Fire safety in healthcare facilities is extremely important due to limited evacuation capacity of occupants. Therefore, poor fire safety precautions lead to more fatalities and financial losses. This study introduces an effective fire risk management approach for healthcare buildings utilizing an interval valued neutrosophic-fuzzy framework. This framework identifies fire risks and determine appropriate safety measures. In addition, essential fire risk criteria in healthcare centers were systematically identified through a multi-factor decision-making process, employing the Fuzzy-Delphi technique and a comprehensive literature review. The proposed framework initially determines the importance weights of these factors using the Interval Valued Neutrosophic-Analytical Hierarchy Process (IVN-AHP). Subsequently, three main parameters - Potential Risk Level (PRL), Acceptance Risk Level (ARL) and Protection Level (PL) - were calculated as alternatives in IVN-AHP technique using novel mathematical equations. A fuzzy inference system (FIS) was then employed to estimate the risk magnitude and subsequently classify departments within the healthcare building based on their risk level. The fire risk control strategy is then determined based on this risk classification. The proposed approach was applied to departments within a hospital in Iran. Its validity was evaluated by comparing the results with the comprehensive Fire Risk Assessment Method for Engineering (FRAME) technique. Additionally, the sensitivity of the IVN-AHP in determining the weights of factors and alternatives was validated using real data. The results revealed that the utilities and kitchen departments exhibited a critical risk class exceeding 50 %. Furthermore, the operating room, laundry, post-NICU 1 and 2, and waste disposal were classified as critical, with more than 50 % falling within the major risk class. A strong correlation coefficient of 99.1 % was observed between the Fire Risk Magnitude (FRM) obtained using the proposed farmwork and the FRM for occupants obtained using the FRAME technique. These findings demonstrate the applicability and reliability of the proposed approach as a valuable tool for risk management and decision-making in healthcare facilities.
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http://dx.doi.org/10.1016/j.heliyon.2025.e41660 | DOI Listing |
Heliyon
January 2025
Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Fire safety in healthcare facilities is extremely important due to limited evacuation capacity of occupants. Therefore, poor fire safety precautions lead to more fatalities and financial losses. This study introduces an effective fire risk management approach for healthcare buildings utilizing an interval valued neutrosophic-fuzzy framework.
View Article and Find Full Text PDFJ Burn Care Res
January 2025
Department of Burn Surgery, Medical University of South Carolina, 171 Ashley Avenue, Charleston SC 29425, USA. MD.
Wildland firefighting is a niche specialization in the fire service - inherently dangerous with unique risks. Over the past decade, fatalities amongst all firefighters have decreased; however, wildland firefighter fatalities have increased. This subject has only been described in the grey literature, and a paucity of medical literature exists.
View Article and Find Full Text PDFBioscience
August 2024
Earth and Environmental Science Department at Lehigh University, Bethlehem, Pennsylvania, United States.
Under climate change, ecosystems are experiencing novel drought regimes, often in combination with stressors that reduce resilience and amplify drought's impacts. Consequently, drought appears increasingly likely to push systems beyond important physiological and ecological thresholds, resulting in substantial changes in ecosystem characteristics persisting long after drought ends (i.e.
View Article and Find Full Text PDFPathogens
January 2025
Centre for Environmental and Marine Studies (CESAM), Departamento de Biologia, Universidade de Aveiro, 3810-193 Aveiro, Portugal.
Globally, forests are constantly threatened by a plethora of disturbances of natural and anthropogenic origin, such as climate change, forest fires, urbanization, and pollution. Besides the most common stressors, during the last few years, Portuguese forests have been impacted by severe decline phenomena caused by invasive pathogens, many of which belong to the genus . The genus includes a large number of species that are invading forest ecosystems worldwide, chiefly as a consequence of global trade and human activities.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.
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