Search Results (48)

Work-related musculoskeletal disorders (WMSDs) are among the most prevalent occupational health issues, particularly affecting public transport drivers due to prolonged sitting, constrained postures, and poorly adaptable cabins. This study addresses the ergonomic risks associated with tram driving, aiming to evaluate biomechanical load and postural stress in relation to drivers’ anthropometric characteristics. A combined methodological approach was applied, integrating two standardized observational tools—RULA and REBA—with anthropometric modeling based on three representatives European morphotypes (SmallW, MidM, and TallM). ErgoFellow 3.0 software was used for digital posture evaluation, and lumbar moments at the L4/L5 vertebral level were calculated to estimate lumbar loading. The analysis was simulation-based, using digital human models, and no real subjects were involved. The results revealed uniform REBA (Rapid Entire Body Assessment) and RULA (Rapid Upper Limb Assessment) scores of 6 across all morphotypes, indicating moderate to high risk and a need for ergonomic intervention. Lumbar moments ranged from 51.35 Nm (SmallW) to 101.67 Nm (TallM), with the tallest model slightly exceeding the recommended ergonomic thresholds. These findings highlight a systemic mismatch between cabin design and user variability. In conclusion, ergonomic improvements such as adjustable seating, better control layout, and driver education are essential to reduce the risk of WMSDs. The study proposes a replicable methodology combining anthropometric, observational, and biomechanical tools for evaluating and improving transport workstation design. Full article

The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO₂ and PM_2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO₂, PM_2.5, and PM₁₀, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems. Full article

In-vehicle physiological sensing is emerging as a vital approach to enhancing driver monitoring and overall automotive safety. This pilot study explores the feasibility of a pressure-based system, repurposing commonplace occupant classification electronics to capture respiration signals during real-world driving. Data were collected from a driver-seat-embedded, fluid-filled pressure bladder sensor during normal on-road driving. The sensor output was processed using simple filtering techniques to isolate low-amplitude respiratory signals from substantial background noise and motion artifacts. The experimental results indicate that the system reliably detects the respiration rate despite the dynamic environment, achieving a mean absolute error of 1.5 breaths per minute with a standard deviation of 1.87 breaths per minute (9.2% of the mean true respiration rate), thereby bridging the gap between controlled laboratory tests and real-world automotive deployment. These findings support the potential integration of unobtrusive physiological monitoring into driver state monitoring systems, which can aid in the early detection of fatigue and impairment, enhance post-crash triage through timely vital sign transmission, and extend to monitoring other vehicle occupants. This study contributes to the development of robust and cost-effective in-cabin sensor systems that have the potential to improve road safety and health monitoring in automotive settings. Full article

(1) Background: This narrative review examines in-vehicle tobacco smoke exposure among private, occupational, and commercial drivers, focusing on prevalence, nicotine biomarkers, and health consequences. (2) Methods: A comprehensive search on the PubMed, Scopus, and Embase databases was used to identify peer-reviewed, full-text, and English articles published between 2014 and 2024. Search terms were related to motor vehicles, tobacco smoke exposure, and drivers. Articles were selected for inclusion based on their relevance to in-vehicle smoking and second- or third-hand smoke exposure attributable to tobacco cigarettes through article title, abstract, and full-text screening. (3) Results: This review highlights the dangers of in-vehicle second- or third-hand smoke exposure, evidenced by the 17 articles included. Significant second-hand smoke exposure and biomarkers were revealed mostly among adolescents and children. However, a gap exists in addressing tobacco smoke exposure among occupational/commercial drivers, specifically, long-haul truck drivers (LHTDs), who have heightened exposure due to their work environment—the truck cabin—which may increase their lung cancer risk. (4) Conclusions: There is a significant literature gap regarding in-vehicle tobacco smoke exposure in occupational/commercial drivers. Future research should include nicotine biomarker usage to quantify nicotine exposures and smoking cessation intervention development tailored to LHTDs. Full article

As the world’s largest open-pit coal producer, China faces severe dust pollution in mining operations. Cabins of mining equipment (electric shovels, haul trucks, drills) exhibit unique micro-environmental contamination due to dual-source pollution (external infiltration and internal secondary dust generation), posing severe health risks to miners. This study focused on electric shovel cabins at the Heidaigou open-pit coal mine to address cabin dust pollution. Through analysis of dust physicochemical properties, a pollution characteristic database was established. Field measurements and statistical methods revealed temporal–spatial variation patterns of dust concentrations, quantifying occupational exposure risks and providing theoretical foundations for dust control. A novel gradient-pressurized air purification system was developed for harsh mining conditions. Key findings include the following. (1) Both coal-shovel and rock-shovel operators were exposed to Level I (mild hazard level), with rock-shovel operators approaching Level II (moderate hazard level). (2) The system reduced respirable dust concentrations from 0.313 mg/m³ to 0.208 mg/m³ (≥33.34% improvement) in coal-shovel cabins and from 0.625 mg/m³ to 0.421 mg/m³ (≥32.64% improvement) in rock-shovel cabins. These findings offer vital guidance for optimizing cabin design, improving dust control, and developing scientific management strategies, thereby effectively protecting miners’ health and ensuring operational safety. Full article

The recent events impacting public health highlight the need for investigating airflow patterns in confined spaces like elevator cabins. It is essential to ensure proper ventilation, prevent the accumulation of contaminants, and ultimately promote a healthy indoor environment for occupants. In this study, an evaluation of the airflow distribution, temperature, and mean age of air control within an occupied elevator cabin is presented. For that, a CFD model that simulated the airflow patterns in an elevator cabin was developed, validated, and used to conduct the study under six air ventilation scenarios, involving mechanical ventilation with air curtains or displacement flows. The proposed ventilation configurations in Cases 2–6 enhanced the airflow circulation within the elevator. Among these configurations, Case 4, a case of displacement flow, exhibited the most favourable conditions, providing an ACH of 27.05, a mean air age of 84.45 s in the breathable plane, an air change effectiveness of 1.478, and a temperature of 25 °C near the doors and around the occupied zone. It is important to highlight Case 3, which had a lower ACH of 21.2 compared to Case 4. Despite this, Case 3 presented a mean average air age of approximately 122.84 s and an air change effectiveness of 1.309. Based on these findings, displacement ventilation (Case 4) is recommended as the most effective configuration, followed by Case 3, which also showed improved air circulation compared to the other scenarios. The results evidence that the ventilation configuration is particularly influential when aiming to promote air ventilation and improve air age conditions in elevator cabins. Full article

A car cabin’s small volume makes it vulnerable to discomfort if temperature, humidity, and carbon dioxide levels are poorly regulated. In electric vehicles, the HVAC system draws energy from the car battery, reducing the driving range by several dozen kilometres under extreme conditions. A 1D simulation model calibrated for the Renault ZOE was used to evaluate the effects of ventilation parameters on thermal comfort, humidity, and power consumption. The results highlighted the interdependence of factors such as the recirculation ratio and blower flow rate, showing that energy-efficient settings depend on ambient conditions and other factors (such as occupancy, vehicle speed, infiltration). Adjustments can reduce heat pump energy use, but no single setting optimally balances power consumption and thermal comfort across all scenarios. The opti-CO₂ mode is proposed as a trade-off, offering energy savings while maintaining safety and comfort. This mode quickly achieves the cabin temperature target, limits carbon dioxide concentration at a safe level (1100 ppm), minimises fogging risks, and reduces heat pump power consumption. Compared to fresh air mode, the opti-CO₂ mode extends the driving range by 9 km in cold conditions and 26 km in hot conditions, highlighting its potential for improving energy efficiency and occupant comfort in electric vehicles. Full article

This systematic literature review (SLR) focuses on indoor environmental quality (IEQ) in passenger transport vehicles within tropical and subtropical regions. It specifically examines indoor air quality (IAQ), thermal comfort (TC), acoustic comfort (AC), and visual comfort (VC) of passenger vehicle cabins (PVCs) in auto rickshaws, sedans, trucks, bus rapid transits (BRTs), buses, trains, trams, metro systems, aircraft and ferries of tropical and subtropical regions. The SLR used the PRISMA approach to identify and review scientific studies between 2000 and 2024 on the IEQ of PVCs in the tropics. Studies reviewed were found in SCOPUS, Web of Science, Science Direct, and EBSCO databases including relevant citation references. Findings reveal a significant geographical imbalance in research, with most studies concentrated in tropical Asia (78.2%), while sub-Saharan Africa (8.2%), South America (11.8%), and Oceania (1.8%) are considerably underrepresented. In 113 studies, most addressed IAQ and TC but limited attention to AC and VC. Moreover, fewer studies have jointly addressed all the IEQ parameters, highlighting the need for a more comprehensive approach to IEQ for tropical PVCs. Several studies alluded to in-cabin commuter risk linked to PM_2.5, PM₁₀, carbon monoxide (CO), and volatile organic compounds (VOCs). These risks are exacerbated by traffic hotspots, poor ventilation, ambient pollution, overcrowding, and poor vehicle conditions. Additionally, thermal discomfort is compounded by extreme heat loads, inefficient HVAC systems, and high vehicle occupancy. Common gaps include a paucity of IEQ studies and inadequate IEQ regulations or adapted standards in developing tropics. Infrastructural and regulatory deficiencies have been identified, along with strategies for mitigation. Recommendations are for more holistic IEQ studies in the tropics, including exposure studies for emerging gaps in new indoor pollutants, integration of AI and IoT for sustainable ventilation strategies, and development of effective regulatory frameworks considering region-specific conditions. Finally, Policymakers are encouraged to establish localized IEQ standards, enforce regulations, and prioritize upgrades to transport infrastructure. The SLR findings emphasize the urgent need for targeted interventions in developing tropical regions to address disparities in IEQ, ensuring healthier and more sustainable transport environments that could be replicated across transport systems worldwide. Full article

Ensuring operational safety within high-risk environments, such as construction sites, is paramount, especially for tower crane operations where distractions can lead to severe accidents. Despite existing behavioral monitoring approaches, the task of identifying small yet hazardous objects like mobile phones and cigarettes in real time remains a significant challenge in ensuring operator compliance and site safety. Traditional object detection models often fall short in crane operator cabins due to complex lighting conditions, cluttered backgrounds, and the small physical scale of target objects. To address these challenges, we introduce YOLO-TC, a refined object detection model tailored specifically for tower crane monitoring applications. Built upon the robust YOLOv7 architecture, our model integrates a novel channel–spatial attention mechanism, ECA-CBAM, into the backbone network, enhancing feature extraction without an increase in parameter count. Additionally, we propose the HA-PANet architecture to achieve progressive feature fusion, addressing scale disparities and prioritizing small object detection while reducing noise from unrelated objects. To improve bounding box regression, the MPDIoU Loss function is employed, resulting in superior accuracy for small, critical objects in dense environments. The experimental results on both the PASCAL VOC benchmark and a custom dataset demonstrate that YOLO-TC outperforms baseline models, showcasing its robustness in identifying high-risk objects under challenging conditions. This model holds significant promise for enhancing automated safety monitoring, potentially reducing occupational hazards by providing a proactive, resilient solution for real-time risk detection in tower crane operations. Full article

Aircraft cabins have high occupant densities and may introduce the risk of COVID-19 contamination. In this study, a segment of a Boeing 767 aircraft cabin with a mixing type of air distribution system was investigated for COVID-19 deposition. A section of a Boeing 737-300 cabin, featuring four rows with 28 box-shaped mannequins, was used for simulation. Conditioned air entered through ceiling inlets and exited near the floor, simulating a mixed air distribution system. Cough droplets were modeled using the Discrete Phase Model from two locations: the centre seat in the second row and the window seat in the fourth row. These droplets had a mean diameter of 90 µm, an exhalation velocity of 11.5 m/s and a flow rate of 8.5 L/s. A high-quality polyhedral mesh of about 7.5 million elements was created, with a skewness of 0.65 and an orthogonality of 0.3. The SIMPLE algorithm and a second-order upwind finite volume method were used to model airflow and droplet dynamics. It was found that the ceiling accounted for the maximum concentration followed by the seats. The concentration of deposits was almost 50% more when the source was at window as compared to the centre seat. The Covid particles resided for longer duration when the source was at the centre of the cabin than when it was located near the widow. Full article

Firefighters can be exposed to complex mixtures of airborne substances, including hazardous substances released during structural fires. This study employed silicone wristbands (SWBs) as passive samplers to investigate potential exposure to polycyclic aromatic hydrocarbons (PAHs) and flame retardants (FRs). SWBs were deployed at different areas of four fire stations, in four truck cabins, and at an office control location; they were also donned outside the jackets of 18 firefighters who responded to fire calls. Overall, office areas had significantly lower PAHs than fire station areas. Vehicle bays and truck cabins had significantly higher concentrations of low molecular weight (LMW) PAHs than sleeping and living room areas. For organophosphate ester flame retardants (OPFRs), tri-n-butyl phosphate (TnBP) and tris(1-chloro-2-propyl) phosphate (TCPP) were detected in all the samples; 2-ethylhexyl diphenyl phosphate (EHDPP) was more frequently detected in the fire station areas. Triphenyl phosphate (TPP) concentrations were highest in the truck cabin and office areas, and tris(1,3-dichloro-2-propyl)phosphate (TDCPP) was highest in truck cabins. Thirteen of 16 PAHs and nine of 36 OPFRs were detected in all the SWBs worn by firefighters, and tris (2-butoxyethyl) phosphate (TBEP) was the predominant OPFR. Levels of LMW PAHs were significantly lower when firefighters did not enter the fire. LMW PAHs, HMW (high molecular weight) PAHs, and EHDPP were significantly elevated when heavy smoke was reported. This work highlights the potential for occupational exposure to PAHs and flame retardants in some fire station areas; moreover, factors that may influence exposure during fire suppression. Whilst firefighters’ occupational exposure to PAHs is likely related to fire suppression and exposure to contaminated gear and trucks, exposure to OPFRs may be more related to their presence in truck interiors and electronics. Full article

Adding occupants to an enclosed space often leads to perceptible changes in the sound field and, therefore, speech intelligibility; however, this issue has not yet been examined in automotive cabins. This study investigated the effect of occupants in an automotive cabin on SI. Binaural room impulse responses (BRIRs) were measured in an automotive cabin with an artificial mouth and dummy head under different speaker–listener position configurations and occupancy modes. Based on the measured BRIRs, the speech transmission index (STI) was determined, and subjective speech–reception thresholds (SRTs) in Mandarin Chinese were assessed. The results indicate that speech intelligibility mostly decreased slightly after adding additional occupants. In most cases, the occupants did not significantly affect speech intelligibility, with STI variations of no more than the just-noticeable difference and SRT variation within 1 dB. When the listener was in the back-right seat, the effect of the occupants on speech intelligibility could not be ignored, with STI variations of up to 0.07 and an SRT variation of 2 dB under different occupancy modes. In addition, the influence of front-row passengers on the speech intelligibility of rear-row listeners was extremely small, and vice versa. Furthermore, altering the distribution of occupants had an effect comparable to changing the number of occupants. Full article

In-cabin occupancy detection has become increasingly important due to incidents involving children left in vehicles under extreme temperature conditions. Frequency modulated continuous wave (FMCW) radars are widely used for non-contact monitoring and sensing applications, particularly for occupancy detection. However, the confined and metallic environment inside vehicle cabins presents significant challenges due to multipath reflections. This paper introduces a novel approach that detects the occupied space in each seat to determine occupancy, using the variance of detected points as an indicator of volume occupancy. In an experimental study involving 70 different scenarios with single and multiple subjects, we classify occupants in each seat into one of three categories: adult, baby, or empty. The proposed method achieves an overall accuracy of 96.7% using an Adaboost classifier and a miss-detection rate of 1.8% for detecting babies. This approach demonstrates superior robustness to multipath interference compared to traditional energy-based methods, offering a significant advancement in in-cabin occupancy detection technology. Full article

The civil aircraft cabin is enclosed and highly occupied, making it susceptible to a decline in indoor environmental quality. The environmental quality of civil aircraft cabins not only depends on objective factors such as temperature, relative humidity, and the presence of air pollutants such as carbon dioxide (CO₂), carbon monoxide (CO), ozone (O₃), particle matter (PM), and volatile organic compounds (VOCs) but also the subjective factors pertaining to the perceptions and health symptoms of passengers and crew. However, few studies have thoroughly examined the air quality and thermal comfort parameters that are measured during in-flight testing in airplane cabins, as well as the passengers’ subjective perceptions. In order to evaluate the in-flight thermal comfort and air quality status, this study conducted a review of the recent literature to compile data on primary categories, standard limits, and distribution ranges of in-flight environmental factors within civil aircraft cabins. Following a search procedure outlined in this paper, 54 papers were selected for inclusion. Utilizing the Monte Carlo method, the Predicted Mean Vote (PMV) distributions under different exercise intensities and clothing thermal resistance were measured with the in-cabin temperature and humidity from in-flight tests. Recommendations based on first-hand data were made to maintain the relative humidity in the cabin below 40%, ensure wind speed remains within the range of 0–1 m/s, and regulate the temperature between 25–27 °C (for summer) and 22–27 °C (for winter). The current estimated cabin air supply rate generally complies with the requirements of international standards. Additionally, potential carcinogenic and non-carcinogenic risks associated with formaldehyde, benzene, tetrachloroethylene, and naphthalene were calculated. The sorted data of in-flight tests and the evaluation of the subjective perception of the occupants provide an evaluation of current cabin thermal comfort and air quality status, which can serve as a reference for optimizing indoor environmental quality in future generations of civil aircraft cabins. Full article

Thermal comfort is very important for the well-being and safety of vehicle occupants, as discomfort can elevate stress, leading to distracted attention and slower reaction times. This creates a riskier driving environment. Addressing this, high-induction air diffusers emerge as a significant innovation, enhancing indoor environmental quality (IEQ) by efficiently mixing cool air from the heating ventilation and air conditioning (HVAC) system with the cabin’s ambient air. This process ensures uniform airflow, diminishes temperature discrepancies, prevents draft sensations, and boosts overall air quality by improving air circulation. In addition to enhancing thermal comfort in vehicles, the novel air diffuser also offers significant potential for personalized ventilation systems, allowing for individualized control over airflow and temperature, thereby catering to the specific comfort needs of each occupant. This study introduces a novel air diffuser that demonstrates a 48% improvement in air entrainment compared to traditional diffusers, verified through Ansys Fluent simulations and laser Doppler velocimetry (LDV) measurements. At a fresh airflow rate of 31.79 m³/h, the total air entrainment rate at 0.6 m for the standard air diffuser is 73.36 m³/h, while for the innovative air diffuser, it is 109.26 m³/h. This solution has the potential to increase the level of thermal comfort and air quality within vehicles, and also signals potential applications across various enclosed spaces, underscoring its importance in advancing automotive safety and environmental standards. Full article