Search Results (581)

Indoor air quality (IAQ) is a critical determinant of respiratory health and plays an essential role in asthma management. Exposure to indoor pollutants such as particulate matter (PM_2.5), volatile organic compounds (VOCs), and biological allergens can exacerbate asthma symptoms. This pilot quasi-experimental, one-group pretest–posttest study evaluated the combined effect of high-efficiency particulate air (HEPA) purifiers and tailored asthma education on the IAQ and asthma outcomes of 30 adults diagnosed with asthma. Indoor PM_2.5, total VOCs (tVOC), temperature, and relative humidity were monitored using low-cost air quality monitors across three home locations for 30 days, and participants completed baseline and follow-up assessments of asthma control (ACQ) and quality of life (AQLQ). The intervention reduced PM_2.5 concentrations from 21.32 µg/m³ to 18.19 µg/m³ (p < 0.001), while tVOC levels increased slightly from 237.05 ppb to 251.81 ppb (p = 0.02). The median ACQ scores improved from 1.17 to 0.50 (p < 0.001), the proportion of participants with well-controlled asthma (ACQ ≤ 0.75) rose from 30% to 66.7%, and the median AQLQ scores increased from 5.75 to 6.30 (p < 0.001). Participants in the intervention experienced significantly improved asthma control, quality of life, and indoor PM_2.5 levels, which underscores the significance of integrating environmental and educational strategies in adult asthma management. Full article

Heating, ventilation, and air conditioning (HVAC) systems account for a significant portion of building energy consumption and play a crucial role in maintaining indoor comfort. However, hidden faults in air-handling units (AHUs) often lead to energy waste and degraded performance, highlighting the importance of reliable fault detection and diagnosis (FDD). This study proposes a simulation-driven FDD framework that integrates a standardized prototype dataset and an independent evaluation dataset generated from a calibrated EnergyPlus model representing a target facility, enabling controlled experimentation and transfer evaluation within simulation environments. Training data were generated from the DOE EnergyPlus Medium Office prototype model, while evaluation data were obtained from a calibrated building-specific EnergyPlus model of a research facility operated by Company H in Korea. Three representative fault scenarios—outdoor air damper stuck closed, cooling coil fouling (65% capacity), and air filter fouling (30% pressure drop)—were systematically implemented. A Deep Belief Network (DBN) classifier was developed and optimized through a two-stage hyperparameter tuning strategy, resulting in a three-layer architecture (256–128–64 nodes) with dropout and regularization for robustness. The optimized DBN achieved diagnostic accuracies of 92.4% for the damper fault, 98.7% for coil fouling, and 95.9% for filter fouling. These results confirm the effectiveness of combining simulation-based dataset generation with advanced deep learning methods for HVAC fault diagnosis. The results indicate that a DBN trained on a standardized EnergyPlus prototype can transfer to a second, independently calibrated EnergyPlus building model when AHU topology, control logic, and monitored variables are aligned. This study should be interpreted as a simulation-based proof-of-concept, motivating future validation with field BMS data and more diverse fault scenarios. Full article

Air conditioning loads play a critical role in maintaining the supply–demand balance of building microgrids (BMGs), yet their distributed nature and volatile response may undermine secure and stable operation. This paper proposes a day-ahead and real-time aggregated control strategy for BMG air conditioning loads with user privacy protection. First, an approximate aggregation model is developed based on building heat transfer characteristics, and the aggregated response potential is evaluated by jointly considering user comfort and willingness. Second, without sharing fine-grained user information, a Building Microgrid Operator (BMO)–Load Aggregator (LA) day-ahead distributed-scheduling model is formulated and solved using the alternating direction method of multipliers (ADMM). Finally, to address load fluctuations caused by heterogeneous initial indoor temperature distributions, a real-time control strategy based on State-Queueing (SQ) temperature-state pre-transfer is proposed. Case studies show that, compared with the baseline scheme, the proposed method reduces the system operating cost from CNY 50,694.58 to CNY 47,131.64, a 7% decrease, and decreases load shedding from 1466.35 kWh to 257.31 kWh, an 82% decrease. Meanwhile, the real-time control effectively suppresses power fluctuations in the early control stage, thereby improving both economic performance and response smoothness. Full article

This exploratory study addresses the problem of limited research on quality assessments of newly emerging multi-use market formats that function as social hubs and their management as privately managed public spaces. Using Āgenskalns Market, a revitalised multi-use market hall in Riga, as a case study, the authors apply an assessment framework based on Yuri Impens’ study on covered food halls, incorporating quality criteria from Vikas Mehta’s Public Space Index and the UN-Habitat’s Site-Specific assessment methodology. Leclercq et al.’s works on privatisation of public spaces are integrated in the analysis of “publicness”. This framework evaluates user and observer perceptions across four dimensions: environmental quality and comfort, accessibility and amenities, social experience, and market offer. Data comprised an online survey of 318 respondents and 21 structured observations conducted during summer in 2024 and 2025. The preliminary results suggest users perceive the market as a well-maintained, aesthetically pleasing, accessible space, while identifying room for improvement regarding restroom facilities, indoor thermal regulation, noise mitigation, outdoor weather protection and parking arrangements. As for meaningful use and promoting sociability, findings highlight that flexible seating areas that allow high degrees of temporary personalisation and appropriation, alongside tailored programming and diverse activities beyond retail and dining, play an important role in attracting and retaining diverse audiences. While pricing concerns were noted for specific product groups, exclusionary effects appear to be counterbalanced by openness and inclusivity of cultural programmes and free events. The findings contribute to broader urban scholarship discussions calling for new typologies that better capture the changing character of public space use. This research suggests that private-public partnerships involving multiple stakeholders can enhance “publicness” by promoting inclusivity and social life through accessible infrastructure, diverse activities and free events, as well as enabling opportunities for temporary appropriation by users. Full article

Asthma continues to affect millions of adults in the United States, with indoor environmental exposures playing a major role in symptom burden and control. Limited research has examined the combined influence of multiple household and environmental determinants on adult asthma morbidity, particularly in diverse states such as Texas. We analyzed pooled data from 1596 Texas adults with asthma who completed the Asthma Call-Back Survey between 2019 and 2022. Multivariable logistic regression models, adjusted for survey design and demographic covariates, were used to examine associations between household and environmental determinants and four morbidity outcomes: asthma attacks, recent symptoms, sleep difficulty, and limited activity due to asthma. Current smoking, lack of bathroom or kitchen ventilation, and absence of air purifier use were consistently associated with higher odds of morbidity. Protective associations were observed for homes without mold, rodents, or furry pets. Disparities were also evident, with older adults, women, and non-Hispanic Black respondents reporting greater morbidity. These findings highlight the importance of addressing modifiable exposures such as indoor smoking, ventilation, and allergen control within comprehensive asthma management strategies. Targeted interventions that combine environmental modifications with health education may help reduce asthma disparities and improve the quality of life for adults with asthma. Full article

The permeability coefficient of saturated clay plays a crucial role in practical engineering applications. In this paper, based on the fractal geometry theory and combined with the relationship between the flowing water volume and non-flowing water volume in saturated clay, the theoretical formulas for the effective pore specific surface area and the effective void ratio of saturated clay are established. Based on the capillary seepage channel model of saturated clay, combined with Poiseuille’s law and the concept of equivalent hydraulic radius, the theoretical formula for the permeability coefficient of saturated clay is established. Finally, the physical parameters of the remolded clay samples are measured and substituted into the modified Kozeny–Carman equation and the equivalent capillary seepage equation of saturated clay before and after the modification. Through the comparative analysis of the above theoretical values and the measured values of indoor seepage tests, it is found that the saturated clay seepage equation established in this paper is more suitable for dense saturated clay with relatively small pores. It has the characteristics of higher calculation accuracy and easier acquisition of basic parameters. The research results provide important references for practical engineering and the study of saturated clay seepage theory, and have broad prospects for practical engineering applications. Full article

Rising summer temperatures are increasing the demand for shading solutions and indoor cooling technologies. Given the substantial surface area of gable roofs, their effective shading plays a significant role in thermal management. While modern buildings often feature heat-insulated roofs equipped with photovoltaic panels or infrared-reflective coatings, such measures are frequently unsuitable for traditional, particularly heritage-protected structures. For this specific category of buildings, ventilated infrared (IR) shielding elements installed on the underside of rafters offer a promising approach to reduce surface temperatures and limit radiative heat transfer to attics or upper living spaces. This study evaluates performance-optimized IR shading systems for heritage roofs, focusing on material selection and emissivity effects. Results indicate that ventilated OSB panels with low-emissivity coatings achieve up to 53% thermal load reduction compared to unshielded conditions. Ventilation of the rafter fields emerges as the critical factor for the functional performance of such IR shading elements. Full article

With the widespread adoption of smartphones and wearable devices, localization systems have become increasingly important in modern society. While Global Positioning System (GPS) technology is widely accepted as a standard outdoors, accurately determining user location indoors remains a significant challenge despite extensive research efforts. Indoor positioning systems (IPSs) play a critical role in various sectors, including retail, tourism, transportation, healthcare, and emergency services. However, existing solutions require costly infrastructure deployments, complex area mapping, or offer suboptimal user experiences without achieving satisfactory accuracy. This paper introduces FloorTag, a scalable, low-cost, and minimally invasive hybrid IPS designed specifically for smartphone platforms. FloorTag leverages a combination of 2D visual markers placed on floor surfaces at key locations, and inertial sensor data from mobile devices. Each marker is associated with a unique identifier and precise spatial coordinates, enabling an immediate reset of accumulated localization errors upon detection. Between markers, a pedometer-based dead reckoning module maintains continuous location tracking. The localization process is designed to be seamless and unobtrusive to the user. When activated by the app during navigation, the phone’s rear camera, naturally angled toward the floor during walking, captures markers. This solution avoids explicit user scans while preserving the performance benefits of visual positioning. To model the indoor environment, FloorTag introduces the concept of Path-Points, which discretize the walkable space, and Informative Layers, which add semantic context to the navigation experience. This paper details the proposed methodology and the client–server system architecture and presents experimental results obtained from a prototype deployed in an academic building at the University of Catania, Italy. The findings demonstrate reliable localization at approximately 2 m spatial granularity and near-real-time performance across varying lighting conditions, confirming the feasibility of the approach and the effectiveness of the system. Full article

Indoor landmarks play a crucial role in the process of indoor positioning and route planning for pedestrians or unmanned devices. Indoor structural landmarks, a type of indoor landmarks, can provide rich steering and semantic descriptions for indoor navigation services. However, most traditional indoor landmark extraction methods rely on indoor points of interest and indoor vector map data. These methods face the problem of difficult acquisition of indoor data and overlook the exploration of indoor structural landmarks. Therefore, this paper innovatively proposes a method for extracting indoor structural landmarks based on the commonly available indoor fire protection plan images. First, the HSV model is employed to eliminate noise from the original image, and vector data of indoor components is obtained using the constructed Canny operator. Subsequently, the visibility is calculated based on the grids of indoor space segmentation. Finally, the identification and extraction of indoor structural landmarks are achieved through grid visibility classification, directional clustering analysis, and spatial proximity verification. This approach opens up new ideas for indoor landmark extraction methods. The experimental results show that the method proposed in this paper can effectively extract indoor structural landmarks, the extraction accuracy of indoor structural landmarks reaches over 90%, verifying the feasibility of using indoor fire protection plan data for landmark extraction and expanding the data sources for indoor landmark extraction. Full article

The radiant heating and cooling (RHC) system is one of the important air-conditioning methods that simultaneously achieves indoor thermal comfort and building energy efficiency. It is characterized by utilizing low-grade energy sources to provide low-temperature heating and high-temperature cooling, playing a significant role in promoting the development of green and low-carbon buildings. This study firstly introduces the typical heat transfer calculation methods of the RHC system and analyzes the surface heat transfer coefficients of radiant heating and cooling. Subsequently, the factors affecting the thermal performance of the RHC system are discussed from two aspects: relevant physical property parameters and flow channel structures. Finally, the control strategies of RHC systems are summarized to address issues such as condensation, overheating, and long response times. And several conclusive findings are presented that are worthy of further investigation in the future. Full article

Housing conditions are increasingly recognized as critical determinants of non-communicable diseases; however, their influence on hypertension (HTN) risk remains underexplored in low- and middle-income countries. In urban India, structural disparities in housing are especially pronounced between slum and non-slum areas, making comparative analysis crucial for understanding context-specific health risks. This study examines the relationship between multidimensional housing conditions and HTN risk among women aged 18–49, drawing on data from 68,422 respondents in the fourth National Family Health Survey. A composite housing index was developed to capture six dimensions: structural quality, housing services access, indoor air quality, crowding, tenure security, and asset ownership. Survey-weighted logistic regressions were used to assess associations between housing conditions and HTN, controlling for key socio-demographic and health-related factors. We found that overall HTN prevalence was lower in slum households (11.6%) than in non-slum households (16.0%). Unexpectedly, slum households reported better structural durability and indoor air quality than non-slum households, suggesting incremental improvements in notified or tenure-secure slums. Better tenure security and asset ownership were found to be protective factors for HTN risk, while better structural quality was associated with higher HTN odds in non-slum areas. Crowding showed contrasting effects: in slums, higher crowding increased HTN risk, whereas in non-slums, lower crowding was associated with higher HTN. These findings highlight the context-dependent nature of housing-health links. Targeted interventions that address both physical infrastructure and broader living conditions can play a vital role in reducing urban hypertension disparities among women in India. Full article

This review systematically examines research on indoor thermal comfort for older adults conducted in China since 2010. It highlights several existing research gaps, including the lack of a systematic understanding of environmental and individual influences, limitations of thermal comfort models, challenges in their optimization, and inadequate integration of intelligent technologies. Results indicate that environmental factors usually exert a greater impact on the elderly’s neutral temperature than individual factors. Thermal comfort models differ in predictive accuracy, data requirements, and applicability. The adaptive predicted mean vote (aPMV) model is better suited for group-level assessments. Machine learning (ML) models, featuring high flexibility and accuracy, are more appropriate for personalized predictions. In addition, physiological parameters could play a critical role in thermal assessments. When integrated with ML models, physiological parameters could further improve predictive accuracy. When integrated into artificial intelligence (AI) and Internet of Things (IoT) systems, forehead and back skin temperatures could act as early-warning indicators during heat exposure, while lower-limb temperatures are more indicative of thermal discomfort during cold exposure. Overall, this review summarizes current progress and limitations, offering a reference for the development of user-friendly modeling and intelligent temperature-control systems. Full article

State estimation plays a vital role in UAV navigation and control. With the continuous decrease in sensor cost and size, UAVs equipped with multiple LiDARs, Inertial Measurement Units (IMUs), and cameras have attracted increasing attention. Such systems can acquire rich environmental and motion information from multiple perspectives, thereby enabling more precise navigation and mapping in complex environments. However, efficiently utilizing multi-sensor data for state estimation remains challenging. There is a complex coupling relationship between IMUs’ bias and UAV state. To address these challenges, this paper proposes an efficient and accurate UAV state estimation method tailored for multi-LiDAR–IMU–camera systems. Specifically, we first construct an efficient distributed state estimation model. It decomposes the multi-LiDAR–IMU–camera system into a series of single LiDAR–IMU–camera subsystems, reformulating the complex coupling problem as an efficient distributed state estimation problem. Then, we derive an accurate feedback function to constrain and optimize the UAV state using estimated subsystem states, thus enhancing overall estimation accuracy. Based on this model, we design an efficient distributed state estimation algorithm with multi-LiDAR-IMU-Camerafusion, termed DLIC. DLIC achieves robust multi-sensor data fusion via shared feature maps, effectively improving both estimation robustness and accuracy. In addition, we design an accelerated image-to-point cloud registration module (A-I2P) to provide reliable visual measurements, further boosting state estimation efficiency. Extensive experiments are conducted on 18 real-world indoor and outdoor scenarios from the public NTU VIRAL dataset. The results demonstrate that DLIC consistently outperforms existing multi-sensor methods across key evaluation metrics, including RMSE, MAE, SD, and SSE. More importantly, our method runs in real time on a resource-constrained embedded device equipped with only an 8-core CPU, while maintaining low memory consumption. Full article

Cultural tourism has become an increasingly significant phenomenon in urban areas, especially in cities rich in heritage sites. However, when the number of visitors exceeds sustainable capacity thresholds, both the physical and psychological comfort and safety of individuals may be compromised. A higher number of visitors inside historic buildings leads to elevated concentrations of carbon dioxide (CO₂), particularly in poorly ventilated enclosed or confined spaces, primarily as a result of human respiration. Such conditions not only accelerate the deterioration processes affecting heritage materials but also introduce potential health risks for visitors. Parameters such as CO₂ concentration, indoor air temperature, and relative humidity represent key measurable parameters for assessing environmental Indoor Air Quality (IAQ) within heritage buildings. Digital real-time monitoring of these parameters plays a crucial role in preventive heritage conservation, sustainable site management, and in ensuring visitors’ comfort and well-being. This paper presents a procedure and methodology that use digital technological tools to efficiently estimate and monitor the Visitor Carrying Capacity (VCC) of enclosed/confined heritage spaces, especially Heritage Building Information Modelling (HBIM) and Sensor Technology. These kinds of spaces require particular attention due to their spatial characteristics. In order to do so, it is necessary to know the geometry of the site, and to consider IAQ conditions. This study also considers the number of People at One Time (PAOT) and Visitor Occupancy (VO). The results focus on the procedural development of the analysis and emphasise the role of digital tools not only due to their efficiency and accuracy in spatial analysis for estimating VCC, but especially for the real-time monitoring of visitors and surveying specific environmental parameters. The experimental phase of this study uses the Chapel of the Holy Chalice of the Valencia Cathedral (Spain) as a pilot case. Monitoring this space reveals how quickly high CO₂ levels are reached with continuous visitor presence, and how long it takes for them to decay in absence of people and under passive ventilation conditions. The outcome of this research is a detailed methodological framework designed to assess and monitor Visitor Carrying Capacity (VCC) in enclosed/confined heritage sites by integrating digital technologies, thereby enhancing sustainable management, planning and decision-making processes. Full article

The concept of green building has become important, as sustainability issues have been acknowledged in the construction industry. Green building certification systems have emerged to measure the sustainability of buildings. While there are numerous studies on green building certification systems, studies evaluating green schools are quite limited, even though green schools not only ensure the health and comfort of students and teachers but also play a role in raising sustainability awareness, especially among growing children. First, a detailed literature review was conducted in this study that identified eight common issues, namely “project management processes”, “land selection and transportation/location”, “energy”, “indoor environmental quality”, “water”, “waste”, “materials” and “innovation”, which were extensively used to evaluate green schools. Four green building certification systems that emerged in developing countries and four systems that existed in advanced countries were compared relative to these eight issues. The weaknesses of the eight certification systems and the fundamental differences between advanced and developing countries were identified, and suggestions for improvements were presented. It was concluded that it is not enough to consider green schools only as buildings that rely on sustainable design and construction but also as important institutions that contribute to the adoption of the concept of sustainability. Consequently, it was found that it is important to create special green certification systems for schools. Full article