Search Results (141)

Air pollution poses a growing threat to public health and the environment, highlighting the need for continuous and precise urban air quality monitoring. The aim of this study was to implement and evaluate an autonomous air quality monitoring platform developed by the University of Ruse, “Angel Kanchev”, under Bulgaria’s National Recovery and Resilience Plan (project BG-RRP-2.013-0001), co-financed by the European Union through the NextGenerationEU initiative. The system, based on Libelium’s mobile sensor technology, was installed at a height of two meters on the university campus near Rodina Boulevard and operated continuously from 1 March 2024 to 30 March 2025. Every 15 min, it recorded concentrations of CO, CO₂, NO₂, SO₂, PM₁, PM_2.5, and PM₁₀, along with meteorological parameters (temperature, humidity, and pressure), transmitting the data via GSM to a cloud-based database. Analyses included a distributional assessment, Spearman rank correlations, Kruskal–Wallis tests with Dunn–Sidak post hoc comparisons, and k-means clustering to identify temporal and meteorological patterns in pollutant levels. The results indicate the high operational stability of the system and reveal characteristic pollution profiles associated with time of day, weather conditions, and seasonal variation. The findings confirm the value of combining calibrated IoT systems with advanced statistical methods to support data-driven air quality management and the development of predictive environmental models. Full article

This article presents the design, implementation, and validation of a Remotely Piloted Safety Cone (RPSC), an autonomous robotic system developed to enhance safety and operational efficiency in road maintenance. The RPSC addresses challenges associated with road works, including workers’ exposure to traffic hazards and inefficiencies of traditional traffic cones, such as manual placement and retrieval, limited visibility in low-light conditions, and inability to adapt to dynamic changes in work zones. In contrast, the RPSC offers autonomous mobility, advanced visual signalling, and real-time communication capabilities, significantly improving safety and operational flexibility during maintenance tasks. The RPSC integrates sensor fusion, combining Global Navigation Satellite System (GNSS) with Real-Time Kinematic (RTK) for precise positioning, Inertial Measurement Unit (IMU) and encoders for accurate odometry, and obstacle detection sensors within an optimised navigation framework using Robot Operating System (ROS2) and Micro Air Vehicle Link (MAVLink) protocols. Complying with European regulations, the RPSC ensures structural integrity, visibility, stability, and regulatory compliance. Safety features include emergency stop capabilities, visual alarms, autonomous safety routines, and edge computing for rapid responsiveness. Field tests validated positioning accuracy below 30 cm, route deviations under 15 cm, and obstacle detection up to 4 m, significantly improved by Kalman filtering, aligning with digitalisation, sustainability, and occupational risk prevention objectives. Full article

This paper proposes a high-reliability power conversion system optimized for Urban Air Mobility (UAM) applications, which utilizes silicon carbide (SiC) chopper modules within a hybrid fuel cell and battery structure. The system features a redundant power configuration that employs both a main and an auxiliary battery to ensure continuous and stable power supply, even under emergency or fault conditions. By integrating SiC-based power converters, the proposed system achieves high efficiency, low switching losses, and enhanced thermal performance, which are crucial for the space- and weight-constrained environment of UAM platforms. Furthermore, a robust control strategy is implemented to enable smooth transitions between multiple power sources, maintaining operational stability and safety. System-level simulations were conducted using PowerSIM to validate the performance and reliability of the proposed architecture. The results demonstrate its effectiveness, making it a strong candidate for future UAM power systems requiring lightweight, efficient, and fault-tolerant power solutions. Full article

The accurate and reliable positioning of unmanned aerial vehicles (UAVs) in urban environments is crucial for urban air mobility (UAM) application, such as logistics, surveillance, and disaster management. However, global navigation satellite systems (GNSSs) often fail in densely populated areas due to signal reflections (multipath propagation) and obstructions non-line-of-sight (NLOS), causing significant positioning errors. To address this, we propose a machine learning (ML) framework that integrates 5G position reference signals (PRSs) to correct UAV position estimates. A dataset was generated using MATLAB’s UAV simulation environment, including estimated coordinates derived from 5G time of arrival (TOA) measurements and corresponding actual positions (ground truth). This dataset was used to train a fully connected feedforward neural network (FNN), which improves the positioning accuracy by learning patterns between predicted and actual coordinates. The model achieved significant accuracy improvements, with a mean absolute error (MAE) of 1.3 m in line-of-sight (LOS) conditions and 1.7 m in NLOS conditions, and a root mean squared error (RMSE) of approximately 2.3 m. The proposed framework enables real-time correction capabilities for dynamic UAV tracking systems, highlighting the potential of combining 5G positioning data with deep learning to enhance UAV navigation in urban settings. This study addresses the limitations of traditional GNSS-based methods in dense urban environments and offers a robust solution for future UAV advancements. Full article

Electric helicopters represent a pivotal component in the advancement of urban air mobility (UAM), with considerable potential for future development. The electric propulsion system (EPS) is the core component of these systems. However, the inherent complexities of electromechanical coupling can induce excessive torsional vibrations, potentially compromising operational comfort and even threatening flight safety. This study proposes an active torsional vibration suppression method for EPS that explicitly incorporates electromechanical coupling characteristics. A nonlinear dynamic model has been developed, accounting for time-varying meshing stiffness, meshing errors, and multi-harmonic motor excitation. The motor and transmission system models are coupled using torsional angular displacement. A harmonic current command generation algorithm is then formulated, based on the analysis of harmonic torque-to-current transmission characteristics. To achieve dynamic tracking and the real-time compensation of high-order harmonic currents under non-steady-state conditions, a high-order resonant controller with frequency-domain decoupling characteristics was designed. The efficacy of the proposed harmonic current modulation is verified through simulations, showing an effective reduction of torsional vibrations in the EPS under both steady-state and non-steady-state conditions. It decreases the peak dynamic meshing force by 4.17% and the sixth harmonic amplitude by 88.15%, while mitigating overshoot and accelerating vibration attenuation during speed regulation. The proposed harmonic current modulation method provides a practical solution for mitigating torsional vibrations in electric propulsion systems, enhancing the comfort, reliability, and safety of electric helicopters. Full article

Ammonium nitrate (NH₄NO₃) is a major constituent of fine particulate matter (PM_2.5), playing a critical role in air quality and atmospheric chemistry. However, the dual regulatory role of ammonia (NH₃) in both the formation and volatilization of NH₄NO₃ under ambient atmospheric conditions remains inadequately understood. To address this gap, we conducted high-resolution field measurements at a clean tropical coastal site in China using an integrated system of Aerosol Ion Monitor-Ion Chromatography, a Scanning Mobility Particle Sizer, and online OC/EC analyzers. These observations were complemented by thermodynamic modeling (E-AIM) and source apportionment via a Positive Matrix Factorization (PMF) model. The E-AIM simulations revealed persistent thermodynamic disequilibrium, with particulate NO₃⁻ tending to volatilize even under NH_3gas-rich conditions during the northeast monsoon. This suggests that NH₄NO₃ in PM_2.5 forms rapidly within fresh combustion plumes and/or those modified by non-precipitation clouds and then undergoes substantial evaporation as it disperses through the atmosphere. Under the southeast monsoon conditions, reactions constrained by sea salt aerosols became dominant, promoting the formation of particulate NO₃⁻ while suppressing NH₄NO₃ formation despite ongoing plume influence. In scenarios of regional accumulation, elevated NH₃ concentrations suppressed NH₄NO₃ volatilization, thereby enhancing the stability of particulate NO₃⁻ in PM_2.5. PMF analysis identified five source factors, with NO₃⁻ in PM_2.5 primarily associated with emissions from local power plants and the large-scale regional background, showing marked seasonal variability. These findings highlight the complex and dynamic interplay between the formation and evaporation of NH₄NO₃ in NH_3gas-rich coastal atmospheres. Full article

The integration of unmanned aerial vehicles (UAVs) into urban air mobility (UAM) systems necessitates reliable and uninterrupted communication infrastructure to ensure safety, control, and data continuity within designated air corridors. This paper proposes and evaluates four radio repeater deployment strategies to support robust UAV communication in urban environments: Strategy 1 with non-overlapping radio coverage, Strategy 2 with fully overlapping coverage zones, Strategy 3 with alternating redundancy between repeater pairs, and Strategy 4 with full duplication of overlapping coverage. A continuous-time Markov modeling approach is employed to quantify communication availability under varying traffic loads and failure conditions. The strategies are assessed based on infrastructure requirements, reliability performance, and suitability for segmented and non-linear corridor geometries. The results show that increasing redundancy significantly improves reliability: for example, channel unavailability drops from 35% under Strategy 1 (no redundancy) to less than 0.5% under Strategy 4 (full duplication). Strategy 3 achieves a balanced performance, maintaining unavailability below 1% with approximately 50% fewer resources than Strategy 4. A case study in the Greenline district of Astana, Kazakhstan, illustrates the practical application of the framework, demonstrating how hybrid deployment strategies can address different operational and environmental demands. The results show that increasing redundancy significantly enhances availability, with Strategy 3 offering the most efficient balance between reliability and resource use. The proposed methodology provides a scalable foundation for designing resilient UAV communication systems to support future urban airspace operations. Full article

Climate conditions in combination with the concentration of pollutants increase the human health stress and exacerbate systemic diseases. The city of Rhodes is a desirable tourist destination that is located in a sensitive climate region of the southeastern Aegean Sea in the Mediterranean region. In this work, hourly recordings from a mobile air quality monitoring system, which is located in an urban area of Rhodes city, are employed in order to measure the concentration of regulated pollutants (${\mathrm{S}\mathrm{O}}_2,{\mathrm{N}\mathrm{O}}_2,{\mathrm{O}}_3,{\mathrm{P}\mathrm{M}}_{10} \mathrm{a}\mathrm{n}\mathrm{d} {\mathrm{P}\mathrm{M}}_{2.5})$ and meteorological factors (pressure, temperature, and relative humidity). The air quality health index (AQHI) and the discomfort index (DI) are calculated to study the impact of air quality and meteorological conditions on human health. The analysis is conducted during a hot summer period, from 29 June to 14 July 2024. During the second half of the studied period, a heatwave episode occurred that affected the bioclimatic conditions over the city. The results show that despite the fact that the concentration of pollutants is lower than the pollutant thresholds (according to Directive 2008/50/EC), the AQHI and DI conditions degrade significantly over the heatwave days. In particular, the AQHI is classified in the “Moderate” class, and the DI indicates that most of the population suffers discomfort. The AQHI and DI simultaneously increase during the days of the heat episode, showing a possible negative synergy for the health risk. Finally, both the day maximum and night minimum temperature are increased (about 0.8 and 0.6 °C, respectively) during the heatwave days as compared to the whole studied period. Full article

A thermodynamic analysis of a compact hydrogen generation system for mobile fuel cell applications is presented. The system consists of a miniature autothermal steam reformer (ATR) and a water–gas shift (WGS) reactor, designed to produce hydrogen from hydrocarbon fuels for a 1 kW proton exchange membrane (PEM) fuel cell. Methane is used as the model fuel, and the study focuses on optimizing feed compositions and operational conditions to maximize hydrogen yield and purity. Feed compositions and operational conditions are optimized. In total, 0.7 Nm³ h⁻¹ H₂ is generated from 0.25 Nm³ h⁻¹ CH₄ with properly adjusted steam and air feeding. Issues with product purity and start-up procedures have been identified and discussed, along with feasible solutions. The system is suitable for remote and mobile applications. Full article

The development of advanced air mobility—an eco-friendly, next-generation transportation system—is underway and garners significant attention. Due to the novel propulsion concept of eVTOL (electric Vertical Take-Off and Landing) and its operation in low altitude, urban environment, regulations for commercialization have not yet been established. Consequently, related research on passenger safety in emergency landings is ongoing, and this study focuses on enhancing the crashworthiness of advanced air mobility. To ensure the crashworthiness of advanced air mobility, civil airworthiness standards were referenced to determine the appropriate test conditions, and a design criterion for developing an energy-absorbing structure was derived. In this study, lattice structures are considered for designing an energy-absorbing structure that satisfies the design criterion, and finite element analysis is conducted to predict the performance of lattice structures. Based on the predicted data, surrogate models are constructed using the Kriging method according to the type of lattice structure. To verify the data obtained from numerical models, representative structures are manufactured using EBM (Electron Beam Melting) technology, and compressive tests are conducted to obtain the force–displacement curves. The test data are compared with the numerical data, and it is confirmed that the test data show good agreement with the numerical data. After this confirmation, the constructed surrogate models are utilized to select a lattice-based energy-absorbing structure that satisfies the crashworthiness-related design criterion. Finally, a crash simulation of a vertical drop test is carried out using the selected lattice structure, and results indicate that the resulting acceleration due to the collision is below the human tolerance limit, thereby verifying the crashworthiness of the energy-absorbing structure. Full article

This paper focuses on the use of Frequency-Modulated Continuous Wave radars as an aiding source to provide precision navigation during approach and landing operations in Advanced Air Mobility scenarios. Specifically, the radar system requirements are delineated through an analysis of operational constraints defined by regulatory guidelines, including approach trajectories and vertiport infrastructure to ensure compatibility with Urban Air Mobility scenarios. A preliminary radar design is proposed which is integrated within a multi-sensor navigation architecture including a GNSS receiver, an inertial measurement unit, and two cameras. The radar is designed to detect high-reflectivity targets placed in the landing area and uses a matching algorithm to associate these detections with their known positions, enabling reliable corrections to the aircraft navigation state. Radar measurements are tightly integrated into an Extended Kalman Filter alongside data from other sensors, refining the vehicle navigation state estimate and ensuring seamless transitions between long-range and short-range sensing modalities. A high-fidelity simulation environment validates the proposed multi-sensor architecture under different visibility conditions and accordingly disactivating the radar to validate its contribution. The results demonstrate significant improvements in navigation performance when the radar is integrated within the multi-sensor architecture thanks to its important role in providing accurate estimates at high ranges from the landing pattern and during low-visibility operations. The reported statistics of the multi-sensor architecture performance are compared with the assumed required navigation performance in the scenarios of interest, demonstrating the radar contribution and showing the effects of designed radar angular resolution on the multi-sensor architecture. Full article

The expansion of Urban Air Mobility (UAM) has led to diverse aircraft designs, with piloted systems expected to evolve into remotely piloted and automated operations. Future advancements in Intelligent Transportation Systems (ITSs) will further improve automation capabilities, promising significant benefits to the environment and overall efficiency of UAM aircraft. However, UAM aircraft face unique operational conditions that need to be accounted for when assessing safety risks, such as lower operating altitudes and hazards present in urban settings, thus leading to a potential increased risk of collisions with foreign objects, particularly birds and drones. This paper reviews historical safety data with an aim to better assess the potential risks of UAM aircraft. A survey was conducted to gather quantitative and qualitative insights from subject matter experts, reinforcing findings from existing studies. The results highlight the need for a comprehensive risk assessment framework to guide design improvements and regulatory strategies, ensuring safer UAM operations. Full article

The accuracy of ultrasonic rangefinders is crucial for mobile robotic navigation systems, yet environmental factors such as temperature, humidity, atmospheric pressure, and wind conditions can influence ultrasonic speed in the air. The primary objective is to investigate how environmental factors influence the output signal of an ultrasonic emitter and to develop a method for improving the accuracy of distance measurements in both outdoor and indoor settings. The research employs a combination of theoretical modeling, statistical analysis, and experimental validation. The research employs an ultrasonic rangefinder integrated with environmental sensors (BME280, Bosch Sensortec GmbH, Kusterdingen, Germany) and wind sensors (WMT700, WINDCAP^®, Vaisala Oyj, Vantaa, Finland) to account for environmental influences. Experimental studies were conducted using a prototype ultrasonic rangefinder, and statistical analysis (Student’s t-test) was performed on collected data. The results of estimation by Student’s t-test for 256 measurements demonstrate the maximum effect of air temperature and the minimum effect of relative air humidity on a piezoelectric emitter output signal both outdoors and indoors. In addition, wind parameters affect the rangefinder’s operation. The maximum range of obstacle detection depends on the reflection coefficient of the material that covers the obstacle. The results align with theoretical expectations for highly reflective surfaces. A cascade-forward artificial neural network model was developed to refine distance estimations. This study demonstrates the importance of considering environmental factors in ultrasonic rangefinder systems for mobile robots. By integrating environmental sensors and using statistical analysis, the accuracy of distance measurements can be significantly improved. The results contribute to the development of more reliable navigation systems for mobile robots operating in diverse environments. Full article

Motivated by the strong transition to electric mobility we are witnessing currently, in this paper, we present a novel methodology to predict the dynamic behavior of heat, ventilation and air conditioning (HVAC) systems for electric vehicles. The approach is based on a lumped parameter energy balance between the vehicle cabin, the external loads (such as solar radiation, ventilation and metabolic load) and the HVAC system. Detailed models are used to obtain the time evolution of the heat transfer coefficients of each subsystem in the HVAC (i.e., evaporator and condenser) on the basis of correlations available in the literature. The model is validated on a real HVAC system, built ad hoc for a retrofitted electric vehicle, by comparing the results obtained from the model with experimental measurements performed in a climatic chamber. Then, some scenarios that represent interesting cases in electric automotive applications, such as vehicle cabin precooling during battery charging and a regulated driving cycle which simulates urban mobility, are considered. The energy consumption of the HVAC system is evaluated from the model in these scenarios and compared. The methodology herein presented is general and easily extendable to other systems, proving to be a powerful method to compare the energy consumption of HVAC systems under unsteady conditions with a more standard approach based on steady considerations. By this approach, it is shown that significant improvement can be obtained with a nonsteady approach. Full article

Current lifestyles bring about an increasing prevalence of unhealthy habits that can negatively affect male fertility. Cigarette smoking, alcohol intake, stress, inadequate physical activity, an unequilibrated diet leading to obesity, and use of mobile telephones and portable electronic devices can affect the male reproductive system through multiple mechanisms. Moreover, the modern man is often exposed to environmental factors independent of his will, such as air pollution, exposure to heat or toxicants in his workplace, or the presence of harmful chemicals in food, beverages, agricultural and industrial products, etc. The susceptibility to these factors depends on genetic and epigenetic predisposition, potentially present systemic disease and medication, and local affections of the genitourinary system. The multifaceted nature of both the causative factors and the susceptibility background makes the resulting fertility disturbance highly individual and variable among different men exposed to the same conditions. This paper critically reviews the current knowledge of different causative and susceptibility factors with a special attention to the molecular mechanisms of their action. Finally, strategies for the prevention of abnormalities due to lifestyle and environmental factors and available treatment modalities for already-present abnormalities are exposed. Full article