, 5, 6, 9, and 10, and further proposed the grade judgment criteria for the calculation results of comprehensive fire demand. Through the quantitative simulation of firefighting demand based on the fire scenario and calculation model test of the consumption prediction of cooperative firefighting equipment, it can also provide a strategic reference for related cooperative fire rescue.

Observed Associations between Fire Danger and Climate Modes and Their Representation in ACCESS-S2

Abstract The increasing frequency and severity of wildfires in Australia, driven by climate change, pose a significant threat to ecosystems, lives, and property. This study examines the impact of climate drivers, specifically El Niño–Southern Oscillation (ENSO), Indian Ocean dipole (IOD), Southern Annular Mode (SAM), Madden–Julian oscillation (MJO), and two modes of persistent high pressure in the Australia–Pacific region, on extreme fire danger. By analyzing observed and simulated fire danger in relation to these climate drivers, we aim to enhance our understanding of climate–fire mechanisms and contribute to Australia’s bushfire preparedness. Our findings indicate that all assessed drivers influence extreme fire danger, with key influences related to the drivers’ established relationships with rainfall and temperature. El Niño, positive IOD, and negative SAM events generally increase extreme fire danger across most of Australia and in most seasons. The two modes of Australian blocking exhibit similar effects, varying spatially. Specific phases of the MJO have significant seasonal relationships with fire danger. In some instances, increased fire danger is not directly linked to temperature or precipitation changes but rather driven by remote teleconnections, airflow, or pressure anomalies. Evaluating the accuracy of weather and climate forecasting systems in representing these relationships is crucial for the effective prediction and mitigation of fire hazards. The leading Australian climate simulation model effectively reproduces observed relationships but reveals biases in capturing certain aspects of climate variability. Advancements in this field would enhance fire weather forecasts, including those by the Australian Bureau of Meteorology with lead times of up to 4 months. Significance Statement This assessment of climate–fire relationships and modeling accuracy is pivotal in understanding the factors behind severe fire events and improving future predictions and mitigation. Prior research has already established links between elevated fire weather conditions and these climate drivers, highlighting their potential for predicting severe fire events. This study aims to deepen our comprehension of the factors driving severe fire events and facilitate improved bushfire risk management in Australia.

Evaluation of Air Consumption Efficiency in Structural Firefighters.

This study examines variability in air consumption (AC) between firefighters (FF) working at a standardized pace, evaluates the relationship between air consumption efficiency (ACE) and work economy, identifies parameters associated with ACE, and explores the relationship between ACE and self-paced work rate. FF completed randomized trials of an air consumption drill at a standardized pace while breathing through a self-contained breathing apparatus and a gas analyzer. A subsample completed another trial at a self-selected pace. The average AC variability (±1 standard deviation) was ~3.1 min of cylinder usage (13.7%). AC was positively associated with work economy and numerous physiological and anthropometric outcomes. No relationship was found between ACE and self-paced air consumption drill time. FF working at higher internal strain demonstrated poorer ACE. Improving metabolic tolerance may extend the self-contained breathing apparatus' functional duration to enhance productivity and safety.

Assessing urban fire risk: An ensemble learning approach based on scenarios and cases

Urban fires represent a significant hazard to people’s lives and property, which makes it critical to estimate the risk adequately. Existing urban fire evaluation methods lack applicability because they do not take into account individual scene components and previous cases. As a result, this study offers the scenario- and case-based urban fire risk assessment approach (SCBUFRA), which seeks to achieve a more thorough and accurate urban fire risk assessment. First, the technique uses fire case and scenario data, as well as the recursive feature elimination method, to pick the elements utilized to assess urban fire risk. Second, the data-driven empowerment technique and stability analysis are utilized to determine the precise fire risk value and correctly quantify the fire danger level in each part of the city. Next, the Affinity Propagation (AP) technique is used to cluster scene elements. Ensemble learning is then used to create a risk prediction model by refining the weighting strategy of R2. Finally, Shapley additive explanations are used to investigate the elements causing urban fires. The findings show that SCBUFRA outperforms popular machine learning methods, that the number of crimes, gross population, and house price are the most important variables for fire prediction, and that the research is applicable to urban fire risk management and firefighting resource allocation.

An adaptable dead fuel moisture model for various fuel types and temporal scales tailored for wildfire danger assessment

Estimating the Dead Fuel Moisture Content (DFMC) is crucial in wildfire risk management, representing a key component in forest fire danger rating systems and wildfire simulation models. DFMC fluctuates sub-daily and spatially, influenced by local weather and fuel characteristics. This necessitates models that provide sub-daily fuel moisture conditions for improving wildfire risk management. Many forest fire danger rating systems typically rely on daily fuel moisture models that overlook local fuel characteristics, with consequent impact on wildfire management. The semi-empirical parametric DFMC model proposed addresses these issues by providing hourly dead fuel moisture dynamics, with specific parameters to consider local fuel characteristics. A calibration framework is proposed by adopting Particle Swarm Optimization-type algorithm. In the present study, the calibration framework has been tested by using hourly 10-hours fuel sticks measurements. Implementing this model in forest fire danger rating systems would enhance detail in forest fire danger conditions, advancing wildfire risk management.

Alcohol Misuse and Correlates with Mental Health Indicators among Firefighters

Background: Stress and repetitive exposures to potentially traumatizing events are inherent to first-responder professions. Firefighters and other crisis responders are often exposed to incidents in their work environments and are at risk of developing acute or posttraumatic symptomatology, depression, and anxiety, as well as harmful patterns of alcohol consumption. Most prior research and theory suggests that many firefighters use alcohol to cope with past and current stressors, and that increased drinking accompanies ongoing exposures to stressful occupational hazards. Objectives: The primary aim of this research was to examine alcohol consumption and mental health variables associated in the literature with alcohol misuse. Participants included 546 predominantly male career firefighters in the U.S. Using a cross-sectional design, we examined alcohol misuse in the context of self-reported depression, generalized anxiety, PTSD, and suicidal ideation using previously validated measures. Results: Based on the AUDIT’s recommended cut score of 8, 38.8% of our sample reported drinking at hazardous levels. Hazardous alcohol use was also significantly associated with several mental health indicators with correlations ranging from .28 to .34. Regression analyses revealed that over 14% of the variance in AUDIT scores could be explained by psychological symptom measures, and 29% of the variance in suicide risk was explained by a model using both alcohol and mental health measures. Conclusions: Findings suggest that psychological distress is associated with hazardous drinking, and that more consistent screening and referral for these issues, as well as multi-level interventions, are needed to effectively address these behavioral health concerns among firefighters.

MONITORING SISTEM PROTEKSI KEBAKARAN AKTIF PADA PLTU ANGGREK 2 X 25 MW

The Anggrek Unit Steam Power Plant (PLTU) is a power generation facility whose construction began in 2007 and began operating in 2019 with a capacity of 2 x 25 MW. Since its inauguration, PLTU Anggrek has become one of the main sources of electricity distribution in Gorontalo Province, so the frequency of power outages in the area has now decreased significantly. The water supply system for fire fighting uses BSP pipes. In this research, the aim is to determine the active fire protection system. This research was carried out with a qualitative descriptive design with data collection: observation and interviews. The assessment of the results of existing suitability will be assessed using descriptive percentage calculations. The research results show that of the 7 variables discussed, the average value for the level of fulfillment is 98.57%. Based on the level of fire audit assessment that meets the requirements of Indonesian national standards and international standards, the results are in the Good criteria or have met the requirements.

Rancang Bangun Sistem Pendeteksi Kebakaran Hutan Menggunakan Drone Berbasis Computer Vision

The danger of forest and land fires in Indonesia is a serious threat that continues to recurevery year. According to U.S. data Fire Service, there are more than 700 forest fires everyyear burning more than 7 million hectares of land. These fires not only damage ecosystems,but also cause the loss of important biodiversity. Many of Indonesia's endemic flora andfauna have fallen victim, increasing the risk of extinction. The use of UAVs can also changedisaster management. This technology can be integrated with early warning systems basedon analytical data and artificial intelligence, increasing the accuracy of fire predictions andmore proactive responses. Thus, the application of this technology is not just a temporarysolution, but a long-term strategic step to maintain environmental sustainability andcommunity welfare. Technological solutions such as UAVs and cooperation betweenvarious parties are needed to overcome this challenge effectively. The aim of this researchis to create a computer vision-based system that uses deep learning algorithms, especiallyYou Only Look Once (YOLO), to detect forest fires quickly and accurately. In mitigating forest fire disasters, early detection of hotspots is an important step to prevent fires fromspreading to other areas and reduce the damage caused by fires to humans and theenvironment. To achieve the objectives of this study, several actions were taken. First,forest fire image data is collected and processed for use in training the YOLO model. Next,the model is trained using a dataset that covers various forest fire conditions, such as fireintensity, time of day, and weather conditions, to ensure that the model can find firehotspots in various conditions.

Simulation Design and Research of Flame Generation in Virtual Fire Scene Based on Unity3D

Since the 21st century, with the continuous development and progress of science and technology, the possibility of fire danger is also rising, the requirements of public fire safety management have also been improved accordingly, and the problems in its fire safety management work make it difficult to meet the management requirements. The selection of firefighters has also become the top priority of management, good psychological quality of firefighters can keep calm in the face of fire explosions and various emergencies, and can make the most correct choice to complete the rescue and fire fighting work. In this paper, a building in a certain location is selected as the location to simulate the scene of fire. Through human-computer interaction to judge the psychological quality of firefighters. First use major modeling software such as 3ds Max, Adobe Fusecc, or find material in the Unity3D store to create models of fire scenes and people and import them into Unity3D. Using Unity3D's own particle system component to build flame models, adding collision body components to all models to detect their collision detection mechanism and the mechanism of flame spreading combustion. A Scenario-based Communication Ability Evaluation System Based on Traditional Cognitive Behavior Measurement and Advanced Eye Movement, EEG and NIR Acquisition Techniques.

ANALISIS INOVASI ROTI 7 LAPIS (RESPONSE TIME 7 MENIT LAYANAN PEMADAMAN KEBAKARAN GRATIS) DI KOTA SURABAYA DALAM PERSPEKTIF NEW PUBLIC SERVICE

The "Roti 7 Lapis" innovation by Surabaya Fire and Rescue Department (DPKP) aims to accelerate fire fighting response with a target time of 7 minutes, at no cost, to reduce material losses and casualties. The program not only focuses on efficiency, but also builds community involvement in fire prevention, in line with New Public Service (NPS) principles that emphasize inclusivity, equity, and collaboration. "Roti 7 Lapis" manages fire risk holistically through cross-sector collaboration and the latest technology. Its implementation is supported by strict regulations and a transparent reporting system that ensures accountability and service effectiveness. Development recommendations include increasing community participation, strengthening transparency, and further integrating technological innovations. In the context of growing urbanization, these measures aim to improve the sustainability and effectiveness of the program in maintaining the safety and well-being of Surabaya's citizens.

СИСТЕМА КАЧЕСТВА ОБУЧЕНИЯ В КАДЕТСКИХ КЛАССАХ МЧС РОССИИ И ПОЖАРНО-СПАСАТЕЛЬНЫХ КОЛЛЕДЖАХ

The results of research on the creation of an internal system for assessing the quality of education teaching children in schools with cadet classes of EMERCOM of Russia and fire and rescue colleges the basics of fire safety are presented. The requirements for the qualifications of a teacher-educator for high-quality classes with children on combustion, the danger of uncontrolled combustion – fire and compliance with fire safety requirements are presented. The methodological features of teaching children of different age groups the basics of fire prevention, fire fighting equipment and tactics are shown. Methods for checking the quality of student learning are proposed.

Coupled Effects of High Temperatures and Droughts on Forest Fires in Northeast China

High temperatures and droughts are two natural disasters that cause forest fires. During climate change, the frequent occurrence of high temperatures, droughts, and their coupled effects significantly increase the forest fire risk. To reveal the seasonal and spatial differences in the coupled effects of high temperatures and droughts on forest fires, this study used the Copula method and proposed the compound extremely high-temperature and drought event index (CTDI). The results indicated that the study area was subject to frequent forest fires in spring (71.56%), and the burned areas were mainly located in forests (40.83%) and the transition zone between farmland and forests (36.91%). The probability of forest fires in summer increased with high temperatures and drought intensity, with high temperatures playing a dominant role. The highest forest fire hazard occurred in summer (>0.98). The probability of a forest fire occurring under extreme meteorological conditions in summer and fall was more than twice as high as that in the same zone under non-extreme conditions. Droughts play a significant role in the occurrence and spread of forest fires during fall. These results can provide decision-making support for forest fire warnings and fire fighting in the Northeast China forest zone.

Application and Research of Intelligent Multi-source Information Fusion Technology in Firefighting Equipment

As modern firefighting environments become increasingly complex, traditional firefighter equipment and operational methods are no longer adequate to address the high-risk challenges of fire rescue operations. Fire scenes are characterized by complex and hazardous environmental factors, with firefighters facing multiple threats such as extreme temperatures, dense smoke, and toxic gases. Therefore, ensuring the safety and efficiency of firefighters is of paramount importance. This study integrates multiple sensor technologies to enable real-time monitoring of firefighters' physiological status, posture changes, and fire scene conditions. The system incorporates ErgoLAB wireless ECG and PPG sensors, the BWT61CL posture sensor, and the MAG14mini infrared camera, which are capable of simultaneously capturing key physiological data and heat distribution in the fire scene. To ensure data accuracy and real-time performance, the study employs efficient signal preprocessing techniques, including noise reduction, baseline correction, and time synchronization. In addition, wireless transmission technology and multimodal data fusion algorithms are utilized to comprehensively analyze the firefighters' status and fire scene conditions. This approach significantly enhances the precision of firefighter safety monitoring and operational efficiency, demonstrating substantial innovation and practical value.

The polk county screening tool screening for detecting subarachnoid hemorrhage

IntroductionThe subarachnoid space in the brain contains crucial blood vessels and cerebrospinal fluid. Aneurysms in these vessels can lead to subarachnoid hemorrhage (SAH), a serious stroke subtype with high morbidity and mortality rates. SAH treatment includes procedures like coiling and clipping, but these are available only at comprehensive stroke centers (CSCs), necessitating urgent diagnosis and transfer to specialized facilities.MethodsThis IRB-approved study was conducted by Polk County Fire Rescue (PCFR) in Florida. PCFR, serving an 850,000-person population, implemented a three-step SAH protocol. The protocol uses both Ottawa SAH criteria and recurring symptoms, such as new-onset seizures and high systolic blood pressure, that were identified by EMS. Acute management included administering labetalol, levetiracetam, and ondansetron.ResultsOf 2175 stroke patients, 80 screened positive for SAH and were eligible for transfer. Patients had a median age of 66, and 33% had an initial systolic BP over 220 mmHg. The interfacility transfer rate dropped from 12.9 to 3.6% after implementing the protocol.ConclusionThe PCFR protocol’s effectiveness suggests its potential for nationwide implementation. Early SAH recognition and prompt transfer to CSCs reduce complications and improve outcomes. Accurate field diagnosis by EMTs can prevent unnecessary transfers and enhance patient care. Future improvements may include portable diagnostic tools and enhanced EMT training to further improve SAH patients’ pre-hospital care.

Analysis of forest fire dangers of the Bryansk region in the zones of radioactive contamination and beyond

The purpose of the study is to analyze the forest fire dangers of the Bryansk region forests, taking into account their radioactive contamination and potential risks for forestry workers involved in forest fires extinguishing. Significant areas of radioactive contamination of forests with a predominance of sites belonging to the classes of high and very high natural fire danger, restrictions on economic activity and a long fire-hazardous period contribute to the occurrence of radioactive forest fires. The analysis of the combined data on forest fires and radioactive contamination of forest areas showed that most forest fires occur outside the zones of radioactive contamination and are not radioactive. The largest number of fires occurs at the beginning of the fire season. Radioactive forest fires in most cases arise from the burning of dry grassy vegetation, as a result of the transition from lands of other categories and through the fault of the population. The average effective dose of additional radiation per a workday can be estimated at 1.96 μSv, and the maximum at ~ 15.4 μSv. Most fires are extinguished in the early stages and do not have time to cover large areas. It indicates the effective work of the forest fire service

Perceptions Experiences and Challenges of Physical Activity among Firefighters with Coronary Heart Disease Risk Factors in the City of Cape Town Fire and Rescue Services

Background The development of atherosclerosis in firefighters is affected by various cardiovascular risk factors, such as smoking, poor dietary choices, and lack of physical activity. Together, these elements lead to obesity, high blood pressure, unhealthy cholesterol, and increased blood sugar levels. Continuous exposure to these risks raises the chances of worsening atherosclerosis, which can impede blood circulation to essential organs like the heart and brain. As a result, sudden cardiac death is the leading cause of fatalities while on duty in the fire service. Aim This study aimed to explore and describe the perceptions, experiences, and challenges associated with physical activity among firefighters with risk factors for coronary heart disease in the City of Cape Town Fire and Rescue Services. Methods A purposive sample of nine full-time active career firefighters from the City of Cape Town Fire and Rescue Services, representing three different ranks, was employed, using a descriptive qualitative study design. The semi-structured interview responses were recorded and transcribed verbatim. The participants were free to leave the study at any time and without penalty, and their rights to confidentiality were protected. The thematic analysis was then used to examine the transcripts. Results The results revealed that firefighters were not physically active enough to meet the suggested minimum levels of physical activity and were physically inactive. Sedentary lifestyles have numerous detrimental effects on the human body, such as elevated rates of dyslipidemia, hypertension, diabetes mellitus, cardiovascular disease mortality, and all-cause death. Therefore, it is essential to reduce sedentary behavior and increase physical exercise to improve the health and well-being of firefighters. Conclusion Policy strategies should be designed to introduce physical activities at low-moderate intensity levels and accommodate firefighters with coronary heart disease risk factors. Implementing team-based physical activity interventions has demonstrated positive impacts on individual behavior changes within the fire service.