Three-dimensional reconstruction of indoor whole elements based on mobile LiDAR point cloud data
NASA Astrophysics Data System (ADS)
Gong, Yuejian; Mao, Wenbo; Bi, Jiantao; Ji, Wei; He, Zhanjun
2014-11-01
Ground-based LiDAR is one of the most effective city modeling tools at present, which has been widely used for three-dimensional reconstruction of outdoor objects. However, as for indoor objects, there are some technical bottlenecks due to lack of GPS signal. In this paper, based on the high-precision indoor point cloud data which was obtained by LiDAR, an international advanced indoor mobile measuring equipment, high -precision model was fulfilled for all indoor ancillary facilities. The point cloud data we employed also contain color feature, which is extracted by fusion with CCD images. Thus, it has both space geometric feature and spectral information which can be used for constructing objects' surface and restoring color and texture of the geometric model. Based on Autodesk CAD platform and with help of PointSence plug, three-dimensional reconstruction of indoor whole elements was realized. Specifically, Pointools Edit Pro was adopted to edit the point cloud, then different types of indoor point cloud data was processed, including data format conversion, outline extracting and texture mapping of the point cloud model. Finally, three-dimensional visualization of the real-world indoor was completed. Experiment results showed that high-precision 3D point cloud data obtained by indoor mobile measuring equipment can be used for indoor whole elements' 3-d reconstruction and that methods proposed in this paper can efficiently realize the 3 -d construction of indoor whole elements. Moreover, the modeling precision could be controlled within 5 cm, which was proved to be a satisfactory result.
Modeling Human Exposure to Indoor Contaminants: External Source to Body Tissues.
Webster, Eva M; Qian, Hua; Mackay, Donald; Christensen, Rebecca D; Tietjen, Britta; Zaleski, Rosemary
2016-08-16
Information on human indoor exposure is necessary to assess the potential risk to individuals from many chemicals of interest. Dynamic indoor and human physicologically based pharmacokinetic (PBPK) models of the distribution of nonionizing, organic chemical concentrations in indoor environments resulting in delivered tissue doses are developed, described and tested. The Indoor model successfully reproduced independently measured, reported time-dependent air concentrations of chloroform released during showering and of 2-butyoxyethanol following use of a volatile surface cleaner. The Indoor model predictions were also comparable to those from a higher tier consumer model (ConsExpo 4.1) for the surface cleaner scenario. The PBPK model successful reproduced observed chloroform exhaled air concentrations resulting from an inhalation exposure. Fugacity based modeling provided a seamless description of the partitioning, fluxes, accumulation and release of the chemical in indoor media and tissues of the exposed subject. This has the potential to assist in health risk assessments, provided that appropriate physical/chemical property, usage characteristics, and toxicological information are available.
Jiao, Jichao; Li, Fei; Deng, Zhongliang; Ma, Wenjing
2017-03-28
Considering the installation cost and coverage, the received signal strength indicator (RSSI)-based indoor positioning system is widely used across the world. However, the indoor positioning performance, due to the interference of wireless signals that are caused by the complex indoor environment that includes a crowded population, cannot achieve the demands of indoor location-based services. In this paper, we focus on increasing the signal strength estimation accuracy considering the population density, which is different to the other RSSI-based indoor positioning methods. Therefore, we propose a new wireless signal compensation model considering the population density, distance, and frequency. First of all, the number of individuals in an indoor crowded scenario can be calculated by our convolutional neural network (CNN)-based human detection approach. Then, the relationship between the population density and the signal attenuation is described in our model. Finally, we use the trilateral positioning principle to realize the pedestrian location. According to the simulation and tests in the crowded scenarios, the proposed model increases the accuracy of the signal strength estimation by 1.53 times compared to that without considering the human body. Therefore, the localization accuracy is less than 1.37 m, which indicates that our algorithm can improve the indoor positioning performance and is superior to other RSSI models.
Indoorgml - a Standard for Indoor Spatial Modeling
NASA Astrophysics Data System (ADS)
Li, Ki-Joune
2016-06-01
With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.
A Hybrid 3D Indoor Space Model
NASA Astrophysics Data System (ADS)
Jamali, Ali; Rahman, Alias Abdul; Boguslawski, Pawel
2016-10-01
GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.
D Modelling of AN Indoor Space Using a Rotating Stereo Frame Camera System
NASA Astrophysics Data System (ADS)
Kang, J.; Lee, I.
2016-06-01
Sophisticated indoor design and growing development in urban architecture make indoor spaces more complex. And the indoor spaces are easily connected to public transportations such as subway and train stations. These phenomena allow to transfer outdoor activities to the indoor spaces. Constant development of technology has a significant impact on people knowledge about services such as location awareness services in the indoor spaces. Thus, it is required to develop the low-cost system to create the 3D model of the indoor spaces for services based on the indoor models. In this paper, we thus introduce the rotating stereo frame camera system that has two cameras and generate the indoor 3D model using the system. First, select a test site and acquired images eight times during one day with different positions and heights of the system. Measurements were complemented by object control points obtained from a total station. As the data were obtained from the different positions and heights of the system, it was possible to make various combinations of data and choose several suitable combinations for input data. Next, we generated the 3D model of the test site using commercial software with previously chosen input data. The last part of the processes will be to evaluate the accuracy of the generated indoor model from selected input data. In summary, this paper introduces the low-cost system to acquire indoor spatial data and generate the 3D model using images acquired by the system. Through this experiments, we ensure that the introduced system is suitable for generating indoor spatial information. The proposed low-cost system will be applied to indoor services based on the indoor spatial information.
Study of indoor radon distribution using measurements and CFD modeling.
Chauhan, Neetika; Chauhan, R P; Joshi, M; Agarwal, T K; Aggarwal, Praveen; Sahoo, B K
2014-10-01
Measurement and/or prediction of indoor radon ((222)Rn) concentration are important due to the impact of radon on indoor air quality and consequent inhalation hazard. In recent times, computational fluid dynamics (CFD) based modeling has become the cost effective replacement of experimental methods for the prediction and visualization of indoor pollutant distribution. The aim of this study is to implement CFD based modeling for studying indoor radon gas distribution. This study focuses on comparison of experimentally measured and CFD modeling predicted spatial distribution of radon concentration for a model test room. The key inputs for simulation viz. radon exhalation rate and ventilation rate were measured as a part of this study. Validation experiments were performed by measuring radon concentration at different locations of test room using active (continuous radon monitor) and passive (pin-hole dosimeters) techniques. Modeling predictions have been found to be reasonably matching with the measurement results. The validated model can be used to understand and study factors affecting indoor radon distribution for more realistic indoor environment. Copyright © 2014 Elsevier Ltd. All rights reserved.
Liu, Zhijian; Li, Hao; Cao, Guoqing
2017-07-30
Indoor airborne culturable bacteria are sometimes harmful to human health. Therefore, a quick estimation of their concentration is particularly necessary. However, measuring the indoor microorganism concentration (e.g., bacteria) usually requires a large amount of time, economic cost, and manpower. In this paper, we aim to provide a quick solution: using knowledge-based machine learning to provide quick estimation of the concentration of indoor airborne culturable bacteria only with the inputs of several measurable indoor environmental indicators, including: indoor particulate matter (PM 2.5 and PM 10 ), temperature, relative humidity, and CO₂ concentration. Our results show that a general regression neural network (GRNN) model can sufficiently provide a quick and decent estimation based on the model training and testing using an experimental database with 249 data groups.
The Isprs Benchmark on Indoor Modelling
NASA Astrophysics Data System (ADS)
Khoshelham, K.; Díaz Vilariño, L.; Peter, M.; Kang, Z.; Acharya, D.
2017-09-01
Automated generation of 3D indoor models from point cloud data has been a topic of intensive research in recent years. While results on various datasets have been reported in literature, a comparison of the performance of different methods has not been possible due to the lack of benchmark datasets and a common evaluation framework. The ISPRS benchmark on indoor modelling aims to address this issue by providing a public benchmark dataset and an evaluation framework for performance comparison of indoor modelling methods. In this paper, we present the benchmark dataset comprising several point clouds of indoor environments captured by different sensors. We also discuss the evaluation and comparison of indoor modelling methods based on manually created reference models and appropriate quality evaluation criteria. The benchmark dataset is available for download at: http://www2.isprs.org/commissions/comm4/wg5/benchmark-on-indoor-modelling.html.
Noar, Seth M; Myrick, Jessica Gall; Zeitany, Alexandra; Kelley, Dannielle; Morales-Pico, Brenda; Thomas, Nancy E
2015-01-01
The lack of a theory-based understanding of indoor tanning is a major impediment to the development of effective messages to prevent or reduce this behavior. This study applied the Comprehensive Indoor Tanning Expectations (CITE) scale in an analysis of indoor tanning behavior among sorority women (total N = 775). Confirmatory factor analyses indicated that CITE positive and negative expectations were robust, multidimensional factors and that a hierarchical structure fit the data well. Social cognitive theory-based structural equation models demonstrated that appearance-oriented variables were significantly associated with outcome expectations. Outcome expectations were, in turn, significantly associated with temptations to tan, intention to tan indoors, and indoor tanning behavior. The implications of these findings for the development of messages to prevent and reduce indoor tanning behavior are discussed in two domains: (a) messages that attempt to change broader societal perceptions about tan skin, and (b) messages that focus more narrowly on indoor tanning-challenging positive expectations, enhancing negative expectations, and encouraging substitution of sunless tanning products.
Liu, Zhijian; Li, Hao; Cao, Guoqing
2017-01-01
Indoor airborne culturable bacteria are sometimes harmful to human health. Therefore, a quick estimation of their concentration is particularly necessary. However, measuring the indoor microorganism concentration (e.g., bacteria) usually requires a large amount of time, economic cost, and manpower. In this paper, we aim to provide a quick solution: using knowledge-based machine learning to provide quick estimation of the concentration of indoor airborne culturable bacteria only with the inputs of several measurable indoor environmental indicators, including: indoor particulate matter (PM2.5 and PM10), temperature, relative humidity, and CO2 concentration. Our results show that a general regression neural network (GRNN) model can sufficiently provide a quick and decent estimation based on the model training and testing using an experimental database with 249 data groups. PMID:28758941
NASA Astrophysics Data System (ADS)
Markov, Detelin
2012-11-01
This paper presents an easy-to-understand procedure for prediction of indoor air composition time variation in air-tight occupied spaces during the night periods. The mathematical model is based on the assumptions for homogeneity and perfect mixing of the indoor air, the ideal gas model for non-reacting gas mixtures, mass conservation equations for the entire system and for each species, a model for prediction of basal metabolic rate of humans as well as a model for prediction of O2 consumption rate and both CO2 and H2O generation rates by breathing. Time variation of indoor air composition is predicted at constant indoor air temperature for three scenarios based on the analytical solution of the mathematical model. The results achieved reveal both the most probable scenario for indoor air time variation in air-tight occupied spaces as well as the cause for morning tiredness after having a sleep in a modern energy efficient space.
Piao, Xinglin; Zhang, Yong; Li, Tingshu; Hu, Yongli; Liu, Hao; Zhang, Ke; Ge, Yun
2016-01-01
The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods. PMID:27827882
Improved spring model-based collaborative indoor visible light positioning
NASA Astrophysics Data System (ADS)
Luo, Zhijie; Zhang, WeiNan; Zhou, GuoFu
2016-06-01
Gaining accuracy with indoor positioning of individuals is important as many location-based services rely on the user's current position to provide them with useful services. Many researchers have studied indoor positioning techniques based on WiFi and Bluetooth. However, they have disadvantages such as low accuracy or high cost. In this paper, we propose an indoor positioning system in which visible light radiated from light-emitting diodes is used to locate the position of receivers. Compared with existing methods using light-emitting diode light, we present a high-precision and simple implementation collaborative indoor visible light positioning system based on an improved spring model. We first estimate coordinate position information using the visible light positioning system, and then use the spring model to correct positioning errors. The system can be employed easily because it does not require additional sensors and the occlusion problem of visible light would be alleviated. We also describe simulation experiments, which confirm the feasibility of our proposed method.
Tang, Chia Hsi; Garshick, Eric; Grady, Stephanie; Coull, Brent; Schwartz, Joel; Koutrakis, Petros
2018-01-01
The effects of indoor air pollution on human health have drawn increasing attention among the scientific community as individuals spend most of their time indoors. However, indoor air sampling is labor-intensive and costly, which limits the ability to study the adverse health effects related to indoor air pollutants. To overcome this challenge, many researchers have attempted to predict indoor exposures based on outdoor pollutant concentrations, home characteristics, and weather parameters. Typically, these models require knowledge of the infiltration factor, which indicates the fraction of ambient particles that penetrates indoors. For estimating indoor fine particulate matter (PM2.5) exposure, a common approach is to use the indoor-to-outdoor sulfur ratio (Sindoor/Soutdoor) as a proxy of the infiltration factor. The objective of this study was to develop a robust model that estimates Sindoor/Soutdoor for individual households that can be incorporated into models to predict indoor PM2.5 and black carbon (BC) concentrations. Overall, our model adequately estimated Sindoor/Soutdoor with an out-of-sample by home-season R2 of 0.89. Estimated Sindoor/Soutdoor reflected behaviors that influence particle infiltration, including window opening, use of forced air heating, and air purifier. Sulfur ratio-adjusted models predicted indoor PM2.5 and BC with high precision, with out-of-sample R2 values of 0.79 and 0.76, respectively. PMID:29064481
Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations
NASA Astrophysics Data System (ADS)
Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.
2017-09-01
This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
Comparison of Highly Resolved Model-Based Exposure ...
Human exposure to air pollution in many studies is represented by ambient concentrations from space-time kriging of observed values. Space-time kriging techniques based on a limited number of ambient monitors may fail to capture the concentration from local sources. Further, because people spend more time indoors, using ambient concentration to represent exposure may cause error. To quantify the associated exposure error, we computed a series of six different hourly-based exposure metrics at 16,095 Census blocks of three Counties in North Carolina for CO, NOx, PM2.5, and elemental carbon (EC) during 2012. These metrics include ambient background concentration from space-time ordinary kriging (STOK), ambient on-road concentration from the Research LINE source dispersion model (R-LINE), a hybrid concentration combining STOK and R-LINE, and their associated indoor concentrations from an indoor infiltration mass balance model. Using a hybrid-based indoor concentration as the standard, the comparison showed that outdoor STOK metrics yielded large error at both population (67% to 93%) and individual level (average bias between −10% to 95%). For pollutants with significant contribution from on-road emission (EC and NOx), the on-road based indoor metric performs the best at the population level (error less than 52%). At the individual level, however, the STOK-based indoor concentration performs the best (average bias below 30%). For PM2.5, due to the relatively low co
Liu, Zhijian; Cheng, Kewei; Li, Hao; Cao, Guoqing; Wu, Di; Shi, Yunjie
2018-02-01
Indoor airborne culturable fungi exposure has been closely linked to occupants' health. However, conventional measurement of indoor airborne fungal concentration is complicated and usually requires around one week for fungi incubation in laboratory. To provide an ultra-fast solution, here, for the first time, a knowledge-based machine learning model is developed with the inputs of indoor air quality data for estimating the concentration of indoor airborne culturable fungi. To construct a database for statistical analysis and model training, 249 data groups of air quality indicators (concentration of indoor airborne culturable fungi, indoor/outdoor PM 2.5 and PM 10 concentrations, indoor temperature, indoor relative humidity, and indoor CO 2 concentration) were measured from 85 residential buildings of Baoding (China) during the period of 2016.11.15-2017.03.15. Our results show that artificial neural network (ANN) with one hidden layer has good prediction performances, compared to a support vector machine (SVM). With the tolerance of ± 30%, the prediction accuracy of the ANN model with ten hidden nodes can at highest reach 83.33% in the testing set. Most importantly, we here provide a quick method for estimating the concentration of indoor airborne fungi that can be applied to real-time evaluation.
Liu, X; Zhai, Z
2008-02-01
Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in finding indoor pollutant sources. The research lays a solid ground for further study of the method for more complicated indoor contamination problems. The method developed can help track indoor contaminant source location with limited sensor outputs. This will ensure an effective and prompt execution of building control strategies and thus achieve a healthy and safe indoor environment. The method can also assist the design of optimal sensor networks.
NASA Astrophysics Data System (ADS)
Dehbi, Y.; Haunert, J.-H.; Plümer, L.
2017-10-01
3D city and building models according to CityGML encode the geometry, represent the structure and model semantically relevant building parts such as doors, windows and balconies. Building information models support the building design, construction and the facility management. In contrast to CityGML, they include also objects which cannot be observed from the outside. The three dimensional indoor models characterize a missing link between both worlds. Their derivation, however, is expensive. The semantic automatic interpretation of 3D point clouds of indoor environments is a methodically demanding task. The data acquisition is costly and difficult. The laser scanners and image-based methods require the access to every room. Based on an approach which does not require an additional geometry acquisition of building indoors, we propose an attempt for filling the gaps between 3D building models and building information models. Based on sparse observations such as the building footprint and room areas, 3D indoor models are generated using combinatorial and stochastic reasoning. The derived models are expanded by a-priori not observable structures such as electric installation. Gaussian mixtures, linear and bi-linear constraints are used to represent the background knowledge and structural regularities. The derivation of hypothesised models is performed by stochastic reasoning using graphical models, Gauss-Markov models and MAP-estimators.
Zota, Ami R.; Fabian, M. Patricia; Chahine, Teresa; Julien, Rhona; Spengler, John D.; Levy, Jonathan I.
2011-01-01
Objectives. The indoor environment has not been fully incorporated into the environmental justice dialogue. To inform strategies to reduce disparities, we developed a framework to identify the individual and place-based drivers of indoor environment quality. Methods. We reviewed empirical evidence of socioeconomic disparities in indoor exposures and key determinants of these exposures for air pollutants, lead, allergens, and semivolatile organic compounds. We also used an indoor air quality model applied to multifamily housing to illustrate how nitrogen dioxide (NO2) and fine particulate matter (PM2.5) vary as a function of factors known to be influenced by socioeconomic status. Results. Indoor concentrations of multiple pollutants are elevated in low-socioeconomic status households. Differences in these exposures are driven by the combined influences of indoor sources, outdoor sources, physical structures, and residential activity patterns. Simulation models confirmed indoor sources’ importance in determining indoor NO2 and PM2.5 exposures and showed the influence of household-specific determinants. Conclusions. Both theoretical models and empirical evidence emphasized that disparities in indoor environmental exposure can be significant. Understanding key determinants of multiple indoor exposures can aid in developing policies to reduce these disparities. PMID:21836112
Indoor Navigation from Point Clouds: 3d Modelling and Obstacle Detection
NASA Astrophysics Data System (ADS)
Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H.; Mahdjoubi, L.
2016-06-01
In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.
Constructing an Indoor Floor Plan Using Crowdsourcing Based on Magnetic Fingerprinting
Zhao, Fang; Jiang, Mengling; Ma, Hao; Zhang, Yuexia
2017-01-01
A large number of indoor positioning systems have recently been developed to cater for various location-based services. Indoor maps are a prerequisite of such indoor positioning systems; however, indoor maps are currently non-existent for most indoor environments. Construction of an indoor map by external experts excludes quick deployment and prevents widespread utilization of indoor localization systems. Here, we propose an algorithm for the automatic construction of an indoor floor plan, together with a magnetic fingerprint map of unmapped buildings using crowdsourced smartphone data. For floor plan construction, our system combines the use of dead reckoning technology, an observation model with geomagnetic signals, and trajectory fusion based on an affinity propagation algorithm. To obtain the indoor paths, the magnetic trajectory data obtained through crowdsourcing were first clustered using dynamic time warping similarity criteria. The trajectories were inferred from odometry tracing, and those belonging to the same cluster in the magnetic trajectory domain were then fused. Fusing these data effectively eliminates the inherent tracking errors originating from noisy sensors; as a result, we obtained highly accurate indoor paths. One advantage of our system is that no additional hardware such as a laser rangefinder or wheel encoder is required. Experimental results demonstrate that our proposed algorithm successfully constructs indoor floor plans with 0.48 m accuracy, which could benefit location-based services which lack indoor maps. PMID:29156639
Sociocultural experiences, body image, and indoor tanning among young adult women.
Stapleton, Jerod L; Manne, Sharon L; Greene, Kathryn; Darabos, Katie; Carpenter, Amanda; Hudson, Shawna V; Coups, Elliot J
2017-10-01
The purpose of this survey study was to evaluate a model of body image influences on indoor tanning behavior. Participants were 823 young adult women recruited from a probability-based web panel in the United States. Consistent with our hypothesized model, tanning-related sociocultural experiences were indirectly associated with lifetime indoor tanning use and intentions to tan as mediated through tan surveillance and tan dissatisfaction. Findings suggest the need for targeting body image constructs as mechanisms of behavior change in indoor tanning behavioral interventions.
Aspect Ratio of Receiver Node Geometry based Indoor WLAN Propagation Model
NASA Astrophysics Data System (ADS)
Naik, Udaykumar; Bapat, Vishram N.
2017-08-01
This paper presents validation of indoor wireless local area network (WLAN) propagation model for varying rectangular receiver node geometry. The rectangular client node configuration is a standard node arrangement in computer laboratories of academic institutes and research organizations. The model assists to install network nodes for the better signal coverage. The proposed model is backed by wide ranging real time received signal strength measurements at 2.4 GHz. The shadow fading component of signal propagation under realistic indoor environment is modelled with the dependency on varying aspect ratio of the client node geometry. The developed new model is useful in predicting indoor path loss for IEEE 802.11b/g WLAN. The new model provides better performance in comparison to well known International Telecommunication Union and free space propagation models. It is shown that the proposed model is simple and can be a useful tool for indoor WLAN node deployment planning and quick method for the best utilisation of the office space.
PARAMS is a Windows-based computer program that implements 30 methods for estimating the parameters in indoor emissions source models, which are an essential component of indoor air quality (IAQ) and exposure models. These methods fall into eight categories: (1) the properties o...
Health behaviours associated with indoor tanning based on the 2012/13 Manitoba Youth Health Survey
Harland, E.; Griffith, J.; Lu, H.; Erickson, T.; Magsino, K.
2016-01-01
Abstract Introduction: Although indoor tanning causes cancer, it remains relatively common among adolescents. Little is known about indoor tanning prevalence and habits in Canada, and even less about associated behaviours. This study explores the prevalence of adolescent indoor tanning in Manitoba and its association with other demographic characteristics and health behaviours. Methods: We conducted secondary analyses of the 2012/13 Manitoba Youth Health Survey data collected from Grade 7 to 12 students (n = 64 174) and examined associations between indoor tanning (whether participants had ever used artificial tanning equipment) and 25 variables. Variables with statistically significant associations to indoor tanning were tested for collinearity and grouped based on strong associations. For each group of highly associated variables, the variable with the greatest effect upon indoor tanning was placed into the final logistic regression model. Separate analyses were conducted for males and females to better understand sex-based differences, and analyses were adjusted for age. Results: Overall, 4% of male and 9% of female students reported indoor tanning, and prevalence increased with age. Relationships between indoor tanning and other variables were similar for male and female students. Binary logistic regression models indicated that several variables significantly predicted indoor tanning, including having part-time work, being physically active, engaging in various risk behaviours such as driving after drinking for males and unplanned sex after alcohol/drugs for females, experiencing someone say something bad about one’s body shape/size/appearance, identifying as trans or with another gender, consuming creatine/other supplements and, for females only, never/rarely using sun protection. Conclusion: Indoor tanning among adolescents was associated with age, part-time work, physical activity and many consumption behaviours and lifestyle risk factors. Though legislation prohibiting adolescent indoor tanning is critical, health promotion to discourage indoor tanning may be most beneficial if it also addresses these associated factors. PMID:27556919
Health behaviours associated with indoor tanning based on the 2012/13 Manitoba Youth Health Survey.
Harland, E; Griffith, J; Lu, H; Erickson, T; Magsino, K
2016-08-01
Although indoor tanning causes cancer, it remains relatively common among adolescents. Little is known about indoor tanning prevalence and habits in Canada, and even less about associated behaviours. This study explores the prevalence of adolescent indoor tanning in Manitoba and its association with other demographic characteristics and health behaviours. We conducted secondary analyses of the 2012/13 Manitoba Youth Health Survey data collected from Grade 7 to 12 students (n = 64 174) and examined associations between indoor tanning (whether participants had ever used artificial tanning equipment) and 25 variables. Variables with statistically significant associations to indoor tanning were tested for collinearity and grouped based on strong associations. For each group of highly associated variables, the variable with the greatest effect upon indoor tanning was placed into the final logistic regression model. Separate analyses were conducted for males and females to better understand sex-based differences, and analyses were adjusted for age. Overall, 4% of male and 9% of female students reported indoor tanning, and prevalence increased with age. Relationships between indoor tanning and other variables were similar for male and female students. Binary logistic regression models indicated that several variables significantly predicted indoor tanning, including having part-time work, being physically active, engaging in various risk behaviours such as driving after drinking for males and unplanned sex after alcohol/drugs for females, experiencing someone say something bad about one's body shape/size/appearance, identifying as trans or with another gender, consuming creatine/other supplements and, for females only, never/rarely using sun protection. Indoor tanning among adolescents was associated with age, part-time work, physical activity and many consumption behaviours and lifestyle risk factors. Though legislation prohibiting adolescent indoor tanning is critical, health promotion to discourage indoor tanning may be most beneficial if it also addresses these associated factors.
Timkova, Jana; Fojtikova, Ivana; Pacherova, Petra
2017-01-01
The purpose of the study is to determine radon-prone areas in the Czech Republic based on the measurements of indoor radon concentration and independent predictors (rock type and permeability of the bedrock, gamma dose rate, GPS coordinates and the average age of family houses). The relationship between the mean observed indoor radon concentrations in monitored areas (∼22% municipalities) and the independent predictors was modelled using a bagged neural network. Levels of mean indoor radon concentration in the unmonitored areas were predicted using the bagged neural network model fitted for the monitored areas. The propensity to increased indoor radon was determined by estimated probability of exceeding the action level of 300Bq/m 3 . Copyright © 2016 Elsevier Ltd. All rights reserved.
Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device
He, Xiang; Aloi, Daniel N.; Li, Jia
2015-01-01
Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387
Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.
He, Xiang; Aloi, Daniel N; Li, Jia
2015-12-14
Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.
Two computational methods are proposed for estimation of the emission rate of volatile organic compounds (VOCs) from solvent-based indoor coating materials based on the knowledge of product formulation. The first method utilizes two previously developed mass transfer models with ...
Integration of GIS and Bim for Indoor Geovisual Analytics
NASA Astrophysics Data System (ADS)
Wu, B.; Zhang, S.
2016-06-01
This paper presents an endeavour of integration of GIS (Geographical Information System) and BIM (Building Information Modelling) for indoor geovisual analytics. The merits of two types of technologies, GIS and BIM are firstly analysed in the context of indoor environment. GIS has well-developed capabilities of spatial analysis such as network analysis, while BIM has the advantages for indoor 3D modelling and dynamic simulation. This paper firstly investigates the important aspects for integrating GIS and BIM. Different data standards and formats such as the IFC (Industry Foundation Classes) and GML (Geography Markup Language) are discussed. Their merits and limitations in data transformation between GIS and BIM are analysed in terms of semantic and geometric information. An optimized approach for data exchange between GIS and BIM datasets is then proposed. After that, a strategy of using BIM for 3D indoor modelling, GIS for spatial analysis, and BIM again for visualization and dynamic simulation of the analysis results is presented. Based on the developments, this paper selects a typical problem, optimized indoor emergency evacuation, to demonstrate the integration of GIS and BIM for indoor geovisual analytics. The block Z of the Hong Kong Polytechnic University is selected as a test site. Detailed indoor and outdoor 3D models of the block Z are created using a BIM software Revit. The 3D models are transferred to a GIS software ArcGIS to carry out spatial analysis. Optimized evacuation plans considering dynamic constraints are generated based on network analysis in ArcGIS assuming there is a fire accident inside the building. The analysis results are then transferred back to BIM software for visualization and dynamic simulation. The developed methods and results are of significance to facilitate future development of GIS and BIM integrated solutions in various applications.
MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.
Tuta, Jure; Juric, Matjaz B
2018-03-24
This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.
MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method
Juric, Matjaz B.
2018-01-01
This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage. PMID:29587352
Indoor Radon Concentration Related to Different Radon Areas and Indoor Radon Prediction
NASA Astrophysics Data System (ADS)
Juhásová Šenitková, Ingrid; Šál, Jiří
2017-12-01
Indoor radon has been observed in the buildings at areas with different radon risk potential. Preventive measures are based on control of main potential radon sources (soil gas, building material and supplied water) to avoid building of new houses above recommended indoor radon level 200 Bq/m3. Radon risk (index) estimation of individual building site bedrock in case of new house siting and building protection according technical building code are obligatory. Remedial actions in buildings built at high radon risk areas were carried out principally by unforced ventilation and anti-radon insulation. Significant differences were found in the level of radon concentration between rooms where radon reduction techniques were designed and those where it was not designed. The mathematical model based on radon exhalation from soil has been developed to describe the physical processes determining indoor radon concentration. The model is focused on combined radon diffusion through the slab and advection through the gap from sub-slab soil. In this model, radon emanated from building materials is considered not having a significant contribution to indoor radon concentration. Dimensional analysis and Gauss-Newton nonlinear least squares parametric regression were used to simplify the problem, identify essential input variables and find parameter values. The presented verification case study is introduced for real buildings with respect to various underground construction types. Presented paper gives picture of possible mathematical approach to indoor radon concentration prediction.
Qi, Meng; Zhu, Xi; Du, Wei; Chen, Yilin; Chen, Yuanchen; Huang, Tianbo; Pan, Xuelian; Zhong, Qirui; Sun, Xu; Zeng, Eddy Y; Xing, Baoshan; Tao, Shu
2017-01-01
Because people spend most of their time indoors, the characterization of indoor air quality is important for exposure assessment. Unfortunately, indoor air data are scarce, leading to a major data gap in risk assessment. In this study, PM 2.5 concentrations in both indoor and outdoor air were simultaneously measured using on-line particulate counters in 13 households in Haidian, Beijing for both heating and non-heating seasons. A bimodal distribution of PM 2.5 concentrations suggests rapid transitions between polluted and non-polluted situations. The PM 2.5 concentrations in indoor and outdoor air varied synchronously, with the indoor variation lagging. The lag time in the heating season was longer than that in the non-heating season. The particle sizes in indoor air were smaller than those in ambient air in the heating season and vice versa in the non-heating season. PM 2.5 concentrations in indoor air were generally lower than those in ambient air except when ambient concentrations dropped sharply to very low levels or there were internal emissions from cooking or other activities. The effectiveness of an air cleaner to reduce indoor PM 2.5 concentrations was demonstrated. Non-linear regression models were developed to predict indoor air PM 2.5 concentrations based on ambient data with lag time incorporated. The models were applied to estimate the overall population exposure to PM 2.5 and the health consequences in Haidian. The health impacts would be significantly overestimated without the indoor exposure being taken into consideration, and this bias would increase as the ambient air quality improved in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.
Zhang, Shengzhi; Yu, Shuai; Liu, Chaojun; Liu, Sheng
2016-06-01
Tracking the position of pedestrian is urgently demanded when the most commonly used GPS (Global Position System) is unavailable. Benefited from the small size, low-power consumption, and relatively high reliability, micro-electro-mechanical system sensors are well suited for GPS-denied indoor pedestrian heading estimation. In this paper, a real-time miniature orientation determination system (MODS) was developed for indoor heading and trajectory tracking based on a novel dual-linear Kalman filter. The proposed filter precludes the impact of geomagnetic distortions on pitch and roll that the heading is subjected to. A robust calibration approach was designed to improve the accuracy of sensors measurements based on a unified sensor model. Online tests were performed on the MODS with an improved turntable. The results demonstrate that the average RMSE (root-mean-square error) of heading estimation is less than 1°. Indoor heading experiments were carried out with the MODS mounted on the shoe of pedestrian. Besides, we integrated the existing MODS into an indoor pedestrian dead reckoning application as an example of its utility in realistic actions. A human attitude-based walking model was developed to calculate the walking distance. Test results indicate that mean percentage error of indoor trajectory tracking achieves 2% of the total walking distance. This paper provides a feasible alternative for accurate indoor heading and trajectory tracking.
Indoor 3D Route Modeling Based On Estate Spatial Data
NASA Astrophysics Data System (ADS)
Zhang, H.; Wen, Y.; Jiang, J.; Huang, W.
2014-04-01
Indoor three-dimensional route model is essential for space intelligence navigation and emergency evacuation. This paper is motivated by the need of constructing indoor route model automatically and as far as possible. By comparing existing building data sources, this paper firstly explained the reason why the estate spatial management data is chosen as the data source. Then, an applicable method of construction three-dimensional route model in a building is introduced by establishing the mapping relationship between geographic entities and their topological expression. This data model is a weighted graph consist of "node" and "path" to express the spatial relationship and topological structure of a building components. The whole process of modelling internal space of a building is addressed by two key steps: (1) each single floor route model is constructed, including path extraction of corridor using Delaunay triangulation algorithm with constrained edge, fusion of room nodes into the path; (2) the single floor route model is connected with stairs and elevators and the multi-floor route model is eventually generated. In order to validate the method in this paper, a shopping mall called "Longjiang New City Plaza" in Nanjing is chosen as a case of study. And the whole building space is constructed according to the modelling method above. By integrating of existing path finding algorithm, the usability of this modelling method is verified, which shows the indoor three-dimensional route modelling method based on estate spatial data in this paper can support indoor route planning and evacuation route design very well.
Automated time activity classification based on global positioning system (GPS) tracking data
2011-01-01
Background Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. Methods We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Results Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Conclusions Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns. PMID:22082316
Automated time activity classification based on global positioning system (GPS) tracking data.
Wu, Jun; Jiang, Chengsheng; Houston, Douglas; Baker, Dean; Delfino, Ralph
2011-11-14
Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.
Chen, Jing
2017-04-01
This study calculates and compares the lifetime lung cancer risks associated with indoor radon exposure based on well-known risk models in the literature; two risk models are from joint studies among miners and the other three models were developed from pooling studies on residential radon exposure from China, Europe and North America respectively. The aim of this article is to make clear that the various models are mathematical descriptions of epidemiologically observed real risks in different environmental settings. The risk from exposure to indoor radon is real and it is normal that variations could exist among different risk models even when they were applied to the same dataset. The results show that lifetime risk estimates vary significantly between the various risk models considered here: the model based on the European residential data provides the lowest risk estimates, while models based on the European miners and Chinese residential pooling with complete dosimetry give the highest values. The lifetime risk estimates based on the EPA/BEIR-VI model lie within this range and agree reasonably well with the averages of risk estimates from the five risk models considered in this study. © Crown copyright 2016.
NASA Astrophysics Data System (ADS)
Shin, Hyeong-Moo; McKone, Thomas E.; Bennett, Deborah H.
2013-04-01
Exposure to environmental chemicals results from multiple sources, environmental media, and exposure routes. Ideally, modeled exposures should be compared to biomonitoring data. This study compares the magnitude and variation of modeled polycyclic aromatic hydrocarbons (PAHs) exposures resulting from emissions to outdoor and indoor air and estimated exposure inferred from biomarker levels. Outdoor emissions result in both inhalation and food-based exposures. We modeled PAH intake doses using U.S. EPA's 2002 National Air Toxics Assessment (NATA) county-level emissions data for outdoor inhalation, the CalTOX model for food ingestion (based on NATA emissions), and indoor air concentrations from field studies for indoor inhalation. We then compared the modeled intake with the measured urine levels of hydroxy-PAH metabolites from the 2001-2002 National Health and Nutrition Examination Survey (NHANES) survey as quantifiable human intake of PAH parent-compounds. Lognormal probability plots of modeled intakes and estimated intakes inferred from biomarkers suggest that a primary route of exposure to naphthalene, fluorene, and phenanthrene for the U.S. population is likely inhalation from indoor sources. For benzo(a)pyrene, the predominant exposure route is likely from food ingestion resulting from multi-pathway transport and bioaccumulation due to outdoor emissions. Multiple routes of exposure are important for pyrene. We also considered the sensitivity of the predicted exposure to the proportion of the total naphthalene production volume emitted to the indoor environment. The comparison of PAH biomarkers with exposure variability estimated from models and sample data for various exposure pathways supports that both indoor and outdoor models are needed to capture the sources and routes of exposure to environmental contaminants.
Alshami, Iyad Husni; Sahibuddin, Shamsul; Firdaus, Firdaus
2017-01-01
The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS) differently, and peoples’ presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS) based on: a dynamic radio map generator, RSS certainty technique and peoples’ presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples’ presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices. PMID:28783047
Extracting Topological Relations Between Indoor Spaces from Point Clouds
NASA Astrophysics Data System (ADS)
Tran, H.; Khoshelham, K.; Kealy, A.; Díaz-Vilariño, L.
2017-09-01
3D models of indoor environments are essential for many application domains such as navigation guidance, emergency management and a range of indoor location-based services. The principal components defined in different BIM standards contain not only building elements, such as floors, walls and doors, but also navigable spaces and their topological relations, which are essential for path planning and navigation. We present an approach to automatically reconstruct topological relations between navigable spaces from point clouds. Three types of topological relations, namely containment, adjacency and connectivity of the spaces are modelled. The results of initial experiments demonstrate the potential of the method in supporting indoor navigation.
Hillhouse, Joel; Turrisi, Rob; Scaglione, Nichole M.; Cleveland, Michael J.; Baker, Katie; Florence, L. Carter
2016-01-01
Youthful indoor tanning as few as ten sessions can increase the risk of melanoma by 2 to 4 times with each additional session adding another 2% to the risk. Recent research estimates that indoor tanning can be linked to approximately 450,000 cases of skin cancer annually in the United States, Europe, and Australia. Despite these risks, indoor tanning remains popular with adolescents. This study tested the efficacy of a web-based skin cancer prevention intervention designed to reduce indoor tanning motivations in adolescent females. A nationally representative sample of 443 female teens were enrolled from an online panel into a two-arm, parallel group design, randomized controlled trial. Treatment participants received an appearance-focused intervention grounded in established health behavior change models. Controls viewed a teen alcohol prevention website. Outcome variables included willingness and intentions to indoor tan, willingness to sunless tan and measures of indoor tanning attitudes and beliefs. The intervention decreased willingness and intentions to indoor tan and increased sunless tanning willingness relative to controls. We also examined indirect mechanisms of change through intervening variables (e.g., indoor tanning attitudes, norms, positive and negative expectancies) using the product of coefficients approach. The web-based intervention demonstrated efficacy in changing adolescent indoor tanning motivations and improving their orientation toward healthier alternatives. Results from the intervening variable analyses give guidance to future adolescent skin cancer prevention interventions. PMID:27549602
Hillhouse, Joel; Turrisi, Rob; Scaglione, Nichole M; Cleveland, Michael J; Baker, Katie; Florence, L Carter
2017-02-01
Youthful indoor tanning as few as ten sessions can increase the risk of melanoma by two to four times with each additional session adding another 2 % to the risk. Recent research estimates that indoor tanning can be linked to approximately 450,000 cases of skin cancer annually in the USA, Europe, and Australia. Despite these risks, indoor tanning remains popular with adolescents. This study tested the efficacy of a web-based skin cancer prevention intervention designed to reduce indoor tanning motivations in adolescent females. A nationally representative sample of 443 female teens was enrolled from an online panel into a two-arm, parallel group design, randomized controlled trial. Treatment participants received an appearance-focused intervention grounded in established health behavior change models. Controls viewed a teen alcohol prevention website. Outcome variables included willingness and intentions to indoor tan, willingness to sunless tan, and measures of indoor tanning attitudes and beliefs. The intervention decreased willingness and intentions to indoor tan and increased sunless tanning willingness relative to controls. We also examined indirect mechanisms of change through intervening variables (e.g., indoor tanning attitudes, norms, positive and negative expectancies) using the product of coefficient approach. The web-based intervention demonstrated efficacy in changing adolescent indoor tanning motivations and improving their orientation toward healthier alternatives. Results from the intervening variable analyses give guidance to future adolescent skin cancer prevention interventions.
NASA Astrophysics Data System (ADS)
Nakagawa, M.; Akano, K.; Kobayashi, T.; Sekiguchi, Y.
2017-09-01
Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.
Modeling indoor air pollution of outdoor origin in homes of SAPALDIA subjects in Switzerland.
Meier, Reto; Schindler, Christian; Eeftens, Marloes; Aguilera, Inmaculada; Ducret-Stich, Regina E; Ineichen, Alex; Davey, Mark; Phuleria, Harish C; Probst-Hensch, Nicole; Tsai, Ming-Yi; Künzli, Nino
2015-09-01
Given the shrinking spatial contrasts in outdoor air pollution in Switzerland and the trends toward tightly insulated buildings, the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) needs to understand to what extent outdoor air pollution remains a determinant for residential indoor exposure. The objectives of this paper are to identify determining factors for indoor air pollution concentrations of particulate matter (PM), ultrafine particles in the size range from 15 to 300nm, black smoke measured as light absorbance of PM (PMabsorbance) and nitrogen dioxide (NO2) and to develop predictive indoor models for SAPALDIA. Multivariable regression models were developed based on indoor and outdoor measurements among homes of selected SAPALDIA participants in three urban (Basel, Geneva, Lugano) and one rural region (Wald ZH) in Switzerland, various home characteristics and reported indoor sources such as cooking. Outdoor levels of air pollutants were important predictors for indoor air pollutants, except for the coarse particle fraction. The fractions of outdoor concentrations infiltrating indoors were between 30% and 66%, the highest one was observed for PMabsorbance. A modifying effect of open windows was found for NO2 and the ultrafine particle number concentration. Cooking was associated with increased particle and NO2 levels. This study shows that outdoor air pollution remains an important determinant of residential indoor air pollution in Switzerland. Copyright © 2015 Elsevier Ltd. All rights reserved.
Effects of ventilation behaviour on indoor heat load based on test reference years.
Rosenfelder, Madeleine; Koppe, Christina; Pfafferott, Jens; Matzarakis, Andreas
2016-02-01
Since 2003, most European countries established heat health warning systems to alert the population to heat load. Heat health warning systems are based on predicted meteorological conditions outdoors. But the majority of the European population spends a substantial amount of time indoors, and indoor thermal conditions can differ substantially from outdoor conditions. The German Meteorological Service (Deutscher Wetterdienst, DWD) extended the existing heat health warning system (HHWS) with a thermal building simulation model to consider heat load indoors. In this study, the thermal building simulation model is used to simulate a standardized building representing a modern nursing home, because elderly and sick people are most sensitive to heat stress. Different types of natural ventilation were simulated. Based on current and future test reference years, changes in the future heat load indoors were analyzed. Results show differences between the various ventilation options and the possibility to minimize the thermal heat stress during summer by using an appropriate ventilation method. Nighttime ventilation for indoor thermal comfort is most important. A fully opened window at nighttime and the 2-h ventilation in the morning and evening are more sufficient to avoid heat stress than a tilted window at nighttime and the 1-h ventilation in the morning and the evening. Especially the ventilation in the morning seems to be effective to keep the heat load indoors low. Comparing the results for the current and the future test reference years, an increase of heat stress on all ventilation types can be recognized.
Effects of ventilation behaviour on indoor heat load based on test reference years
NASA Astrophysics Data System (ADS)
Rosenfelder, Madeleine; Koppe, Christina; Pfafferott, Jens; Matzarakis, Andreas
2016-02-01
Since 2003, most European countries established heat health warning systems to alert the population to heat load. Heat health warning systems are based on predicted meteorological conditions outdoors. But the majority of the European population spends a substantial amount of time indoors, and indoor thermal conditions can differ substantially from outdoor conditions. The German Meteorological Service (Deutscher Wetterdienst, DWD) extended the existing heat health warning system (HHWS) with a thermal building simulation model to consider heat load indoors. In this study, the thermal building simulation model is used to simulate a standardized building representing a modern nursing home, because elderly and sick people are most sensitive to heat stress. Different types of natural ventilation were simulated. Based on current and future test reference years, changes in the future heat load indoors were analyzed. Results show differences between the various ventilation options and the possibility to minimize the thermal heat stress during summer by using an appropriate ventilation method. Nighttime ventilation for indoor thermal comfort is most important. A fully opened window at nighttime and the 2-h ventilation in the morning and evening are more sufficient to avoid heat stress than a tilted window at nighttime and the 1-h ventilation in the morning and the evening. Especially the ventilation in the morning seems to be effective to keep the heat load indoors low. Comparing the results for the current and the future test reference years, an increase of heat stress on all ventilation types can be recognized.
Modeling indoor particulate exposures in inner city school classrooms
Gaffin, Jonathan M.; Petty, Carter R.; Hauptman, Marissa; Kang, Choong-Min; Wolfson, Jack M.; Awad, Yara Abu; Di, Qian; Lai, Peggy S.; Sheehan, William J.; Baxi, Sachin; Coull, Brent A.; Schwartz, Joel D.; Gold, Diane R.; Koutrakis, Petros; Phipatanakul, Wanda
2016-01-01
Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed-effects linear models were used to determine the relationships between indoor PM2.5 and BC and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor-outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM2.5 and BC in 199 samples from 136 classrooms (30 school buildings) were compared to those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: 1) there are important PM2.5 sources in classrooms; 2) the penetration of outdoor PM2.5 particles varies by school, and 3) the site-specific outside PM2.5 levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (Out of sample correlations: PM2.5: r2 = 0.68, BC; r2 = 0.61). Our results suggest that PM2.5 has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available. PMID:27599884
Continuous Indoor Positioning Fusing WiFi, Smartphone Sensors and Landmarks
Deng, Zhi-An; Wang, Guofeng; Qin, Danyang; Na, Zhenyu; Cui, Yang; Chen, Juan
2016-01-01
To exploit the complementary strengths of WiFi positioning, pedestrian dead reckoning (PDR), and landmarks, we propose a novel fusion approach based on an extended Kalman filter (EKF). For WiFi positioning, unlike previous fusion approaches setting measurement noise parameters empirically, we deploy a kernel density estimation-based model to adaptively measure the related measurement noise statistics. Furthermore, a trusted area of WiFi positioning defined by fusion results of previous step and WiFi signal outlier detection are exploited to reduce computational cost and improve WiFi positioning accuracy. For PDR, we integrate a gyroscope, an accelerometer, and a magnetometer to determine the user heading based on another EKF model. To reduce accumulation error of PDR and enable continuous indoor positioning, not only the positioning results but also the heading estimations are recalibrated by indoor landmarks. Experimental results in a realistic indoor environment show that the proposed fusion approach achieves substantial positioning accuracy improvement than individual positioning approaches including PDR and WiFi positioning. PMID:27608019
Continuous Indoor Positioning Fusing WiFi, Smartphone Sensors and Landmarks.
Deng, Zhi-An; Wang, Guofeng; Qin, Danyang; Na, Zhenyu; Cui, Yang; Chen, Juan
2016-09-05
To exploit the complementary strengths of WiFi positioning, pedestrian dead reckoning (PDR), and landmarks, we propose a novel fusion approach based on an extended Kalman filter (EKF). For WiFi positioning, unlike previous fusion approaches setting measurement noise parameters empirically, we deploy a kernel density estimation-based model to adaptively measure the related measurement noise statistics. Furthermore, a trusted area of WiFi positioning defined by fusion results of previous step and WiFi signal outlier detection are exploited to reduce computational cost and improve WiFi positioning accuracy. For PDR, we integrate a gyroscope, an accelerometer, and a magnetometer to determine the user heading based on another EKF model. To reduce accumulation error of PDR and enable continuous indoor positioning, not only the positioning results but also the heading estimations are recalibrated by indoor landmarks. Experimental results in a realistic indoor environment show that the proposed fusion approach achieves substantial positioning accuracy improvement than individual positioning approaches including PDR and WiFi positioning.
A 3D Model Based Imdoor Navigation System for Hubei Provincial Museum
NASA Astrophysics Data System (ADS)
Xu, W.; Kruminaite, M.; Onrust, B.; Liu, H.; Xiong, Q.; Zlatanova, S.
2013-11-01
3D models are more powerful than 2D maps for indoor navigation in a complicate space like Hubei Provincial Museum because they can provide accurate descriptions of locations of indoor objects (e.g., doors, windows, tables) and context information of these objects. In addition, the 3D model is the preferred navigation environment by the user according to the survey. Therefore a 3D model based indoor navigation system is developed for Hubei Provincial Museum to guide the visitors of museum. The system consists of three layers: application, web service and navigation, which is built to support localization, navigation and visualization functions of the system. There are three main strengths of this system: it stores all data needed in one database and processes most calculations on the webserver which make the mobile client very lightweight, the network used for navigation is extracted semi-automatically and renewable, the graphic user interface (GUI), which is based on a game engine, has high performance of visualizing 3D model on a mobile display.
Pedestrian mobile mapping system for indoor environments based on MEMS IMU and range camera
NASA Astrophysics Data System (ADS)
Haala, N.; Fritsch, D.; Peter, M.; Khosravani, A. M.
2011-12-01
This paper describes an approach for the modeling of building interiors based on a mobile device, which integrates modules for pedestrian navigation and low-cost 3D data collection. Personal navigation is realized by a foot mounted low cost MEMS IMU, while 3D data capture for subsequent indoor modeling uses a low cost range camera, which was originally developed for gaming applications. Both steps, navigation and modeling, are supported by additional information as provided from the automatic interpretation of evacuation plans. Such emergency plans are compulsory for public buildings in a number of countries. They consist of an approximate floor plan, the current position and escape routes. Additionally, semantic information like stairs, elevators or the floor number is available. After the user has captured an image of such a floor plan, this information is made explicit again by an automatic raster-to-vector-conversion. The resulting coarse indoor model then provides constraints at stairs or building walls, which restrict the potential movement of the user. This information is then used to support pedestrian navigation by eliminating drift effects of the used low-cost sensor system. The approximate indoor building model additionally provides a priori information during subsequent indoor modeling. Within this process, the low cost range camera Kinect is used for the collection of multiple 3D point clouds, which are aligned by a suitable matching step and then further analyzed to refine the coarse building model.
Determinants of indoor benzene in Europe
NASA Astrophysics Data System (ADS)
Lai, H. K.; Jantunen, M. J.; Künzli, N.; Kulinskaya, E.; Colvile, R.; Nieuwenhuijsen, M. J.
This study identified the key determinants associated with the indoor benzene concentrations that were measured between 1996 and 2000 using the EXPOLIS protocol in the residences of six European cities, including Athens (Greece), Basel (Switzerland), Helsinki (Finland), Milan (Italy), Oxford (United Kingdom), and Prague (Czech Republic). Two consecutive days of home indoor and home outdoor measurements of benzene were carried out at the homes of adult participants on different dates and seasons during the sampling period. Regression models, with interactions searched by all-possible subset method, were used to assess the city effects and the determinants of home indoor benzene (adjusted R2=0.57, n=412). Outdoor benzene concentrations, outdoor temperature, wind speed, the use of anti-moth products, and indoor smoking in terms of number of cigarettes consumed per day were shown to be the key determinants of indoor benzene concentrations. The model was further used to predict the indoor benzene levels in cities. Non-linear relationships were commonly found, indicating that a unit change in the indoor concentration cannot be simply estimated by a proportional change of the determinant, and the pattern of relationships could be differed in different places. This finding is important in formulating indoor air quality guidelines as well as calculating an accurate health risk estimate based on the estimates of population's lifetime exposure levels.
Aronson, Dallas B; Bosch, Stephen; Gray, D Anthony; Howard, Philip H; Guiney, Patrick D
2007-10-01
A comparison of the human health risk to consumers using one of two types of toilet rimblock products, either a p-dichlorobenzene-based rimblock or two newer fragrance/surfactant-based alternatives, was conducted. Rimblock products are designed for global use by consumers worldwide and function by releasing volatile compounds into indoor air with subsequent exposure presumed to be mainly by inhalation of indoor air. Using the THERdbASE exposure model and experimentally determined emission data, indoor air concentrations and daily intake values were determined for both types of rimblock products. Modeled exposure concentrations from a representative p-dichlorobenzene rimblock product are an order of magnitude higher than those from the alternative rimblock products due to its nearly pure composition and high sublimation rate. Lifetime exposure to p-dichlorobenzene or the subset of fragrance components with available RfD values is not expected to lead to non-cancer-based adverse health effects based on the exposure concentrations estimated using the THERdbASE model. A similar comparison of cancer-based effects was not possible as insufficient data were available for the fragrance components.
Indoor tanning and the MC1R genotype: risk prediction for basal cell carcinoma risk in young people.
Molinaro, Annette M; Ferrucci, Leah M; Cartmel, Brenda; Loftfield, Erikka; Leffell, David J; Bale, Allen E; Mayne, Susan T
2015-06-01
Basal cell carcinoma (BCC) incidence is increasing, particularly in young people, and can be associated with significant morbidity and treatment costs. To identify young individuals at risk of BCC, we assessed existing melanoma or overall skin cancer risk prediction models and built a novel risk prediction model, with a focus on indoor tanning and the melanocortin 1 receptor gene, MC1R. We evaluated logistic regression models among 759 non-Hispanic whites from a case-control study of patients seen between 2006 and 2010 in New Haven, Connecticut. In our data, the adjusted area under the receiver operating characteristic curve (AUC) for a model by Han et al. (Int J Cancer. 2006;119(8):1976-1984) with 7 MC1R variants was 0.72 (95% confidence interval (CI): 0.66, 0.78), while that by Smith et al. (J Clin Oncol. 2012;30(15 suppl):8574) with MC1R and indoor tanning had an AUC of 0.69 (95% CI: 0.63, 0.75). Our base model had greater predictive ability than existing models and was significantly improved when we added ever-indoor tanning, burns from indoor tanning, and MC1R (AUC = 0.77, 95% CI: 0.74, 0.81). Our early-onset BCC risk prediction model incorporating MC1R and indoor tanning extends the work of other skin cancer risk prediction models, emphasizes the value of both genotype and indoor tanning in skin cancer risk prediction in young people, and should be validated with an independent cohort. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles
NASA Astrophysics Data System (ADS)
Hamledari, Hesam
In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.
Shirazi, Elham; Pennell, Kelly G
2017-12-13
Vapor intrusion (IV) exposure risks are difficult to characterize due to the role of atmospheric, building and subsurface processes. This study presents a three-dimensional VI model that extends the common subsurface fate and transport equations to incorporate wind and stack effects on indoor air pressure, building air exchange rate (AER) and indoor contaminant concentration to improve VI exposure risk estimates. The model incorporates three modeling programs: (1) COMSOL Multiphysics to model subsurface fate and transport processes, (2) CFD0 to model atmospheric air flow around the building, and (3) CONTAM to model indoor air quality. The combined VI model predicts AER values, zonal indoor air pressures and zonal indoor air contaminant concentrations as a function of wind speed, wind direction and outdoor and indoor temperature. Steady state modeling results for a single-story building with a basement demonstrate that wind speed, wind direction and opening locations in a building play important roles in changing the AER, indoor air pressure, and indoor air contaminant concentration. Calculated indoor air pressures ranged from approximately -10 Pa to +4 Pa depending on weather conditions and building characteristics. AER values, mass entry rates and indoor air concentrations vary depending on weather conditions and building characteristics. The presented modeling approach can be used to investigate the relationship between building features, AER, building pressures, soil gas concentrations, indoor air concentrations and VI exposure risks.
Vanhove, Wouter; Maalsté, Nicole; Van Damme, Patrick
2017-07-01
Together, the Netherlands and Belgium are the largest indoor cannabis producing countries in Europe. In both countries, legal prosecution procedure of convicted illicit cannabis growers usually includes recovery of the profits gained. However, it is not easy to make a reliable estimation of the latter profits, due to the wide range of factors that determine indoor cannabis yields and eventual selling prices. In the Netherlands, since 2005, a reference model is used that assumes a constant yield (g) per plant for a given indoor cannabis plant density. Later, in 2011, a new model was developed in Belgium for yield estimation of Belgian indoor cannabis plantations that assumes a constant yield per m 2 of growth surface, provided that a number of growth conditions are met. Indoor cannabis plantations in the Netherlands and Belgium share similar technical characteristics. As a result, for indoor cannabis plantations in both countries, both aforementioned yield estimation models should yield similar yield estimations. By means of a real-case study from the Netherlands, we show that the reliability of both models is hampered by a number of flaws and unmet preconditions. The Dutch model is based on a regression equation that makes use of ill-defined plant development stages, assumes a linear plant growth, does not discriminate between different plantation size categories and does not include other important yield determining factors (such as fertilization). The Belgian model addresses some of the latter shortcomings, but its applicability is constrained by a number of pre-conditions including plantation size between 50 and 1000 plants; cultivation in individual pots with peat soil; 600W (electrical power) assimilation lamps; constant temperature between 20°C and 30°C; adequate fertilizer application and plants unaffected by pests and diseases. Judiciary in both the Netherlands and Belgium require robust indoor cannabis yield models for adequate legal prosecution of illicit indoor cannabis growth operations. To that aim, the current models should be optimized whereas the validity of their application should be examined case by case. Copyright © 2017 Elsevier B.V. All rights reserved.
Grammar-Supported 3d Indoor Reconstruction from Point Clouds for As-Built Bim
NASA Astrophysics Data System (ADS)
Becker, S.; Peter, M.; Fritsch, D.
2015-03-01
The paper presents a grammar-based approach for the robust automatic reconstruction of 3D interiors from raw point clouds. The core of the approach is a 3D indoor grammar which is an extension of our previously published grammar concept for the modeling of 2D floor plans. The grammar allows for the modeling of buildings whose horizontal, continuous floors are traversed by hallways providing access to the rooms as it is the case for most office buildings or public buildings like schools, hospitals or hotels. The grammar is designed in such way that it can be embedded in an iterative automatic learning process providing a seamless transition from LOD3 to LOD4 building models. Starting from an initial low-level grammar, automatically derived from the window representations of an available LOD3 building model, hypotheses about indoor geometries can be generated. The hypothesized indoor geometries are checked against observation data - here 3D point clouds - collected in the interior of the building. The verified and accepted geometries form the basis for an automatic update of the initial grammar. By this, the knowledge content of the initial grammar is enriched, leading to a grammar with increased quality. This higher-level grammar can then be applied to predict realistic geometries to building parts where only sparse observation data are available. Thus, our approach allows for the robust generation of complete 3D indoor models whose quality can be improved continuously as soon as new observation data are fed into the grammar-based reconstruction process. The feasibility of our approach is demonstrated based on a real-world example.
Woodruff, Susan I.; Slymen, Donald J.; Sallis, James F.; Forster, Jean L.; Clapp, Elizabeth J.; Hoerster, Katherine D.; Pichon, Latrice C.; Weeks, John R.; Belch, George E.; Weinstock, Martin A.; Gilmer, Todd
2011-01-01
Objectives. We evaluated psychosocial, built-environmental, and policy-related correlates of adolescents’ indoor tanning use. Methods. We developed 5 discrete data sets in the 100 most populous US cities, based on interviews of 6125 adolescents (aged 14–17 years) and their parents, analysis of state indoor tanning laws, interviews with enforcement experts, computed density of tanning facilities, and evaluations of these 3399 facilities’ practices regarding access by youths. After univariate analyses, we constructed multilevel models with generalized linear mixed models (GLMMs). Results. In the past year, 17.1% of girls and 3.2% of boys had used indoor tanning. The GLMMs indicated that several psychosocial or demographic variables significantly predicted use, including being female, older, and White; having a larger allowance and a parent who used indoor tanning and allowed their adolescent to use it; and holding certain beliefs about indoor tanning's consequences. Living within 2 miles of a tanning facility also was a significant predictor. Residing in a state with youth-access legislation was not significantly associated with use. Conclusions. Current laws appear ineffective in reducing indoor tanning; bans likely are needed. Parents have an important role in prevention efforts. PMID:21421947
3-D model-based tracking for UAV indoor localization.
Teulière, Céline; Marchand, Eric; Eck, Laurent
2015-05-01
This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localization problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights.
The role of building models in the evaluation of heat-related risks
NASA Astrophysics Data System (ADS)
Buchin, Oliver; Jänicke, Britta; Meier, Fred; Scherer, Dieter; Ziegler, Felix
2016-04-01
Hazard-risk relationships in epidemiological studies are generally based on the outdoor climate, despite the fact that most of humans' lifetime is spent indoors. By coupling indoor and outdoor climates with a building model, the risk concept developed can still be based on the outdoor conditions but also includes exposure to the indoor climate. The influence of non-linear building physics and the impact of air conditioning on heat-related risks can be assessed in a plausible manner using this risk concept. For proof of concept, the proposed risk concept is compared to a traditional risk analysis. As an example, daily and city-wide mortality data of the age group 65 and older in Berlin, Germany, for the years 2001-2010 are used. Four building models with differing complexity are applied in a time-series regression analysis. This study shows that indoor hazard better explains the variability in the risk data compared to outdoor hazard, depending on the kind of building model. Simplified parameter models include the main non-linear effects and are proposed for the time-series analysis. The concept shows that the definitions of heat events, lag days, and acclimatization in a traditional hazard-risk relationship are influenced by the characteristics of the prevailing building stock.
Colard, Stéphane; O’Connell, Grant; Verron, Thomas; Cahours, Xavier; Pritchard, John D.
2014-01-01
There has been rapid growth in the use of electronic cigarettes (“vaping”) in Europe, North America and elsewhere. With such increased prevalence, there is currently a debate on whether the aerosol exhaled following the use of e-cigarettes has implications for the quality of air breathed by bystanders. Conducting chemical analysis of the indoor environment can be costly and resource intensive, limiting the number of studies which can be conducted. However, this can be modelled reasonably accurately based on empirical emissions data and using some basic assumptions. Here, we present a simplified model, based on physical principles, which considers aerosol propagation, dilution and extraction to determine the potential contribution of a single puff from an e-cigarette to indoor air. From this, it was then possible to simulate the cumulative effect of vaping over time. The model was applied to a virtual, but plausible, scenario considering an e-cigarette user and a non-user working in the same office space. The model was also used to reproduce published experimental studies and showed good agreement with the published values of indoor air nicotine concentration. With some additional refinements, such an approach may be a cost-effective and rapid way of assessing the potential exposure of bystanders to exhaled e-cigarette aerosol constituents. PMID:25547398
Current implications of past DDT indoor spraying in Oman.
Booij, Petra; Holoubek, Ivan; Klánová, Jana; Kohoutek, Jiří; Dvorská, Alice; Magulová, Katarína; Al-Zadjali, Said; Čupr, Pavel
2016-04-15
In Oman, DDT was sprayed indoors during an intensive malaria eradication program between 1976 and 1992. DDT can remain for years after spraying and is associated with potential health risk. This raises the concern for human exposure in areas where DDT was used for indoor spraying. Twelve houses in three regions with a different history of DDT indoor spraying were chosen for a sampling campaign in 2005 to determine p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT), p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) and p,p'-dichlorodiphenyldichloroethane (p,p'-DDD) levels in indoor air, dust, and outdoor soil. Although DDT was only sprayed indoor, p,p'-DDT, p,p'-DDE and p,p'-DDD were also found in outdoor soil. The results indicate that release and exposure continue for years after cessation of spraying. The predicted cancer risk based on concentrations determined in 2005, indicate that there was still a significant cancer risk up to 13 to 16years after indoor DDT spraying. A novel approach, based on region-specific half-lives, was used to predict concentrations in 2015 and showed that more than 21years after spraying, cancer risk for exposure to indoor air, dust, and outdoor soil are acceptable in Oman for adults and young children. The model can be used for other locations and countries to predict prospective exposure of contaminants based on indoor experimental measurements and knowledge about the spraying time-schedule to extrapolate region-specific half-lives and predict effects on the human population years after spraying. Copyright © 2015 Elsevier B.V. All rights reserved.
Appleton, J D; Cave, M R; Miles, J C H; Sumerling, T J
2011-03-01
Least squares (LS), Theil's (TS) and weighted total least squares (WTLS) regression analysis methods are used to develop empirical relationships between radium in the ground, radon in soil and radon in dwellings to assist in the post-closure assessment of indoor radon related to near-surface radioactive waste disposal at the Low Level Waste Repository in England. The data sets used are (i) estimated ²²⁶Ra in the < 2 mm fraction of topsoils (eRa226) derived from equivalent uranium (eU) from airborne gamma spectrometry data, (ii) eRa226 derived from measurements of uranium in soil geochemical samples, (iii) soil gas radon and (iv) indoor radon data. For models comparing indoor radon and (i) eRa226 derived from airborne eU data and (ii) soil gas radon data, some of the geological groupings have significant slopes. For these groupings there is reasonable agreement in slope and intercept between the three regression analysis methods (LS, TS and WTLS). Relationships between radon in dwellings and radium in the ground or radon in soil differ depending on the characteristics of the underlying geological units, with more permeable units having steeper slopes and higher indoor radon concentrations for a given radium or soil gas radon concentration in the ground. The regression models comparing indoor radon with soil gas radon have intercepts close to 5 Bq m⁻³ whilst the intercepts for those comparing indoor radon with eRa226 from airborne eU vary from about 20 Bq m⁻³ for a moderately permeable geological unit to about 40 Bq m⁻³ for highly permeable limestone, implying unrealistically high contributions to indoor radon from sources other than the ground. An intercept value of 5 Bq m⁻³ is assumed as an appropriate mean value for the UK for sources of indoor radon other than radon from the ground, based on examination of UK data. Comparison with published data used to derive an average indoor radon: soil ²²⁶Ra ratio shows that whereas the published data are generally clustered with no obvious correlation, the data from this study have substantially different relationships depending largely on the permeability of the underlying geology. Models for the relatively impermeable geological units plot parallel to the average indoor radon: soil ²²⁶Ra model but with lower indoor radon: soil ²²⁶Ra ratios, whilst the models for the permeable geological units plot parallel to the average indoor radon: soil ²²⁶Ra model but with higher than average indoor radon: soil ²²⁶Ra ratios. Copyright © 2010 Natural Environment Research Council. Published by Elsevier Ltd.. All rights reserved.
Zhu, Yue-Shan; Yang, Wan-Dong; Li, Xiu-Wen; Ni, Hong-Gang; Zeng, Hui
2018-02-01
The quality of indoor environments has a significant impact on public health. Usually, an indoor environment is treated as a static box, in which physicochemical reactions of indoor air contaminants are negligible. This results in conservative estimates for primary indoor air pollutant concentrations, while also ignoring secondary pollutants. Thus, understanding the relationship between indoor and outdoor particles and particle-bound pollutants is of great significance. For this reason, we collected simultaneous indoor and outdoor measurements of the size distribution of airborne brominated flame retardant (BFR) congeners. The time-dependent concentrations of indoor particles and particle-bound BFRs were then estimated with the mass balance model, accounting for the outdoor concentration, indoor source strength, infiltration, penetration, deposition and indoor resuspension. Based on qualitative observation, the size distributions of ΣPBDE and ΣHBCD were characterized by bimodal peaks. According to our results, particle-bound BDE209 and γ-HBCD underwent degradation. Regardless of the surface adsorption capability of particles and the physicochemical properties of the target compounds, the concentration of BFRs in particles of different size fractions seemed to be governed by the particle distribution. Based on our estimations, for airborne particles and particle-bound BFRs, a window-open ventilated room only takes a quarter of the time to reach an equilibrium between the concentration of pollutants inside and outside compared to a closed room. Unfortunately, indoor pollutants and outdoor pollutants always exist simultaneously, which poses a window-open-or-closed dilemma to achieve proper ventilation. Copyright © 2017 Elsevier Ltd. All rights reserved.
Navigation studies based on the ubiquitous positioning technologies
NASA Astrophysics Data System (ADS)
Ye, Lei; Mi, Weijie; Wang, Defeng
2007-11-01
This paper summarized the nowadays positioning technologies, such as absolute positioning methods and relative positioning methods, indoor positioning and outdoor positioning, active positioning and passive positioning. Global Navigation Satellite System (GNSS) technologies were introduced as the omnipresent out-door positioning technologies, including GPS, GLONASS, Galileo and BD-1/2. After analysis of the shortcomings of GNSS, indoor positioning technologies were discussed and compared, including A-GPS, Cellular network, Infrared, Electromagnetism, Computer Vision Cognition, Embedded Pressure Sensor, Ultrasonic, RFID (Radio Frequency IDentification), Bluetooth, WLAN etc.. Then the concept and characteristics of Ubiquitous Positioning was proposed. After the ubiquitous positioning technologies contrast and selection followed by system engineering methodology, a navigation system model based on Incorporate Indoor-Outdoor Positioning Solution was proposed. And this model was simulated in the Galileo Demonstration for World Expo Shanghai project. In the conclusion, the prospects of ubiquitous positioning based navigation were shown, especially to satisfy the public location information acquiring requirement.
NASA Astrophysics Data System (ADS)
Kumar, Manish; Sharma, Navjeet; Sarin, Amit
2018-05-01
Studies have confirmed that elevated levels of radon/thoron in the human-environments can substantially increase the risk of lung cancer in general population. The building materials are the second largest contributors to indoor radon/thoron after soil and bedrock beneath dwellings. In present investigation, the exhalation rates of radon/thoron from different building materials samples have been analysed using active technique. Radon/thoron concentrations in a model room have been predicted based on the exhalation rates from walls, floor and roof. The indoor concentrations show significant variations depending upon the ventilation rate and type of building materials used.
REVIEW OF INDOOR EMISSION SOURCE MODELS--PART 1. OVERVIEW
Indoor emission source models are mainly used as a component in indoor air quality (IAQ) and exposure modeling. They are also widely used to interpret the experimental data obtained from environmental chambers and buildings. This paper compiles 46 indoor emission source models fo...
NASA Astrophysics Data System (ADS)
Mendez, Maxence; Blond, Nadège; Blondeau, Patrice; Schoemaecker, Coralie; Hauglustaine, Didier A.
2015-12-01
INCA-Indoor, a new indoor air quality (IAQ) model, has been developed to simulate the concentrations of volatile organic compounds (VOC) and oxidants considering indoor air specific processes such as: emission, ventilation, surface interactions (sorption, deposition, uptake). Based on the detailed version of SAPRC-07 chemical mechanism, INCA-Indoor is able to analyze the contribution of the production and loss pathways of key chemical species (VOCs, oxidants, radical species). The potential of this model has been tested through three complementary analyses: a comparison with the most detailed IAQ model found in the literature, focusing on oxidant species; realistic scenarios covering a large range of conditions, involving variable OH sources like HONO; and the investigation of alkenes ozonolysis under a large range of indoor conditions that can increase OH and HO2 concentrations. Simulations have been run changing nitrous acid (HONO) concentrations, NOx levels, photolysis rates and ventilation rates, showing that HONO can be the main source of indoor OH. Cleaning events using products containing D-limonene have been simulated at different periods of the day. These scenarios show that HOX concentrations can significantly increase in specific conditions. An assessment of the impact of indoor chemistry on the potential formation of secondary species such as formaldehyde (HCHO) and acetaldehyde (CH3CHO) has been carried out under various room configuration scenarios and a study of the HOx budget for different realistic scenarios has been performed. It has been shown that, under the simulation conditions, formaldehyde can be affected by oxidant concentrations via chemical production which can account for more than 10% of the total production, representing 6.5 ppb/h. On the other hand, acetaldehyde production is affected more by oxidation processes. When the photolysis rates are high, chemical processes are responsible for about 50% of the total production of acetaldehyde (9 ppb/h).
Wang, Hua; Wen, Yingyou; Zhao, Dazhe
2017-07-20
Medical applications have begun to benefit from Internet of Things (IoT) technology through the introduction of wearable devices. Several medical applications require accurate patient location as various changes affect pressure parameters inside the body. This study aims to develop a system to measure indoor altitude for IoT medical applications. We propose a differential barometric-based positioning system to estimate the altitude between a reference sensor and a localizing sensor connected to the human body. The differential barometric altimetry model is introduced to estimate indoor elevations and eliminate environmental artifacts. In addition, a Gaussian filter processing is adopted to remove noise from the elevation measurements. The proposed system is then investigated through extensive experiments, using various evaluation criteria. The results indicate that the proposed system yielded good accuracy with reduced implementation complexity and fewer costs. The proposed system is resilient compared to other indoor localization approaches, even when numerous environmental artifacts in indoor environments are present.
Indoor localization using magnetic fields
NASA Astrophysics Data System (ADS)
Pathapati Subbu, Kalyan Sasidhar
Indoor localization consists of locating oneself inside new buildings. GPS does not work indoors due to multipath reflection and signal blockage. WiFi based systems assume ubiquitous availability and infrastructure based systems require expensive installations, hence making indoor localization an open problem. This dissertation consists of solving the problem of indoor localization by thoroughly exploiting the indoor ambient magnetic fields comprising mainly of disturbances termed as anomalies in the Earth's magnetic field caused by pillars, doors and elevators in hallways which are ferromagnetic in nature. By observing uniqueness in magnetic signatures collected from different campus buildings, the work presents the identification of landmarks and guideposts from these signatures and further develops magnetic maps of buildings - all of which can be used to locate and navigate people indoors. To understand the reason behind these anomalies, first a comparison between the measured and model generated Earth's magnetic field is made, verifying the presence of a constant field without any disturbances. Then by modeling the magnetic field behavior of different pillars such as steel reinforced concrete, solid steel, and other structures like doors and elevators, the interaction of the Earth's field with the ferromagnetic fields is described thereby explaining the causes of the uniqueness in the signatures that comprise these disturbances. Next, by employing the dynamic time warping algorithm to account for time differences in signatures obtained from users walking at different speeds, an indoor localization application capable of classifying locations using the magnetic signatures is developed solely on the smart phone. The application required users to walk short distances of 3-6 m anywhere in hallway to be located with accuracies of 80-99%. The classification framework was further validated with over 90% accuracies using model generated magnetic signatures representing hallways with different kinds of pillars, doors and elevators. All in all, this dissertation contributes the following: 1) provides a framework for understanding the presence of ambient magnetic fields indoors and utilizing them to solve the indoor localization problem; 2) develops an application that is independent of the user and the smart phones and 3) requires no other infrastructure since it is deployed on a device that encapsulates the sensing, computing and inferring functionalities, thereby making it a novel contribution to the mobile and pervasive computing domain.
NASA Astrophysics Data System (ADS)
Baxter, Lisa K.; Clougherty, Jane E.; Paciorek, Christopher J.; Wright, Rosalind J.; Levy, Jonathan I.
Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households. As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3-4 day samples of nitrogen dioxide (NO 2) and fine particulate matter (PM 2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor. The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM 2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO 2 with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50 m buffer of a home and distance from a truck route as important contributors to indoor levels of NO 2 and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.
Received Signal Strength Database Interpolation by Kriging for a Wi-Fi Indoor Positioning System
Jan, Shau-Shiun; Yeh, Shuo-Ju; Liu, Ya-Wen
2015-01-01
The main approach for a Wi-Fi indoor positioning system is based on the received signal strength (RSS) measurements, and the fingerprinting method is utilized to determine the user position by matching the RSS values with the pre-surveyed RSS database. To build a RSS fingerprint database is essential for an RSS based indoor positioning system, and building such a RSS fingerprint database requires lots of time and effort. As the range of the indoor environment becomes larger, labor is increased. To provide better indoor positioning services and to reduce the labor required for the establishment of the positioning system at the same time, an indoor positioning system with an appropriate spatial interpolation method is needed. In addition, the advantage of the RSS approach is that the signal strength decays as the transmission distance increases, and this signal propagation characteristic is applied to an interpolated database with the Kriging algorithm in this paper. Using the distribution of reference points (RPs) at measured points, the signal propagation model of the Wi-Fi access point (AP) in the building can be built and expressed as a function. The function, as the spatial structure of the environment, can create the RSS database quickly in different indoor environments. Thus, in this paper, a Wi-Fi indoor positioning system based on the Kriging fingerprinting method is developed. As shown in the experiment results, with a 72.2% probability, the error of the extended RSS database with Kriging is less than 3 dBm compared to the surveyed RSS database. Importantly, the positioning error of the developed Wi-Fi indoor positioning system with Kriging is reduced by 17.9% in average than that without Kriging. PMID:26343673
Received Signal Strength Database Interpolation by Kriging for a Wi-Fi Indoor Positioning System.
Jan, Shau-Shiun; Yeh, Shuo-Ju; Liu, Ya-Wen
2015-08-28
The main approach for a Wi-Fi indoor positioning system is based on the received signal strength (RSS) measurements, and the fingerprinting method is utilized to determine the user position by matching the RSS values with the pre-surveyed RSS database. To build a RSS fingerprint database is essential for an RSS based indoor positioning system, and building such a RSS fingerprint database requires lots of time and effort. As the range of the indoor environment becomes larger, labor is increased. To provide better indoor positioning services and to reduce the labor required for the establishment of the positioning system at the same time, an indoor positioning system with an appropriate spatial interpolation method is needed. In addition, the advantage of the RSS approach is that the signal strength decays as the transmission distance increases, and this signal propagation characteristic is applied to an interpolated database with the Kriging algorithm in this paper. Using the distribution of reference points (RPs) at measured points, the signal propagation model of the Wi-Fi access point (AP) in the building can be built and expressed as a function. The function, as the spatial structure of the environment, can create the RSS database quickly in different indoor environments. Thus, in this paper, a Wi-Fi indoor positioning system based on the Kriging fingerprinting method is developed. As shown in the experiment results, with a 72.2% probability, the error of the extended RSS database with Kriging is less than 3 dBm compared to the surveyed RSS database. Importantly, the positioning error of the developed Wi-Fi indoor positioning system with Kriging is reduced by 17.9% in average than that without Kriging.
NASA Astrophysics Data System (ADS)
Mousa, Farag I. K.; Almaadeed, Noor; Busawon, Krishna; Bouridane, Ahmed; Binns, Richard; Elliot, Ian
2018-01-01
Visible light communication (VLC) based on light-emitting diodes (LEDs) technology not only provides higher data rate for indoor wireless communications and offering room illumination but also has the potential for indoor localization. VLC-based indoor positioning using the received optical power levels from emitting LEDs is investigated. We consider both scenarios of line-of-sight (LOS) and LOS with non-LOS (LOSNLOS) positioning. The performance of the proposed system is evaluated under both noisy and noiseless channel as is the impact of different location codes on positioning error. The analytical model of the system with noise and the corresponding numerical evaluation for a range of signal-to-noise ratio (SNR) are presented. The results show that an accuracy of <10 cm on average is achievable at an SNR>12 dB.
Modeling the reversible, diffusive sink effect in response to transient contaminant sources.
Zhao, D; Little, J C; Hodgson, A T
2002-09-01
A physically based diffusion model is used to evaluate the sink effect of diffusion-controlled indoor materials and to predict the transient contaminant concentration in indoor air in response to several time-varying contaminant sources. For simplicity, it is assumed the predominant indoor material is a homogeneous slab, initially free of contaminant, and the air within the room is well mixed. The model enables transient volatile organic compound (VOC) concentrations to be predicted based on the material/air partition coefficient (K) and the material-phase diffusion coefficient (D) of the sink. Model predictions are made for three scenarios, each mimicking a realistic situation in a building. Styrene, phenol, and naphthalene are used as representative VOCs. A styrene butadiene rubber (SBR) backed carpet, vinyl flooring (VF), and a polyurethane foam (PUF) carpet cushion are considered as typical indoor sinks. In scenarios involving a sinusoidal VOC input and a double exponential decaying input, the model predicts the sink has a modest impact for SBR/styrene, but the effect increases for VF/phenol and PUF/naphthalene. In contrast, for an episodic chemical spill, SBR is predicted to reduce the peak styrene concentration considerably. A parametric study reveals for systems involving a large equilibrium constant (K), the kinetic constant (D) will govern the shape of the resulting gasphase concentration profile. On the other hand, for systems with a relaxed mass transfer resistance, K will dominate the profile.
A Robust Crowdsourcing-Based Indoor Localization System.
Zhou, Baoding; Li, Qingquan; Mao, Qingzhou; Tu, Wei
2017-04-14
WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS.
A Robust Crowdsourcing-Based Indoor Localization System
Zhou, Baoding; Li, Qingquan; Mao, Qingzhou; Tu, Wei
2017-01-01
WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS. PMID:28420108
Climate change and health: Indoor heat exposure in vulnerable populations☆
White-Newsome, Jalonne L.; Sánchez, Brisa N.; Jolliet, Olivier; Zhang, Zhenzhen; Parker, Edith A.; Dvonch, J. Timothy; O'Neill, Marie S.
2015-01-01
Introduction Climate change is increasing the frequency of heat waves and hot weather in many urban environments. Older people are more vulnerable to heat exposure but spend most of their time indoors. Few published studies have addressed indoor heat exposure in residences occupied by an elderly population. The purpose of this study is to explore the relationship between outdoor and indoor temperatures in homes occupied by the elderly and determine other predictors of indoor temperature. Materials and methods We collected hourly indoor temperature measurements of 30 different homes; outdoor temperature, dewpoint temperature, and solar radiation data during summer 2009 in Detroit, MI. We used mixed linear regression to model indoor temperatures’ responsiveness to weather, housing and environmental characteristics, and evaluated our ability to predict indoor heat exposures based on outdoor conditions. Results Average maximum indoor temperature for all locations was 34.85 °C, 13.8 °C higher than average maximum outdoor temperature. Indoor temperatures of single family homes constructed of vinyl paneling or wood siding were more sensitive than brick homes to outdoor temperature changes and internal heat gains. Outdoor temperature, solar radiation, and dewpoint temperature predicted 38% of the variability of indoor temperatures. Conclusions Indoor exposures to heat in Detroit exceed the comfort range among elderly occupants, and can be predicted using outdoor temperatures, characteristics of the housing stock and surroundings PMID:22071034
Contribution of 222Rn in domestic water supplies to 222Rn in indoor air in Colorado homes
Lawrence, E.P.; Wanty, R.B.; Nyberg, P.
1992-01-01
The contribution of 222Rn from domestic water wells to indoor air was investigated in a study of 28 houses near Conifer, CO. Air concentrations determined by alpha-track detectors (ATDs) and continuous radon monitors were compared with the predictions of a single-cell model. In many of the houses, the water supply was shown to contribute significantly to levels of indoor 222Rn. The data from the ATD study were augmented with a continuous monitoring study of a house near Lyons, CO. The well water in that house has the highest known concentration of 222Rn in water yet reported (93 MBq m-3). The temporal pattern in the indoor 222Rn concentration corresponds to water-use records. In general, it is difficult to quantify the proportion of indoor radon attributable to water use. Several lines of evidence suggest that the single-cell model underestimates this proportion. Continuous- monitoring data, although useful, are impractical due to the cost of the equipment. We propose a protocol for 222Rn measurement based on three simultaneous integrating radon detectors that may help estimate the proportion of indoor 222Rn derived from the water supply.
Modelling of Indoor Environments Using Lindenmayer Systems
NASA Astrophysics Data System (ADS)
Peter, M.
2017-09-01
Documentation of the "as-built" state of building interiors has gained a lot of interest in the recent years. Various data acquisition methods exist, e.g. the extraction from photographed evacuation plans using image processing or, most prominently, indoor mobile laser scanning. Due to clutter or data gaps as well as errors during data acquisition and processing, automatic reconstruction of CAD/BIM-like models from these data sources is not a trivial task. Thus it is often tried to support reconstruction by general rules for the perpendicularity and parallelism which are predominant in man-made structures. Indoor environments of large, public buildings, however, often also follow higher-level rules like symmetry and repetition of e.g. room sizes and corridor widths. In the context of reconstruction of city city elements (e.g. street networks) or building elements (e.g. façade layouts), formal grammars have been put to use. In this paper, we describe the use of Lindenmayer systems - which originally have been developed for the computer-based modelling of plant growth - to model and reproduce the layout of indoor environments in 2D.
Providing pressure inputs to multizone building models
Herring, Steven J.; Batchelor, Simon; Bieringer, Paul E.; ...
2016-02-13
A study to assess how the fidelity of wind pressure inputs and indoor model complexity affect the predicted air change rate for a study building is presented. The purpose of the work is to support the development of a combined indoor-outdoor hazard prediction tool, which links the CONTAM multizone building simulation tool with outdoor dispersion models. The study building, representing a large office block of a simple rectangular geometry under natural ventilation, was based on a real building used in the Joint Urban 2003 experiment. A total of 1600 indoor model flow simulations were made, driven by 100 meteorological conditionsmore » which provided a wide range of building surface pressures. These pressures were applied at four levels of resolution to four different building configurations with varying numbers of internal zones and indoor and outdoor flow paths. Analysis of the results suggests that surface pressures and flow paths across the envelope should be specified at a resolution consistent with the dimensions of the smallest volume of interest, to ensure that appropriate outputs are obtained.« less
A salient region detection model combining background distribution measure for indoor robots.
Li, Na; Xu, Hui; Wang, Zhenhua; Sun, Lining; Chen, Guodong
2017-01-01
Vision system plays an important role in the field of indoor robot. Saliency detection methods, capturing regions that are perceived as important, are used to improve the performance of visual perception system. Most of state-of-the-art methods for saliency detection, performing outstandingly in natural images, cannot work in complicated indoor environment. Therefore, we propose a new method comprised of graph-based RGB-D segmentation, primary saliency measure, background distribution measure, and combination. Besides, region roundness is proposed to describe the compactness of a region to measure background distribution more robustly. To validate the proposed approach, eleven influential methods are compared on the DSD and ECSSD dataset. Moreover, we build a mobile robot platform for application in an actual environment, and design three different kinds of experimental constructions that are different viewpoints, illumination variations and partial occlusions. Experimental results demonstrate that our model outperforms existing methods and is useful for indoor mobile robots.
Climate change and health: Indoor heat exposure in vulnerable populations
DOE Office of Scientific and Technical Information (OSTI.GOV)
White-Newsome, Jalonne L., E-mail: jalonne@umich.edu; Sanchez, Brisa N., E-mail: brisa@umich.edu; Jolliet, Olivier, E-mail: ojolliet@umich.edu
2012-01-15
Introduction: Climate change is increasing the frequency of heat waves and hot weather in many urban environments. Older people are more vulnerable to heat exposure but spend most of their time indoors. Few published studies have addressed indoor heat exposure in residences occupied by an elderly population. The purpose of this study is to explore the relationship between outdoor and indoor temperatures in homes occupied by the elderly and determine other predictors of indoor temperature. Materials and methods: We collected hourly indoor temperature measurements of 30 different homes; outdoor temperature, dewpoint temperature, and solar radiation data during summer 2009 inmore » Detroit, MI. We used mixed linear regression to model indoor temperatures' responsiveness to weather, housing and environmental characteristics, and evaluated our ability to predict indoor heat exposures based on outdoor conditions. Results: Average maximum indoor temperature for all locations was 34.85 Degree-Sign C, 13.8 Degree-Sign C higher than average maximum outdoor temperature. Indoor temperatures of single family homes constructed of vinyl paneling or wood siding were more sensitive than brick homes to outdoor temperature changes and internal heat gains. Outdoor temperature, solar radiation, and dewpoint temperature predicted 38% of the variability of indoor temperatures. Conclusions: Indoor exposures to heat in Detroit exceed the comfort range among elderly occupants, and can be predicted using outdoor temperatures, characteristics of the housing stock and surroundings to improve heat exposure assessment for epidemiological investigations. Weatherizing homes and modifying home surroundings could mitigate indoor heat exposure among the elderly.« less
A mechanistic study of limonene oxidation products and pathways following cleaning activities
NASA Astrophysics Data System (ADS)
Carslaw, Nicola
2013-12-01
Indoor air pollution has caused increasing concern since the 1970s, when the advent of stricter energy efficiency measures lead to increased reports of building related symptoms. Cleaning activities have been linked to adverse health effects indoors, although it is unclear which of the components of cleaning products cause these reported health effects. This paper uses a detailed chemical model for indoor air chemistry, to identify the species formed at the highest concentrations following use of a limonene-based cleaning product. The explicit nature of the chemical mechanism also permits the key pathways to their formation to be identified. The results show that the key species in terms of gas-phase concentration are multi-functional carbonyl species including limonaldehyde, 4-acetyl-1-methyl-1-cyclohexene and other dicarbonyl species. The particle-phase was dominated by peroxide species. The predicted gas-phase concentrations for three limonene-oxidation products were compared to recently published human reference values, but found not to be high enough to cause concern for typical indoor conditions, or under high indoor ozone conditions. However, cleaning products contain a range of terpenes other than limonene, which could also produce some of the secondary products identified here, as well as more common species such as formaldehyde, glyoxal and hydrogen peroxide. A mechanistic pathway analysis shows that the secondary products formed through limonene oxidation indoors depend critically on the competition between ozone and hydroxyl radicals, such that indoor pollutant concentrations and composition could vary widely in different locations for a nominally similar residence and indoor activities. Future studies should focus on aiming to measure multi-functional carbonyl species indoors to help validate models, whilst human reference values are needed for many more relevant species indoors.
Mobile Modelling for Crowdsourcing Building Interior Data
NASA Astrophysics Data System (ADS)
Rosser, J.; Morley, J.; Jackson, M.
2012-06-01
Indoor spatial data forms an important foundation to many ubiquitous computing applications. It gives context to users operating location-based applications, provides an important source of documentation of buildings and can be of value to computer systems where an understanding of environment is required. Unlike external geographic spaces, no centralised body or agency is charged with collecting or maintaining such information. Widespread deployment of mobile devices provides a potential tool that would allow rapid model capture and update by a building's users. Here we introduce some of the issues involved in volunteering building interior data and outline a simple mobile tool for capture of indoor models. The nature of indoor data is inherently private; however in-depth analysis of this issue and legal considerations are not discussed in detail here.
Real-time localization of mobile device by filtering method for sensor fusion
NASA Astrophysics Data System (ADS)
Fuse, Takashi; Nagara, Keita
2017-06-01
Most of the applications with mobile devices require self-localization of the devices. GPS cannot be used in indoor environment, the positions of mobile devices are estimated autonomously by using IMU. Since the self-localization is based on IMU of low accuracy, and then the self-localization in indoor environment is still challenging. The selflocalization method using images have been developed, and the accuracy of the method is increasing. This paper develops the self-localization method without GPS in indoor environment by integrating sensors, such as IMU and cameras, on mobile devices simultaneously. The proposed method consists of observations, forecasting and filtering. The position and velocity of the mobile device are defined as a state vector. In the self-localization, observations correspond to observation data from IMU and camera (observation vector), forecasting to mobile device moving model (system model) and filtering to tracking method by inertial surveying and coplanarity condition and inverse depth model (observation model). Positions of a mobile device being tracked are estimated by system model (forecasting step), which are assumed as linearly moving model. Then estimated positions are optimized referring to the new observation data based on likelihood (filtering step). The optimization at filtering step corresponds to estimation of the maximum a posterior probability. Particle filter are utilized for the calculation through forecasting and filtering steps. The proposed method is applied to data acquired by mobile devices in indoor environment. Through the experiments, the high performance of the method is confirmed.
Active-passive measurements and CFD based modelling for indoor radon dispersion study.
Chauhan, Neetika; Chauhan, R P
2015-06-01
Computational fluid dynamics (CFD) play a significant role in indoor pollutant dispersion study. Radon is an indoor pollutant which is radioactive and inert gas in nature. The concentration level and spatial distribution of radon may be affected by the dwelling's ventilation conditions. Present work focus at the study of indoor radon gas distribution via measurement and CFD modeling in naturally ventilated living room. The need of the study is the prediction of activity level and to study the effect of natural ventilation on indoor radon. Two measurement techniques (Passive measurement using pin-hole dosimeters and active measurement using continuous radon monitor (SRM)) were used for the validation purpose of CFD results. The CFD simulation results were compared with the measurement results at 15 points, 3 XY planes at different heights along with the volumetric average concentration. The simulation results found to be comparable with the measurement results. The future scope of these CFD codes is to study the effect of varying inflow rate of air on the radon concentration level and dispersion pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.
Analysis of Indoor Environment in Classroom Based on Hygienic Requirements
NASA Astrophysics Data System (ADS)
Javorček, Miroslav; Sternová, Zuzana
2016-06-01
The article contains the analysis of experimental ventilation measurement in selected classrooms of the Elementary School Štrba. Mathematical model of selected classroom was prepared according to in-situ measurements and air exchange was calculated. Interior air temperature and quality influences the students ´ comfort. Evaluated data were compared to requirements of standard (STN EN 15251,2008) applicable to classroom indoor environment during lectures, highlighting the difference between required ambiance quality and actually measured values. CO2 concentration refers to one of the parameters indicating indoor environment quality.
NASA Astrophysics Data System (ADS)
Hodas, Natasha; Meng, Qingyu; Lunden, Melissa M.; Turpin, Barbara J.
2014-02-01
Because people spend the majority of their time indoors, the variable efficiency with which ambient PM2.5 penetrates and persists indoors is a source of error in epidemiologic studies that use PM2.5 concentrations measured at central-site monitors as surrogates for ambient PM2.5 exposure. To reduce this error, practical methods to model indoor concentrations of ambient PM2.5 are needed. Toward this goal, we evaluated and refined an outdoor-to-indoor transport model using measured indoor and outdoor PM2.5 species concentrations and air exchange rates from the Relationships of Indoor, Outdoor, and Personal Air Study. Herein, we present model evaluation results, discuss what data are most critical to prediction of residential exposures at the individual-subject and populations levels, and make recommendations for the application of the model in epidemiologic studies. This paper demonstrates that not accounting for certain human activities (air conditioning and heating use, opening windows) leads to bias in predicted residential PM2.5 exposures at the individual-subject level, but not the population level. The analyses presented also provide quantitative evidence that shifts in the gas-particle partitioning of ambient organics with outdoor-to-indoor transport contribute significantly to variability in indoor ambient organic carbon concentrations and suggest that methods to account for these shifts will further improve the accuracy of outdoor-to-indoor transport models.
An electrical circuit model for simulation of indoor radon concentration.
Musavi Nasab, S M; Negarestani, A
2013-01-01
In this study, a new model based on electric circuit theory was introduced to simulate the behaviour of indoor radon concentration. In this model, a voltage source simulates radon generation in walls, conductivity simulates migration through walls and voltage across a capacitor simulates radon concentration in a room. This simulation considers migration of radon through walls by diffusion mechanism in one-dimensional geometry. Data reported in a typical Greek house were employed to examine the application of this technique of simulation to the behaviour of radon.
Study on the Influence of Building Materials on Indoor Pollutants and Pollution Sources
NASA Astrophysics Data System (ADS)
Wang, Yao
2018-01-01
The paper summarizes the achievements and problems of indoor air quality research at home and abroad. The pollutants and pollution sources in the room are analyzed systematically. The types of building materials and pollutants are also discussed. The physical and chemical properties and health effects of main pollutants were analyzed and studied. According to the principle of mass balance, the basic mathematical model of indoor air quality is established. Considering the release rate of pollutants and indoor ventilation, a mathematical model for predicting the concentration of indoor air pollutants is derived. The model can be used to analyze and describe the variation of pollutant concentration in indoor air, and to predict and calculate the concentration of pollutants in indoor air at a certain time. The results show that the mathematical model established in this study can be used to analyze and predict the variation law of pollutant concentration in indoor air. The evaluation model can be used to evaluate the impact of indoor air quality and evaluation of current situation. Especially in the process of building and interior decoration, through pre-evaluation, it can provide reliable design parameters for selecting building materials and determining ventilation volume.
Fabian, Maria Patricia; Adamkiewicz, Gary; Stout, Natasha Kay; Sandel, Megan; Levy, Jonathan Ian
2013-01-01
Background Although indoor environmental conditions can affect pediatric asthmatics, few studies have characterized the impact of building interventions on asthma-related outcomes. Simulation models can evaluate such complex systems but have not been applied in this context. Objective To evaluate the impacts of building interventions on indoor environmental quality and pediatric asthma healthcare utilization, and to conduct cost comparisons between intervention and healthcare costs, and energy savings. Methods We applied our previously developed discrete event simulation model (DEM) to simulate the effect of environmental factors, medication compliance, seasonality, and medical history on: 1) pollutant concentrations indoors, and 2) asthma outcomes in low-income multi-family housing. We estimated healthcare utilization and costs at baseline and subsequent to interventions, and then compared healthcare costs to energy savings and intervention costs. Results Interventions such as integrated pest management and repairing kitchen exhaust fans led to 7–12% reductions in serious asthma events with 1–3 year payback periods. Weatherization efforts targeted solely towards tightening a building envelope led to 20% more serious asthma events, but bundling with repairing kitchen exhaust fans and eliminating indoor sources (e.g. gas stoves or smokers) mitigated this impact. Conclusion Our pediatric asthma model provides a tool to prioritize individual and bundled building interventions based on their impact on health and cost, and highlighting the tradeoffs between weatherization, indoor air quality, and health. Our work bridges the gap between clinical and environmental health sciences by increasing physicians’ understanding of the impact that home environmental changes can have on their patients’ asthma. PMID:23910689
NASA Astrophysics Data System (ADS)
Kollerud, R.; Blaasaas, K.; Ganerød, G.; Daviknes, H. K.; Aune, E.; Claussen, B.
2014-04-01
Radon exposures were assigned to each residential address in the Oslo region using a geographic information system (GIS) that included indoor radon measurements. The results will be used in an epidemiologic study regarding leukemia and brain cancer. The model is based on 6% of measured residential buildings. High density of indoor radon measurements allowed us to develop a buffer model where indoor radon measurements found around each dwelling were used to assign a radon value for homes lacking radon measurement. Intraclass correlation coefficients (ICCs) were used to study the agreement between radon values from the buffer method, from indoor radon values of measured houses, and from a regression model constructed with radiometric data (eTh, eU) and bedrock geology. We obtained good agreement for both comparisons with ICC values between 0.54 and 0.68. GIS offers a useful variety of tools to study the indoor-radon exposure assessment. By using the buffer method it is more likely that geological conditions are similar within the buffer and this may take more into account the variation of radon over short distances. It is also probable that short-distance-scale correlation patterns express similarities in building styles and living habits. Although the method has certain limitations, we regard it as acceptable for use in epidemiological studies.
3D modeling of building indoor spaces and closed doors from imagery and point clouds.
Díaz-Vilariño, Lucía; Khoshelham, Kourosh; Martínez-Sánchez, Joaquín; Arias, Pedro
2015-02-03
3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction.
Vukovic, Vladimir; Tabares-Velasco, Paulo Cesar; Srebric, Jelena
2010-09-01
A growing interest in security and occupant exposure to contaminants revealed a need for fast and reliable identification of contaminant sources during incidental situations. To determine potential contaminant source positions in outdoor environments, current state-of-the-art modeling methods use computational fluid dynamic simulations on parallel processors. In indoor environments, current tools match accidental contaminant distributions with cases from precomputed databases of possible concentration distributions. These methods require intensive computations in pre- and postprocessing. On the other hand, neural networks emerged as a tool for rapid concentration forecasting of outdoor environmental contaminants such as nitrogen oxides or sulfur dioxide. All of these modeling methods depend on the type of sensors used for real-time measurements of contaminant concentrations. A review of the existing sensor technologies revealed that no perfect sensor exists, but intensity of work in this area provides promising results in the near future. The main goal of the presented research study was to extend neural network modeling from the outdoor to the indoor identification of source positions, making this technology applicable to building indoor environments. The developed neural network Locator of Contaminant Sources was also used to optimize number and allocation of contaminant concentration sensors for real-time prediction of indoor contaminant source positions. Such prediction should take place within seconds after receiving real-time contaminant concentration sensor data. For the purpose of neural network training, a multizone program provided distributions of contaminant concentrations for known source positions throughout a test building. Trained networks had an output indicating contaminant source positions based on measured concentrations in different building zones. A validation case based on a real building layout and experimental data demonstrated the ability of this method to identify contaminant source positions. Future research intentions are focused on integration with real sensor networks and model improvements for much more complicated contamination scenarios.
Thermal comfort: research and practice.
van Hoof, Joost; Mazej, Mitja; Hensen, Jan L M
2010-01-01
Thermal comfort--the state of mind, which expresses satisfaction with the thermal environment--is an important aspect of the building design process as modern man spends most of the day indoors. This paper reviews the developments in indoor thermal comfort research and practice since the second half of the 1990s, and groups these developments around two main themes; (i) thermal comfort models and standards, and (ii) advances in computerization. Within the first theme, the PMV-model (Predicted Mean Vote), created by Fanger in the late 1960s is discussed in the light of the emergence of models of adaptive thermal comfort. The adaptive models are based on adaptive opportunities of occupants and are related to options of personal control of the indoor climate and psychology and performance. Both models have been considered in the latest round of thermal comfort standard revisions. The second theme focuses on the ever increasing role played by computerization in thermal comfort research and practice, including sophisticated multi-segmental modeling and building performance simulation, transient thermal conditions and interactions, thermal manikins.
Indoor Modelling from Slam-Based Laser Scanner: Door Detection to Envelope Reconstruction
NASA Astrophysics Data System (ADS)
Díaz-Vilariño, L.; Verbree, E.; Zlatanova, S.; Diakité, A.
2017-09-01
Updated and detailed indoor models are being increasingly demanded for various applications such as emergency management or navigational assistance. The consolidation of new portable and mobile acquisition systems has led to a higher availability of 3D point cloud data from indoors. In this work, we explore the combined use of point clouds and trajectories from SLAM-based laser scanner to automate the reconstruction of building indoors. The methodology starts by door detection, since doors represent transitions from one indoor space to other, which constitutes an initial approach about the global configuration of the point cloud into building rooms. For this purpose, the trajectory is used to create a vertical point cloud profile in which doors are detected as local minimum of vertical distances. As point cloud and trajectory are related by time stamp, this feature is used to subdivide the point cloud into subspaces according to the location of the doors. The correspondence between subspaces and building rooms is not unambiguous. One subspace always corresponds to one room, but one room is not necessarily depicted by just one subspace, for example, in case of a room containing several doors and in which the acquisition is performed in a discontinue way. The labelling problem is formulated as combinatorial approach solved as a minimum energy optimization. Once the point cloud is subdivided into building rooms, envelop (conformed by walls, ceilings and floors) is reconstructed for each space. The connectivity between spaces is included by adding the previously detected doors to the reconstructed model. The methodology is tested in a real case study.
Rostami, Ali A; Pithawalla, Yezdi B; Liu, Jianmin; Oldham, Michael J; Wagner, Karl A; Frost-Pineda, Kimberly; Sarkar, Mohamadi A
2016-08-16
Concerns have been raised in the literature for the potential of secondhand exposure from e-vapor product (EVP) use. It would be difficult to experimentally determine the impact of various factors on secondhand exposure including, but not limited to, room characteristics (indoor space size, ventilation rate), device specifications (aerosol mass delivery, e-liquid composition), and use behavior (number of users and usage frequency). Therefore, a well-mixed computational model was developed to estimate the indoor levels of constituents from EVPs under a variety of conditions. The model is based on physical and thermodynamic interactions between aerosol, vapor, and air, similar to indoor air models referred to by the Environmental Protection Agency. The model results agree well with measured indoor air levels of nicotine from two sources: smoking machine-generated aerosol and aerosol exhaled from EVP use. Sensitivity analysis indicated that increasing air exchange rate reduces room air level of constituents, as more material is carried away. The effect of the amount of aerosol released into the space due to variability in exhalation was also evaluated. The model can estimate the room air level of constituents as a function of time, which may be used to assess the level of non-user exposure over time.
Hodas, Natasha; Meng, Qingyu; Lunden, Melissa M.; Turpin, Barbara J.
2014-01-01
Because people spend the majority of their time indoors, the variable efficiency with which ambient PM2.5 penetrates and persists indoors is a source of error in epidemiologic studies that use PM2.5 concentrations measured at central-site monitors as surrogates for ambient PM2.5 exposure. To reduce this error, practical methods to model indoor concentrations of ambient PM2.5 are needed. Toward this goal, we evaluated and refined an outdoor-to-indoor transport model using measured indoor and outdoor PM2.5 species concentrations and air exchange rates from the Relationships of Indoor, Outdoor, and Personal Air Study. Herein, we present model evaluation results, discuss what data are most critical to prediction of residential exposures at the individual-subject and populations levels, and make recommendations for the application of the model in epidemiologic studies. This paper demonstrates that not accounting for certain human activities (air conditioning and heating use, opening windows) leads to bias in predicted residential PM2.5 exposures at the individual-subject level, but not the population level. The analyses presented also provide quantitative evidence that shifts in the gas-particle partitioning of ambient organics with outdoor-to-indoor transport contribute significantly to variability in indoor ambient organic carbon concentrations and suggest that methods to account for these shifts will further improve the accuracy of outdoor-to-indoor transport models. PMID:25798047
NASA Astrophysics Data System (ADS)
Li, C.; Zhu, X.; Guo, W.; Liu, Y.; Huang, H.
2015-05-01
A method suitable for indoor complex semantic query considering the computation of indoor spatial relations is provided According to the characteristics of indoor space. This paper designs ontology model describing the space related information of humans, events and Indoor space objects (e.g. Storey and Room) as well as their relations to meet the indoor semantic query. The ontology concepts are used in IndoorSPARQL query language which extends SPARQL syntax for representing and querying indoor space. And four types specific primitives for indoor query, "Adjacent", "Opposite", "Vertical" and "Contain", are defined as query functions in IndoorSPARQL used to support quantitative spatial computations. Also a method is proposed to analysis the query language. Finally this paper adopts this method to realize indoor semantic query on the study area through constructing the ontology model for the study building. The experimental results show that the method proposed in this paper can effectively support complex indoor space semantic query.
Equivalent ZF precoding scheme for downlink indoor MU-MIMO VLC systems
NASA Astrophysics Data System (ADS)
Fan, YangYu; Zhao, Qiong; Kang, BoChao; Deng, LiJun
2018-01-01
In indoor visible light communication (VLC) systems, the channels of photo detectors (PDs) at one user are highly correlated, which determines the choice of spatial diversity model for individual users. In a spatial diversity model, the signals received by PDs belonging to one user carry the same information, and can be combined directly. Based on the above, we propose an equivalent zero-forcing (ZF) precoding scheme for multiple-user multiple-input single-output (MU-MIMO) VLC systems by transforming an indoor MU-MIMO VLC system into an indoor multiple-user multiple-input single-output (MU-MISO) VLC system through simply processing. The power constraints of light emitting diodes (LEDs) are also taken into account. Comprehensive computer simulations in three scenarios indicate that our scheme can not only reduce the computational complexity, but also guarantee the system performance. Furthermore, the proposed scheme does not require noise information in the calculating of the precoding weights, and has no restrictions on the numbers of APs and PDs.
Guxens, Mònica; Vermeulen, Roel; van Eijsden, Manon; Beekhuizen, Johan; Vrijkotte, Tanja G M; van Strien, Rob T; Kromhout, Hans; Huss, Anke
2016-10-01
Little is known about the exposure of young children to radiofrequency electromagnetic fields (RF-EMF) and potentially associated health effects. We assessed the relationship between residential RF-EMF exposure from mobile phone base stations, residential presence of indoor sources, personal cell phone and cordless phone use, and children's cognitive function at 5-6 years of age. Cross-sectional study on children aged 5-6 years from the Amsterdam Born Children and their Development (ABCD) study, the Netherlands (n=2354). Residential RF-EMF exposure from mobile phone base stations was estimated with a 3D geospatial radio wave propagation model. Residential presence of indoor sources (cordless phone base stations and Wi-Fi) and children's cell phone and cordless phone use was reported by the mother. Speed of information processing, inhibitory control, cognitive flexibility, and visuomotor coordination was assessed using the Amsterdam Neuropsychological Tasks. Residential presence of RF-EMF indoor sources was associated with an improved speed of information processing. Higher residential RF-EMF exposure from mobile phone base stations and presence of indoor sources was associated with an improved inhibitory control and cognitive flexibility whereas we observed a reduced inhibitory control and cognitive flexibility with higher personal cordless phone use. Higher residential RF-EMF exposure from mobile phone base stations was associated with a reduced visuomotor coordination whereas we observed an improved visuomotor coordination with residential presence of RF-EMF indoor sources and higher personal cell phone use. We found inconsistent associations between different sources of RF-EMF exposure and cognitive function in children aged 5-6 years. Copyright © 2016 Elsevier Inc. All rights reserved.
Daraktchieva, Z
2017-06-01
Indoor radon concentrations generally vary with season. Radon gas enters buildings from beneath due to a small air pressure difference between the inside of a house and outdoors. This underpressure which draws soil gas including radon into the house depends on the difference between the indoor and outdoor temperatures. The variation in a typical house in UK showed that the mean indoor radon concentration reaches a maximum in January and a minimum in July. Sine functions were used to model the indoor radon data and monthly average outdoor temperatures, covering the period between 2005 and 2014. The analysis showed a strong negative correlation between the modelled indoor radon data and outdoor temperature. This correlation was used to calculate new correction factors that could be used for estimation of annual radon concentration in UK homes. The comparison between the results obtained with the new correction factors and the previously published correction factors showed that the new correction factors perform consistently better on the selected data sets. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
The Effects of Workplace Clean Indoor Air Law Coverage on Workers' Smoking-Related Outcomes.
Cheng, Kai-Wen; Liu, Feng; Gonzalez, MariaElena; Glantz, Stanton
2017-02-01
This study investigated the effects of workplace clean indoor air law (CIAL) coverage on worksite compliance with CIALs, smoking participation among indoor workers, and secondhand smoke (SHS) exposure among nonsmoker indoor workers. This study improved on previous research by using the probability of a resident in a county covered by workplace CIALs, taking into account the state, county, and city legislation. The county-level probability of being covered by a CIAL is merged into two large nationally representative US surveys on smoking behaviors: Tobacco Use Supplement of the Current Population Survey (2001-2010) and Behavioral Risk Factor Surveillance System (2000-2006) based on the year of the survey and respondent's geographic location to identify respondents' CIAL coverage. This study estimated several model specifications of including and not including state or county fixed effects, and the effects of workplace CIALs are consistent across models. Increased coverage by workplace CIALs significantly increased likelihood of reporting a complete smoking restriction by 8% and 10% for the two different datasets, decreased smoking participation among indoor workers by 12%, and decreased SHS exposure among nonsmokers by 28%. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Shin, Hyeong-Moo; McKone, Thomas E.; Nishioka, Marcia G.; Fallin, M. Daniele; Croen, Lisa A.; Hertz-Picciotto, Irva; Newschaffer, Craig J.; Bennett, Deborah H.
2014-01-01
Consumer products and building materials emit a number of semivolatile organic compounds (SVOCs) in the indoor environment. Because indoor SVOCs accumulate in dust, we explore the use of dust to determine source strength and report here on analysis of dust samples collected in 30 U.S. homes for six phthalates, four personal care product ingredients, and five flame retardants. We then use a fugacity-based indoor mass-balance model to estimate the whole house emission rates of SVOCs that would account for the measured dust concentrations. Di-2-ethylhexyl phthalate (DEHP) and di-iso-nonyl phthalate (DiNP) were the most abundant compounds in these dust samples. On the other hand, the estimated emission rate of diethyl phthalate (DEP) is the largest among phthalates, although its dust concentration is over two orders of magnitude smaller than DEHP and DiNP. The magnitude of the estimated emission rate that corresponds to the measured dust concentration is found to be inversely correlated with the vapor pressure of the compound, indicating that dust concentrations alone cannot be used to determine which compounds have the greatest emission rates. The combined dust-assay modeling approach shows promise for estimating indoor emission rates for SVOCs. PMID:24118221
The Effects of Workplace Clean Indoor Air Law Coverage on Workers’ Smoking-Related Outcomes
Cheng, Kai-Wen; Liu, Feng; Gonzalez, MariaElena; Glantz, Stanton
2015-01-01
This study investigated the effects of workplace clean indoor air law (CIAL) coverage on worksite compliance with CIALs, smoking participation among indoor workers, and secondhand smoke (SHS) exposure among non-smoker indoor workers. This study improved on previous research by using the probability of a resident in a county covered by workplace CIALs taking into account the state, county, and city legislation. The county-level probability of being covered by a CIAL is merged into two large nationally representative US surveys on smoking behaviors: Tobacco Use Supplement of the Current Population Survey (2001–2010) and Behavioral Risk Factor Surveillance System (2000–2006) based on the year of the survey and respondent’s geographic location to identify respondents’ CIAL coverage. This study estimated several model specifications of including and not including state or county fixed effects, and the effects of workplace CIALs are consistent across models. Increased coverage by workplace CIALs significantly increased likelihood of reporting a complete smoking restriction by 8% and 10% for the two different datasets, decreased smoking participation among indoor workers by 12%, and decreased SHS exposure among non-smokers by 28%. PMID:26639369
Fabian, Maria Patricia; Adamkiewicz, Gary; Stout, Natasha Kay; Sandel, Megan; Levy, Jonathan Ian
2014-01-01
Although indoor environmental conditions can affect pediatric asthmatic patients, few studies have characterized the effect of building interventions on asthma-related outcomes. Simulation models can evaluate such complex systems but have not been applied in this context. We sought to evaluate the impact of building interventions on indoor environmental quality and pediatric asthma health care use, and to conduct cost comparisons between intervention and health care costs and energy savings. We applied our previously developed discrete event simulation model (DEM) to simulate the effect of environmental factors, medication compliance, seasonality, and medical history on (1) pollutant concentrations indoors and (2) asthma outcomes in low-income multifamily housing. We estimated health care use and costs at baseline and subsequent to interventions, and then compared health care costs with energy savings and intervention costs. Interventions, such as integrated pest management and repairing kitchen exhaust fans, led to 7% to 12% reductions in serious asthma events with 1- to 3-year payback periods. Weatherization efforts targeted solely toward tightening a building envelope led to 20% more serious asthma events, but bundling with repairing kitchen exhaust fans and eliminating indoor sources (eg, gas stoves or smokers) mitigated this effect. Our pediatric asthma model provides a tool to prioritize individual and bundled building interventions based on their effects on health and costs, highlighting the tradeoffs between weatherization, indoor air quality, and health. Our work bridges the gap between clinical and environmental health sciences by increasing physicians' understanding of the effect that home environmental changes can have on their patients' asthma. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.
Fan, Qigao; Wu, Yaheng; Hui, Jing; Wu, Lei; Yu, Zhenzhong; Zhou, Lijuan
2014-01-01
In some GPS failure conditions, positioning for mobile target is difficult. This paper proposed a new method based on INS/UWB for attitude angle and position synchronous tracking of indoor carrier. Firstly, error model of INS/UWB integrated system is built, including error equation of INS and UWB. And combined filtering model of INS/UWB is researched. Simulation results show that the two subsystems are complementary. Secondly, integrated navigation data fusion strategy of INS/UWB based on Kalman filtering theory is proposed. Simulation results show that FAKF method is better than the conventional Kalman filtering. Finally, an indoor experiment platform is established to verify the integrated navigation theory of INS/UWB, which is geared to the needs of coal mine working environment. Static and dynamic positioning results show that the INS/UWB integrated navigation system is stable and real-time, positioning precision meets the requirements of working condition and is better than any independent subsystem.
Neural computing thermal comfort index PMV for the indoor environment intelligent control system
NASA Astrophysics Data System (ADS)
Liu, Chang; Chen, Yifei
2013-03-01
Providing indoor thermal comfort and saving energy are two main goals of indoor environmental control system. An intelligent comfort control system by combining the intelligent control and minimum power control strategies for the indoor environment is presented in this paper. In the system, for realizing the comfort control, the predicted mean vote (PMV) is designed as the control goal, and with chastening formulas of PMV, it is controlled to optimize for improving indoor comfort lever by considering six comfort related variables. On the other hand, a RBF neural network based on genetic algorithm is designed to calculate PMV for better performance and overcoming the nonlinear feature of the PMV calculation better. The formulas given in the paper are presented for calculating the expected output values basing on the input samples, and the RBF network model is trained depending on input samples and the expected output values. The simulation result is proved that the design of the intelligent calculation method is valid. Moreover, this method has a lot of advancements such as high precision, fast dynamic response and good system performance are reached, it can be used in practice with requested calculating error.
Ryan, Patrick H; Brokamp, Cole; Fan, Zhi-Hua; Rao, M B
2015-12-01
The complex mixture of chemicals and elements that constitute particulate matter (PM*) varies by season and geographic location because source contributors differ over time and place. The composition of PM having an aerodynamic diameter < 2.5 μm (PM2.5) is hypothesized to be responsible, in part, for its toxicity. Epidemiologic studies have identified specific components and sources of PM2.5 that are associated with adverse health outcomes. The majority of these studies use measures of outdoor concentrations obtained from one or a few central monitoring sites as a surrogate for measures of personal exposure. Personal PM2.5 (and its elemental composition), however, may be different from the PM2.5 measured at stationary outdoor sites. The objectives of this study were (1) to describe the relationships between the concentrations of various elements in indoor, outdoor, and personal PM2.5 samples, (2) to identify groups of individuals with similar exposures to mixtures of elements in personal PM2.5 and to examine personal and home characteristics of these groups, and (3) to evaluate whether concentrations of elements from outdoor PM2.5 samples are appropriate surrogates for personal exposure to PM2.5 and its elements and whether indoor PM2.5 concentrations and information about home characteristics improve the prediction of personal exposure. The objectives of the study were addressed using data collected as part of the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study. The RIOPA study has previously measured the mass concentrations of PM2.5 and its elemental constituents during 48-hour concurrent indoor, outdoor (directly outside the home), and personal samplings in three urban areas (Los Angeles, California; Houston, Texas; and Elizabeth, New Jersey). The resulting data and information about personal and home characteristics (including air-conditioning use, nearby emission sources, time spent indoors, census-tract geography, air-exchange rates, and other information) for each RIOPA participant were downloaded from the RIOPA study database. We performed three sets of analyses to address the study aims. First, we conducted descriptive analyses to describe the relationships between elemental concentrations in the concurrently gathered indoor, outdoor, and personal air samples. We assessed the correlation between personal exposure and indoor concentrations as well as personal exposure and outdoor concentrations of each element and calculated ratios between them. In addition, we performed principal component analysis (PCA) and calculated principal component scores (PCSs) to examine the heterogeneity of the elemental composition and then tested whether the mixture of elements in indoor, outdoor, and personal PM2.5 was significantly different within each study site and across study sites. Secondly, we performed model-based clustering analysis to group RIOPA participants with similar exposures to mixtures of elements in personal PM2.5. We examined the association between cluster membership and the concentrations of elements in indoor and outdoor PM2.5 samples and personal and home characteristics. Finally, we developed a series of linear regression models and random forest models to examine the association between personal exposure to elements in PM2.5 and (1) outdoor measurements, (2) outdoor and indoor measurements, and (3) outdoor and indoor measurements and home characteristics. As we developed each model, the improvement in prediction of personal exposure when including additional information was assessed. Personal exposures to PM2.5 and to most elements were significantly correlated with both indoor and outdoor concentrations, although concentrations in personal samples frequently exceeded those of indoor and outdoor samples. In general, for most PM2.5 elements indoor concentrations were more highly correlated with personal exposure than were outdoor concentrations. PCA showed that the mixture of elements in indoor, outdoor, and personal PM2.5 varied significantly across sample types within each study site and also across study sites within each sample type. Using model-based clustering, we identified seven clusters of RIOPA participants whose personal PM2.5 samples had similar patterns of elemental composition. Using this approach, subsets of RIOPA participants were identified whose personal exposures to PM2.5 (and its elements) were significantly higher than their indoor and outdoor concentrations (and vice versa). The results of linear and random forest regression models were consistent with our correlation analyses and demonstrated that (1) indoor concentrations were more significantly associated with personal exposure than were outdoor concentrations and (2) participant reports of time spent at their home significantly modified many of the associations between indoor and personal concentrations. In linear regression models, the inclusion of indoor concentrations significantly improved the prediction of personal exposures to Ba, Ca, Cl, Cu, K, Sn, Sr, V, and Zn compared with the use of outdoor elemental concentrations alone. Including additional information on personal and home characteristics improved the prediction for only one element, Pb. Our results support the use of outdoor monitoring sites as surrogates of personal exposure for a limited number of individual elements associated with long-range transport and with a few local or indoor sources. Based on our PCA and clustering analyses, we concluded that the overall elemental composition of PM2.5 obtained at outdoor monitoring sites may not accurately represent the elemental composition of personal PM2.5. Although the data used in these analyses compared outdoor PM2.5 composition collected at the home with indoor and personal samples, our results imply that studies examining the complete elemental composition of PM2.5 should be cautious about using data from central outdoor monitoring sites because of the potential for exposure misclassification. The inclusion of personal and home characteristics only marginally improved the prediction of personal exposure for a small number of elements in PM2.5. We concluded that the additional cost and burden of indoor and personal sampling may be justified for studies examining elements because neither outdoor monitoring nor questionnaire data on home and personal characteristics were able to represent adequately the overall elemental composition of personal PM2.5.
Contribution of indoor and outdoor nitrogen dioxide to indoor air quality of wayside shops.
Shuai, Jianfei; Yang, Wonho; Ahn, Hogi; Kim, Sunshin; Lee, Seokyong; Yoon, Sung-Uk
2013-06-01
Indoor nitrogen dioxide (NO₂) concentration is an important factor for personal exposure despite the wide distribution of its sources. Exposure to NO₂ may produce adverse health effects. The aims of this study were to characterize the indoor air quality of wayside shops using multiple NO₂ measurements, and to estimate the contribution of outdoor NO₂ sources such as vehicle emission to indoor air quality. Daily indoor and outdoor NO₂ concentrations were measured for 21 consecutive days in wayside shops (5 convenience stores, 5 coffee shops, and 5 restaurants). Contributions of outdoor NO₂ sources to indoor air quality were calculated with penetration factors and source strength factors by indoor mass balance model in winter and summer, respectively. Most wayside shops had significant differences in indoor and outdoor NO₂ concentrations both in winter and in summer. Indoor NO₂ concentrations in restaurants were twice more than those in convenience stores and coffee shops in winter. While outdoor NO₂ contributions in indoor convenience stores and coffee shops were dominant, indoor NO₂ contributions were dominant in restaurants. These could be explained that indoor NO₂ sources such as gas range and smoking mainly affect indoor concentrations comparing to outdoor sources such as vehicle emission. The indoor mass balance model by multiple measurements suggests that quantitative contribution of outdoor air on indoor air quality might be estimated without measurements of ventilation, indoor generation and decay rate.
Quantitative health impact of indoor radon in France.
Ajrouche, Roula; Roudier, Candice; Cléro, Enora; Ielsch, Géraldine; Gay, Didier; Guillevic, Jérôme; Marant Micallef, Claire; Vacquier, Blandine; Le Tertre, Alain; Laurier, Dominique
2018-05-08
Radon is the second leading cause of lung cancer after smoking. Since the previous quantitative risk assessment of indoor radon conducted in France, input data have changed such as, estimates of indoor radon concentrations, lung cancer rates and the prevalence of tobacco consumption. The aim of this work was to update the risk assessment of lung cancer mortality attributable to indoor radon in France using recent risk models and data, improving the consideration of smoking, and providing results at a fine geographical scale. The data used were population data (2012), vital statistics on death from lung cancer (2008-2012), domestic radon exposure from a recent database that combines measurement results of indoor radon concentration and the geogenic radon potential map for France (2015), and smoking prevalence (2010). The risk model used was derived from a European epidemiological study, considering that lung cancer risk increased by 16% per 100 becquerels per cubic meter (Bq/m 3 ) indoor radon concentration. The estimated number of lung cancer deaths attributable to indoor radon exposure is about 3000 (1000; 5000), which corresponds to about 10% of all lung cancer deaths each year in France. About 33% of lung cancer deaths attributable to radon are due to exposure levels above 100 Bq/m 3 . Considering the combined effect of tobacco and radon, the study shows that 75% of estimated radon-attributable lung cancer deaths occur among current smokers, 20% among ex-smokers and 5% among never-smokers. It is concluded that the results of this study, which are based on precise estimates of indoor radon concentrations at finest geographical scale, can serve as a basis for defining French policy against radon risk.
Good practices in managing work-related indoor air problems: a psychosocial perspective.
Lahtinen, Marjaana; Huuhtanen, Pekka; Vähämäki, Kari; Kähkönen, Erkki; Mussalo-Rauhamaa, Helena; Reijula, Kari
2004-07-01
Indoor air problems at workplaces are often exceedingly complex. Technical questions are interrelated with the dynamics of the work community, and the cooperation and interaction skills of the parties involved in the problem solving process are also put to the test. The objective of our study was to analyze the process of managing and solving indoor air problems from a psychosocial perspective. This collective case study was based on data from questionnaires, interviews and various documentary materials. Technical inspections of the buildings and indoor air measurements were also carried out. The following four factors best differentiated successful cases from impeded cases: extensive multiprofessional collaboration and participative action, systematic action and perseverance, investment in information and communication, and process thinking and learning. The study also proposed a theoretical model for the role of the psychosocial work environment in indoor air problems. The expertise related to social and human aspects of problem solving plays a significant role in solving indoor air problems. Failures to properly handle these aspects may lead to resources being wasted and result in a problematic situation becoming stagnant or worse. Copyright 2004 Wiley-Liss, Inc.
Indoor Air Quality Building Education and Assessment Model Forms
The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
Challoner, Avril; Pilla, Francesco; Gill, Laurence
2015-12-01
NO₂ and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person's well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO₂ indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO₂ exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts.
Information on human behavior and consumer product use is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure-assessors have relied on time-use surveys to obtain information on exposure-related behavior. In ...
Zhou, Bin; Zhao, Bin
2014-01-01
It is difficult to evaluate and compare interventions for reducing exposure to air pollutants, including polycyclic aromatic hydrocarbons (PAHs), a widely found air pollutant in both indoor and outdoor air. This study presents the first application of the Monte Carlo population exposure assessment model to quantify the effects of different intervention strategies on inhalation exposure to PAHs and the associated lung cancer risk. The method was applied to the population in Beijing, China, in the year 2006. Several intervention strategies were designed and studied, including atmospheric cleaning, smoking prohibition indoors, use of clean fuel for cooking, enhancing ventilation while cooking and use of indoor cleaners. Their performances were quantified by population attributable fraction (PAF) and potential impact fraction (PIF) of lung cancer risk, and the changes in indoor PAH concentrations and annual inhalation doses were also calculated and compared. The results showed that atmospheric cleaning and use of indoor cleaners were the two most effective interventions. The sensitivity analysis showed that several input parameters had major influence on the modeled PAH inhalation exposure and the rankings of different interventions. The ranking was reasonably robust for the remaining majority of parameters. The method itself can be extended to other pollutants and in different places. It enables the quantitative comparison of different intervention strategies and would benefit intervention design and relevant policy making.
Inverse modeling methods for indoor airborne pollutant tracking: literature review and fundamentals.
Liu, X; Zhai, Z
2007-12-01
Reduction in indoor environment quality calls for effective control and improvement measures. Accurate and prompt identification of contaminant sources ensures that they can be quickly removed and contaminated spaces isolated and cleaned. This paper discusses the use of inverse modeling to identify potential indoor pollutant sources with limited pollutant sensor data. The study reviews various inverse modeling methods for advection-dispersion problems and summarizes the methods into three major categories: forward, backward, and probability inverse modeling methods. The adjoint probability inverse modeling method is indicated as an appropriate model for indoor air pollutant tracking because it can quickly find source location, strength and release time without prior information. The paper introduces the principles of the adjoint probability method and establishes the corresponding adjoint equations for both multi-zone airflow models and computational fluid dynamics (CFD) models. The study proposes a two-stage inverse modeling approach integrating both multi-zone and CFD models, which can provide a rapid estimate of indoor pollution status and history for a whole building. Preliminary case study results indicate that the adjoint probability method is feasible for indoor pollutant inverse modeling. The proposed method can help identify contaminant source characteristics (location and release time) with limited sensor outputs. This will ensure an effective and prompt execution of building management strategies and thus achieve a healthy and safe indoor environment. The method can also help design optimal sensor networks.
Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing o...
Emission models developed using small chamber data were combined with an Indoor Air Quality (IAQ) model to analyze the impact of volatile organic compound (VOC) emissions from latex paint on indoor environments. Test house experiments were conducted to verify the IAQ model's pred...
Indoor Air Quality Building Education and Assessment Model
The Indoor Air Quality Building Education and Assessment Model (I-BEAM), released in 2002, is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
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The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
Bibliography for the Indoor Air Quality Building Education and Assessment Model
The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
NASA Astrophysics Data System (ADS)
Giuseppina, Nicolosi; Salvatore, Tirrito
2015-12-01
Wireless Sensor Networks (WSNs) were studied by researchers in order to manage Heating, Ventilating and Air-Conditioning (HVAC) indoor systems. WSN can be useful specially to regulate indoor confort in a urban canyon scenario, where the thermal parameters vary rapidly, influenced by outdoor climate changing. This paper shows an innovative neural network approach, by using WSN data collected, in order to forecast the indoor temperature to varying the outdoor conditions based on climate parameters and boundary conditions typically of urban canyon. In this work more attention will be done to influence of traffic jam and number of vehicles in queue.
Improving IMES Localization Accuracy by Integrating Dead Reckoning Information
Fujii, Kenjiro; Arie, Hiroaki; Wang, Wei; Kaneko, Yuto; Sakamoto, Yoshihiro; Schmitz, Alexander; Sugano, Shigeki
2016-01-01
Indoor positioning remains an open problem, because it is difficult to achieve satisfactory accuracy within an indoor environment using current radio-based localization technology. In this study, we investigate the use of Indoor Messaging System (IMES) radio for high-accuracy indoor positioning. A hybrid positioning method combining IMES radio strength information and pedestrian dead reckoning information is proposed in order to improve IMES localization accuracy. For understanding the carrier noise ratio versus distance relation for IMES radio, the signal propagation of IMES radio is modeled and identified. Then, trilateration and extended Kalman filtering methods using the radio propagation model are developed for position estimation. These methods are evaluated through robot localization and pedestrian localization experiments. The experimental results show that the proposed hybrid positioning method achieved average estimation errors of 217 and 1846 mm in robot localization and pedestrian localization, respectively. In addition, in order to examine the reason for the positioning accuracy of pedestrian localization being much lower than that of robot localization, the influence of the human body on the radio propagation is experimentally evaluated. The result suggests that the influence of the human body can be modeled. PMID:26828492
Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin
2016-01-01
With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053
Challenges in Flying Quadrotor Unmanned Aerial Vehicle for 3d Indoor Reconstruction
NASA Astrophysics Data System (ADS)
Yan, J.; Grasso, N.; Zlatanova, S.; Braggaar, R. C.; Marx, D. B.
2017-09-01
Three-dimensional modelling plays a vital role in indoor 3D tracking, navigation, guidance and emergency evacuation. Reconstruction of indoor 3D models is still problematic, in part, because indoor spaces provide challenges less-documented than their outdoor counterparts. Challenges include obstacles curtailing image and point cloud capture, restricted accessibility and a wide array of indoor objects, each with unique semantics. Reconstruction of indoor environments can be achieved through a photogrammetric approach, e.g. by using image frames, aligned using recurring corresponding image points (CIP) to build coloured point clouds. Our experiments were conducted by flying a QUAV in three indoor environments and later reconstructing 3D models which were analysed under different conditions. Point clouds and meshes were created using Agisoft PhotoScan Professional. We concentrated on flight paths from two vantage points: 1) safety and security while flying indoors and 2) data collection needed for reconstruction of 3D models. We surmised that the main challenges in providing safe flight paths are related to the physical configuration of indoor environments, privacy issues, the presence of people and light conditions. We observed that the quality of recorded video used for 3D reconstruction has a high dependency on surface materials, wall textures and object types being reconstructed. Our results show that 3D indoor reconstruction predicated on video capture using a QUAV is indeed feasible, but close attention should be paid to flight paths and conditions ultimately influencing the quality of 3D models. Moreover, it should be decided in advance which objects need to be reconstructed, e.g. bare rooms or detailed furniture.
A malaria transmission-directed model of mosquito life cycle and ecology
2011-01-01
Background Malaria is a major public health issue in much of the world, and the mosquito vectors which drive transmission are key targets for interventions. Mathematical models for planning malaria eradication benefit from detailed representations of local mosquito populations, their natural dynamics and their response to campaign pressures. Methods A new model is presented for mosquito population dynamics, effects of weather, and impacts of multiple simultaneous interventions. This model is then embedded in a large-scale individual-based simulation and results for local elimination of malaria are discussed. Mosquito population behaviours, such as anthropophily and indoor feeding, are included to study their effect upon the efficacy of vector control-based elimination campaigns. Results Results for vector control tools, such as bed nets, indoor spraying, larval control and space spraying, both alone and in combination, are displayed for a single-location simulation with vector species and seasonality characteristic of central Tanzania, varying baseline transmission intensity and vector bionomics. The sensitivities to habitat type, anthropophily, indoor feeding, and baseline transmission intensity are explored. Conclusions The ability to model a spectrum of local vector species with different ecologies and behaviours allows local customization of packages of interventions and exploration of the effect of proposed new tools. PMID:21999664
Residential air exchange rates (AERs) are a key determinant in the infiltration of ambient air pollution indoors. Population-based human exposure models using probabilistic approaches to estimate personal exposure to air pollutants have relied on input distributions from AER meas...
An IMU-Aided Body-Shadowing Error Compensation Method for Indoor Bluetooth Positioning
Deng, Zhongliang
2018-01-01
Research on indoor positioning technologies has recently become a hotspot because of the huge social and economic potential of indoor location-based services (ILBS). Wireless positioning signals have a considerable attenuation in received signal strength (RSS) when transmitting through human bodies, which would cause significant ranging and positioning errors in RSS-based systems. This paper mainly focuses on the body-shadowing impairment of RSS-based ranging and positioning, and derives a mathematical expression of the relation between the body-shadowing effect and the positioning error. In addition, an inertial measurement unit-aided (IMU-aided) body-shadowing detection strategy is designed, and an error compensation model is established to mitigate the effect of body-shadowing. A Bluetooth positioning algorithm with body-shadowing error compensation (BP-BEC) is then proposed to improve both the positioning accuracy and the robustness in indoor body-shadowing environments. Experiments are conducted in two indoor test beds, and the performance of both the BP-BEC algorithm and the algorithms without body-shadowing error compensation (named no-BEC) is evaluated. The results show that the BP-BEC outperforms the no-BEC by about 60.1% and 73.6% in terms of positioning accuracy and robustness, respectively. Moreover, the execution time of the BP-BEC algorithm is also evaluated, and results show that the convergence speed of the proposed algorithm has an insignificant effect on real-time localization. PMID:29361718
An IMU-Aided Body-Shadowing Error Compensation Method for Indoor Bluetooth Positioning.
Deng, Zhongliang; Fu, Xiao; Wang, Hanhua
2018-01-20
Research on indoor positioning technologies has recently become a hotspot because of the huge social and economic potential of indoor location-based services (ILBS). Wireless positioning signals have a considerable attenuation in received signal strength (RSS) when transmitting through human bodies, which would cause significant ranging and positioning errors in RSS-based systems. This paper mainly focuses on the body-shadowing impairment of RSS-based ranging and positioning, and derives a mathematical expression of the relation between the body-shadowing effect and the positioning error. In addition, an inertial measurement unit-aided (IMU-aided) body-shadowing detection strategy is designed, and an error compensation model is established to mitigate the effect of body-shadowing. A Bluetooth positioning algorithm with body-shadowing error compensation (BP-BEC) is then proposed to improve both the positioning accuracy and the robustness in indoor body-shadowing environments. Experiments are conducted in two indoor test beds, and the performance of both the BP-BEC algorithm and the algorithms without body-shadowing error compensation (named no-BEC) is evaluated. The results show that the BP-BEC outperforms the no-BEC by about 60.1% and 73.6% in terms of positioning accuracy and robustness, respectively. Moreover, the execution time of the BP-BEC algorithm is also evaluated, and results show that the convergence speed of the proposed algorithm has an insignificant effect on real-time localization.
Challoner, Avril; Pilla, Francesco; Gill, Laurence
2015-01-01
NO2 and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person’s well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO2 indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO2 exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts. PMID:26633448
Bim-Based Indoor Path Planning Considering Obstacles
NASA Astrophysics Data System (ADS)
Xu, M.; Wei, S.; Zlatanova, S.; Zhang, R.
2017-09-01
At present, 87 % of people's activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people's daily life are more and more complex, many obstacles influence humans' moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC) as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.
Wei, Wenjuan; Mandin, Corinne; Ramalho, Olivier
2018-03-01
Semi-volatile organic compounds (SVOCs) in indoor environments can partition among the gas phase, airborne particles, settled dust, and available surfaces. The mass transfer parameters of SVOCs, such as the mass transfer coefficient and the partition coefficient, are influenced by indoor environmental factors. Subsequently, indoor SVOC concentrations and thus occupant exposure can vary depending on environmental factors. In this review, the influence of six environmental factors, i.e., indoor temperature, humidity, ventilation, airborne particle concentration, source loading factor, and reactive chemistry, on the mass transfer parameters and indoor concentrations of SVOCs was analyzed and tentatively quantified. The results show that all mass transfer parameters vary depending on environmental factors. These variations are mostly characterized by empirical equations, particularly for humidity. Theoretical calculations of these parameters based on mass transfer mechanisms are available only for the emission of SVOCs from source surfaces when airborne particles are not present. All mass transfer parameters depend on the temperature. Humidity influences the partition of SVOCs among different phases and is associated with phthalate hydrolysis. Ventilation has a combined effect with the airborne particle concentration on SVOC emission and their mass transfer among different phases. Indoor chemical reactions can produce or eliminate SVOCs slowly. To better model the dynamic SVOC concentration indoors, the present review suggests studying the combined effect of environmental factors in real indoor environments. Moreover, interactions between indoor environmental factors and human activities and their influence on SVOC mass transfer processes should be considered. Copyright © 2017 Elsevier Ltd. All rights reserved.
Source apportionment of indoor air pollution
NASA Astrophysics Data System (ADS)
Sexton, Ken; Hayward, Steven B.
An understanding of the relative contributions from important pollutant sources to human exposures is necessary for the design and implementation of effective control strategies. In the past, societal efforts to control air pollution have focused almost exclusively on the outdoor (ambient) environment. As a result, substantial amounts of time and money have been spent to limit airborne discharges from mobile and stationary sources. Yet it is now recognized that exposures to elevated pollutant concentrations often occur as a result of indoor, rather than outdoor, emissions. While the major indoor sources have been identified, their relative impacts on indoor air quality have not been well defined. Application of existing source apportionment models to nonindustrial indoor environments is only just beginning. It is possible that these models might be used to distinguish between indoor and outdoor emissions, as well as to distinguish among indoor sources themselves. However, before the feasibility and suitability of source-apportionment methods for indoor applications can be assessed adequately, it is necessary to take account of model assumptions and associated data requirements. This paper examines the issue of indoor source apportionment and reviews the need for emission characterization studies to support such source-apportionment efforts.
A Robust Wireless Sensor Network Localization Algorithm in Mixed LOS/NLOS Scenario.
Li, Bing; Cui, Wei; Wang, Bin
2015-09-16
Localization algorithms based on received signal strength indication (RSSI) are widely used in the field of target localization due to its advantages of convenient application and independent from hardware devices. Unfortunately, the RSSI values are susceptible to fluctuate under the influence of non-line-of-sight (NLOS) in indoor space. Existing algorithms often produce unreliable estimated distances, leading to low accuracy and low effectiveness in indoor target localization. Moreover, these approaches require extra prior knowledge about the propagation model. As such, we focus on the problem of localization in mixed LOS/NLOS scenario and propose a novel localization algorithm: Gaussian mixed model based non-metric Multidimensional (GMDS). In GMDS, the RSSI is estimated using a Gaussian mixed model (GMM). The dissimilarity matrix is built to generate relative coordinates of nodes by a multi-dimensional scaling (MDS) approach. Finally, based on the anchor nodes' actual coordinates and target's relative coordinates, the target's actual coordinates can be computed via coordinate transformation. Our algorithm could perform localization estimation well without being provided with prior knowledge. The experimental verification shows that GMDS effectively reduces NLOS error and is of higher accuracy in indoor mixed LOS/NLOS localization and still remains effective when we extend single NLOS to multiple NLOS.
The influence of mosquito resting behaviour and associated microclimate for malaria risk.
Paaijmans, Krijn P; Thomas, Matthew B
2011-07-07
The majority of the mosquito and parasite life-history traits that combine to determine malaria transmission intensity are temperature sensitive. In most cases, the process-based models used to estimate malaria risk and inform control and prevention strategies utilize measures of mean outdoor temperature. Evidence suggests, however, that certain malaria vectors can spend large parts of their adult life resting indoors. If significant proportions of mosquitoes are resting indoors and indoor conditions differ markedly from ambient conditions, simple use of outdoor temperatures will not provide reliable estimates of malaria transmission intensity. To date, few studies have quantified the differential effects of indoor vs outdoor temperatures explicitly, reflecting a lack of proper understanding of mosquito resting behaviour and associated microclimate. Published records from 8 village sites in East Africa revealed temperatures to be warmer indoors than outdoors and to generally show less daily variation. Exploring the effects of these temperatures on malaria parasite development rate suggested indoor-resting mosquitoes could transmit malaria between 0.3 and 22.5 days earlier than outdoor-resting mosquitoes. These differences translate to increases in transmission risk ranging from 5 to approaching 3,000%, relative to predictions based on outdoor temperatures. The pattern appears robust for low- and highland areas, with differences increasing with altitude. Differences in indoor vs outdoor environments lead to large differences in the limits and the intensity of malaria transmission. This finding highlights a need to better understand mosquito resting behaviour and the associated microclimate, and to broaden assessments of transmission ecology and risk to consider the potentially important role of endophily.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kong, S.H.; Chung, K.S.; Park, J.S.
1999-07-01
Currently, there are many researches on the analysis of indoor environment in Sokkuram Cave Temple. However, there is not enough researches about an experimental study on the dome's indoor environment in Sokkuram Cave Temple using a miniature model. The purpose of this investigation is to measure and analyze characteristics of indoor environment such as relative humidity, dry bulb temperature and air velocity in the miniature model of Sokkuram Cave dome during winter season.
NASA Astrophysics Data System (ADS)
Pahlavani, P.; Gholami, A.; Azimi, S.
2017-09-01
This paper presents an indoor positioning technique based on a multi-layer feed-forward (MLFF) artificial neural networks (ANN). Most of the indoor received signal strength (RSS)-based WLAN positioning systems use the fingerprinting technique that can be divided into two phases: the offline (calibration) phase and the online (estimation) phase. In this paper, RSSs were collected for all references points in four directions and two periods of time (Morning and Evening). Hence, RSS readings were sampled at a regular time interval and specific orientation at each reference point. The proposed ANN based model used Levenberg-Marquardt algorithm for learning and fitting the network to the training data. This RSS readings in all references points and the known position of these references points was prepared for training phase of the proposed MLFF neural network. Eventually, the average positioning error for this network using 30% check and validation data was computed approximately 2.20 meter.
Implementing Green Walls in Schools.
McCullough, Michael B; Martin, Michael D; Sajady, Mollika A
2018-01-01
Numerous studies in applied pedagogical design have shown that, at all educational levels, direct exposure to the natural environment can enhance learning by improving student attention and behaviors. Implementing green walls-a "vertical garden," or "living wall" interior wall that typically includes greenery, a growing medium (soil or substrate) and a water delivery system-provides environmental health benefits, but also provides a practical application within classrooms for minimizing directed attention fatigue in students by connecting them to "outdoor nature" within the indoor environment. Hands-on "project-based" learning is another pedagogical strategy that has proved to be effective across the spectrum of educational levels and across subject areas. Green walls have the potential to inspire critical thinking through a combination of project-based learning strategies and environmental education. The authors have outlined a curriculum involving the implementation of an indoor living wall system within a classroom-learning environment, incorporating project-based learning modules that interact with the wall. In conjunction with the passive health benefits of a green wall, project-based curriculum models can connect students interactively with indoor nature and have the potential to inspire real-world thinking related to science, technology, engineering, art, and mathematics fields within the indoor learning environment. Through a combination of these passive and interactive modes, students are connected to nature in the indoor environment regardless of weather conditions outdoors. Future research direction could include post-construction studies of the effectiveness of project-based curricula related to living walls, and the long-term impacts of implementing green walls in classrooms on school achievement and student behaviors.
Real-time door detection for indoor autonomous vehicle
NASA Astrophysics Data System (ADS)
He, Zhihao; Zhu, Ming
2017-07-01
Indoor Autonomous Vehicle(IAV) is used in many indoor scenes. Such as hotels and hospitals. Door detection is a key issue to guide the IAV into rooms. In this paper, we consider door detection in the use of indoor navigation of IAV. Since real-time properties are important for real-world IAV, the detection algorithm must be fast enough. Most monocular-camera based door detection model need a perfect detection of the four line segments of the door or the four corners. But in many situations, line segments could be extended or cut off. And there could be many false detected corners. And few of them can distinguish doors from door-like objects with door-like shape effectively. We proposed a 2-D vision model of the door that is made up of line segments. The number of parts detected is used to determine the possibility of a door. Our algorithm is tested on a database of doors.1 The robustness and real-time are verified. The precision is 89.4%. Average time consumed for processing a 640x320 figure is 44.73ms.
Huang, Lihui; Mo, Jinhan; Sundell, Jan; Fan, Zhihua; Zhang, Yinping
2013-01-01
Objective To assess health risks associated with inhalation exposure to formaldehyde and benzene mainly emitted from building and decoration materials in newly remodeled indoor spaces in Beijing. Methods We tested the formaldehyde and benzene concentrations in indoor air of 410 dwellings and 451 offices remodeled within the past year, in which the occupants had health concerns about indoor air quality. To assess non-carcinogenic health risks, we compared the data to the health guidelines in China and USA, respectively. To assess carcinogenic health risks, we first modeled indoor personal exposure to formaldehyde and benzene using the concentration data, and then estimated the associated cancer risks by multiplying the indoor personal exposure by the Inhalation Unit Risk values (IURs) provided by the U.S. EPA Integrated Risk Information System (U.S. EPA IRIS) and the California Office of Environmental Health Hazard Assessment (OEHHA), respectively. Results (1) The indoor formaldehyde concentrations of 85% dwellings and 67% offices were above the acute Reference Exposure Level (REL) recommended by the OEHHA and the concentrations of all tested buildings were above the chronic REL recommended by the OEHHA; (2) The indoor benzene concentrations of 12% dwellings and 32% offices exceeded the reference concentration (RfC) recommended by the U.S. EPA IRIS; (3) The median cancer risks from indoor exposure to formaldehyde and benzene were 1,150 and 106 per million (based on U.S. EPA IRIS IURs), 531 and 394 per million (based on OEHHA IURs). Conclusions In the tested buildings, formaldehyde exposure may pose acute and chronic non-carcinogenic health risks to the occupants, whereas benzene exposure may pose chronic non-carcinogenic risks to the occupants. Exposure to both compounds is associated with significant carcinogenic risks. Improvement in ventilation, establishment of volatile organic compounds (VOCs) emission labeling systems for decorating and refurbishing materials are recommended to reduce indoor VOCs exposure. PMID:24244522
MODELING INDOOR CONCENTRATIONS AND EXPOSURE
The paper discusses the use of an indoor air quality model, EXPOSURE, to predict pollutant concentrations and exposures. The effects of indoor air pollutants depend on the concentrations of the pollutants and the exposure of individuals to the pollutants. The air pollutant concen...
Hasheminassab, Sina; Daher, Nancy; Shafer, Martin M.; Schauer, James J.; Delfino, Ralph J.; Sioutas, Constantinos
2014-01-01
Concurrent indoor and outdoor measurements of fine particulate matter (PM2.5) were conducted at three retirement homes in the Los Angeles Basin during two separate phases (cold and warm) between 2005 and 2006. Indoor-to-outdoor relationships of PM2.5 chemical constituents were determined and sources of indoor and outdoor PM2.5 were evaluated using a molecular marker-based chemical mass balance (MM-CMB) model. Indoor levels of elemental carbon (EC) along with metals and trace elements were found to be significantly affected by outdoor sources. EC, in particular, displayed very high indoor-to-outdoor (I/O) mass ratios accompanied by strong I/O correlations, illustrating the significant impact of outdoor sources on indoor levels of EC. Similarly, indoor levels of polycyclic aromatic hydrocarbons (PAHs), hopanes, and steranes were strongly correlated with their outdoor components and displayed I/O ratios close to unity. On the other hand, concentrations of n-alkanes and organic acids inside the retirement communities were dominated by indoor sources (e.g. food cooking and consumer products), as indicated by their I/O ratios, which exceeded unity. Source apportionment results revealed that vehicular emissions were the major contributor to both indoor and outdoor PM2.5, accounting for 39 and 46% of total mass, respectively. Moreover, the contribution of vehicular sources to indoor levels was generally comparable to its corresponding outdoor estimate. Other water-insoluble organic matter (other WIOM), which accounts for emissions from uncharacterized primary biogenic sources, displayed a wider range of contributions, varying from 2 to 73% of PM2.5, across all sites and phases of the study. Lastly, higher indoor than outdoor contribution of other water-soluble organic matter (other WSOM) was evident at some of the sites, suggesting the production of secondary aerosols as well as direct emissions from primary sources (including cleaning or other consumer products) at the indoor environments. PMID:24880542
Wang, Fang; Meng, Dan; Li, Xiuwei; Tan, Junjie
2016-08-01
Indoor and outdoor air PM2.5 concentrations in four residential dwellings characterized with different building envelope air tightness levels and HVAC-filter configurations in Yangtze River Delta (YRD) were measured during winter periods in 2014-2015. Steady-state models for indoor PM2.5 were developed for each of the tested dwellings, based on mass balance equation. The indoor air PM2.5 concentrations in the four tested apartments were significantly different. The lowest geometric mean values of indoor air PM2.5 concentrations, I/O ratios, and infiltration factor were observed in D3 with high air tightness and without HVAC-filter system (26.0 μg/m(3), 0.197, and 0.167, respectively), while the highest geometric mean values of indoor air PM2.5 concentrations, I/O ratios, and infiltration factor were observed in D1 (64.9 μg/m(3), 0.876, and 0.867, respectively). For apartment D1 with normal air tightness and without any HVAC-filter system, indoor air PM2.5 concentrations were significantly correlated with outdoor PM2.5 concentrations, especially in severe ambient pollution days, when closed windows can only play a very weak role on the decline of indoor PM2.5 concentrations. With the enhancement of building air tightness, the indoor air PM2.5 concentrations can be decreased effectively and don't vary as much in response to fluctuations in ambient concentrations. For buildings with normal air tightness, the use of HVAC-filter combinations will decrease the indoor PM2.5 significantly. However, for buildings with enhanced air tightness, the only use of fresh makeup air supply system with filter may increase the indoor PM2.5 concentrations. The improvement of filter efficiency for both fresh makeup air and indoor recirculated air are very important. However, purifiers for indoor recirculated air were highly recommended for all buildings. Copyright © 2016 Elsevier Ltd. All rights reserved.
a Review of Recent Research in Indoor Modelling & Mapping
NASA Astrophysics Data System (ADS)
Gunduz, M.; Isikdag, U.; Basaraner, M.
2016-06-01
Indoor modeling and mapping has been an active area of research in last 20 years in order to tackle the problems related to positioning and tracking of people and objects indoors, and provides many opportunities for several domains ranging from emergency response to logistics in micro urban spaces. The outputs of recent research in the field have been presented in several scientific publications and events primarily related to spatial information science and technology. This paper summarizes the outputs of last 10 years of research on indoor modeling and mapping within a proper classification which covers 7 areas, i.e. Information Acquisition by Sensors, Model Definition, Model Integration, Indoor Positioning and LBS, Routing & Navigation Methods, Augmented and Virtual Reality Applications, and Ethical Issues. Finally, the paper outlines the current and future research directions and concluding remarks.
Fabian, P; Adamkiewicz, G; Levy, J I
2012-02-01
Residents of low-income multifamily housing can have elevated exposures to multiple environmental pollutants known to influence asthma. Simulation models can characterize the health implications of changing indoor concentrations, but quantifying the influence of interventions on concentrations is challenging given complex airflow and source characteristics. In this study, we simulated concentrations in a prototype multifamily building using CONTAM, a multizone airflow and contaminant transport program. Contaminants modeled included PM(2.5) and NO(2) , and parameters included stove use, presence and operability of exhaust fans, smoking, unit level, and building leakiness. We developed regression models to explain variability in CONTAM outputs for individual sources, in a manner that could be utilized in simulation modeling of health outcomes. To evaluate our models, we generated a database of 1000 simulated households with characteristics consistent with Boston public housing developments and residents and compared the predicted levels of NO(2) and PM(2.5) and their correlates with the literature. Our analyses demonstrated that CONTAM outputs could be readily explained by available parameters (R(2) between 0.89 and 0.98 across models), but that one-compartment box models would mischaracterize concentrations and source contributions. Our study quantifies the key drivers for indoor concentrations in multifamily housing and helps to identify opportunities for interventions. Many low-income urban asthmatics live in multifamily housing that may be amenable to ventilation-related interventions such as weatherization or air sealing, wall and ceiling hole repairs, and exhaust fan installation or repair, but such interventions must be designed carefully given their cost and their offsetting effects on energy savings as well as indoor and outdoor pollutants. We developed models to take into account the complex behavior of airflow patterns in multifamily buildings, which can be used to identify and evaluate environmental and non-environmental interventions targeting indoor air pollutants which can trigger asthma exacerbations. © 2011 John Wiley & Sons A/S.
Indoor Thermal Factors and Symptoms in Office Workers: Findings from the U.S. EPA BASE Study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mendell, Mark; Mirer, Anna
2008-06-01
Some prior research in office buildings has associated higher indoor temperatures even within the recommended thermal comfort range with increased worker symptoms. We reexamined this relationship in data from 95 office buildings in the U.S. Environmental Protection Agency's Building Assessment Survey and Evaluation (BASE) Study. We investigated relationships between building-related symptoms and thermal metrics constructed from real-time measurements. We estimated odds ratios (ORs) and 95percent confidence intervals in adjusted logistic regression models with general estimating equations, overall and by season. Winter indoor temperatures spanned the recommended winter comfort range; summer temperatures were mostly colder than the recommended summer range. Increasingmore » indoor temperatures, overall, were associated with increases in few symptoms. Higher winter indoor temperatures, however, were associated with increases in all symptoms analyzed. Higher summer temperatures, above 23oC, were associated with decreases in most symptoms. Humidity ratio, a metric of absolute humidity, showed few clear associations. Thus, increased symptoms with higher temperatures within the thermal comfort range were found only in winter. In summer, buildings were overcooled, and only the higher observed temperatures were within the comfort range; these were associated with decreased symptoms. Confirmation of these findings would suggest that thermal management guidelines consider health effects as well as comfort.« less
The effect of the indoor environment on the fate of organic chemicals in the urban landscape.
Cousins, Anna Palm
2012-11-01
To assess the effect of the indoor environment on the urban fate of organic chemicals, an 8-compartment indoor-inclusive steady state multimedia chemical fate model was developed. The model includes typical urban compartments (air, soil, water, sediment, and urban film) and a novel module representing a generic indoor environment. The model was parameterized to the municipality of Stockholm, Sweden and applied to four organic chemicals with different physical-chemical characteristics and use patterns: formaldehyde, 2,4,6-tribromophenol, di-ethylhexylphthalate and decabromodiphenyl ether. The results show that emissions to indoor air may increase the steady state mass and residence time in the urban environment by a factor of 1.1 to 22 for the four chemicals, compared to if emissions are assigned to outdoor air. This is due to the nested nature of the indoor environment, which creates a physical barrier that prevents chemicals from leaving the urban system with outflowing air. For DEHP and BDE 209, the additional partitioning to indoor surfaces results in a greater importance of the indoor removal pathways from surfaces. The outdoor environmental concentrations of these chemicals are predicted to be lower if emitted to indoor air than if emitted to outdoor air because of the additional indoor removal pathways of dust and indoor film, leading to loss of chemical from the system. For formaldehyde and 2,4,6-TBP outdoor environmental concentrations are not affected by whether the release occurs indoors or outdoors because of the limited partitioning to indoor surfaces. A sensitivity analysis revealed that there appears to be a relationship between logK(OA) and the impact of the ventilation rate on the urban fate of organic chemicals. Copyright © 2012 Elsevier B.V. All rights reserved.
Application of zonal model on indoor air sensor network design
NASA Astrophysics Data System (ADS)
Chen, Y. Lisa; Wen, Jin
2007-04-01
Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.
Zhou, Bin; Zhao, Bin
2014-01-01
It is difficult to evaluate and compare interventions for reducing exposure to air pollutants, including polycyclic aromatic hydrocarbons (PAHs), a widely found air pollutant in both indoor and outdoor air. This study presents the first application of the Monte Carlo population exposure assessment model to quantify the effects of different intervention strategies on inhalation exposure to PAHs and the associated lung cancer risk. The method was applied to the population in Beijing, China, in the year 2006. Several intervention strategies were designed and studied, including atmospheric cleaning, smoking prohibition indoors, use of clean fuel for cooking, enhancing ventilation while cooking and use of indoor cleaners. Their performances were quantified by population attributable fraction (PAF) and potential impact fraction (PIF) of lung cancer risk, and the changes in indoor PAH concentrations and annual inhalation doses were also calculated and compared. The results showed that atmospheric cleaning and use of indoor cleaners were the two most effective interventions. The sensitivity analysis showed that several input parameters had major influence on the modeled PAH inhalation exposure and the rankings of different interventions. The ranking was reasonably robust for the remaining majority of parameters. The method itself can be extended to other pollutants and in different places. It enables the quantitative comparison of different intervention strategies and would benefit intervention design and relevant policy making. PMID:24416436
Liu, Wen; Fu, Xiao; Deng, Zhongliang
2016-12-02
Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.
Liu, Wen; Fu, Xiao; Deng, Zhongliang
2016-01-01
Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means. PMID:27918454
Layout Slam with Model Based Loop Closure for 3d Indoor Corridor Reconstruction
NASA Astrophysics Data System (ADS)
Baligh Jahromi, A.; Sohn, G.; Jung, J.; Shahbazi, M.; Kang, J.
2018-05-01
In this paper, we extend a recently proposed visual Simultaneous Localization and Mapping (SLAM) techniques, known as Layout SLAM, to make it robust against error accumulations, abrupt changes of camera orientation and miss-association of newly visited parts of the scene to the previously visited landmarks. To do so, we present a novel technique of loop closing based on layout model matching; i.e., both model information (topology and geometry of reconstructed models) and image information (photometric features) are used to address a loop-closure detection. The advantages of using the layout-related information in the proposed loop-closing technique are twofold. First, it imposes a metric constraint on the global map consistency and, thus, adjusts the mapping scale drifts. Second, it can reduce matching ambiguity in the context of indoor corridors, where the scene is homogenously textured and extracting sufficient amount of distinguishable point features is a challenging task. To test the impact of the proposed technique on the performance of Layout SLAM, we have performed the experiments on wide-angle videos captured by a handheld camera. This dataset was collected from the indoor corridors of a building at York University. The obtained results demonstrate that the proposed method successfully detects the instances of loops while producing very limited trajectory errors.
Appleton, J D; Doyle, E; Fenton, D; Organo, C
2011-06-01
The probability of homes in Ireland having high indoor radon concentrations is estimated on the basis of known in-house radon measurements averaged over 10 km × 10 km grid squares. The scope for using airborne gamma-ray spectrometer data for the Tralee-Castleisland area of county Kerry and county Cavan to predict the radon potential (RP) in two distinct areas of Ireland is evaluated in this study. Airborne data are compared statistically with in-house radon measurements in conjunction with geological and ground permeability data to establish linear regression models and produce radon potential maps. The best agreement between the percentage of dwellings exceeding the reference level (RL) for radon concentrations in Ireland (% > RL), estimated from indoor radon data, and modelled RP in the Tralee-Castleisland area is produced using models based on airborne gamma-ray spectrometry equivalent uranium (eU) and ground permeability data. Good agreement was obtained between the % > RL from indoor radon data and RP estimated from eU data in the Cavan area using terrain specific models. In both areas, RP maps derived from eU data are spatially more detailed than the published 10 km grid map. The results show the potential for using airborne radiometric data for producing RP maps.
Oh, TaeSeok; Kim, MinJeong; Lim, JungJin; Kang, OnYu; Shetty, K Vidya; SankaraRao, B; Yoo, ChangKyoo; Park, Jae Hyung; Kim, Jeong Tai
2012-05-01
Subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, in this study, a new cumulative calculation method for the estimation of total amounts of indoor air pollutants emitted inside the subway station is proposed by taking cumulative amounts of indoor air pollutants based on integration concept. Minimum concentration of individual air pollutants which naturally exist in indoor space is referred as base concentration of air pollutants and can be found from the data collected. After subtracting the value of base concentration from data point of each data set of indoor air pollutant, the primary quantity of emitted air pollutant is calculated. After integration is carried out with these values, adding the base concentration to the integration quantity gives the total amount of indoor air pollutant emitted. Moreover the values of new index for cumulative indoor air quality obtained for 1 day are calculated using the values of cumulative air quality index (CAI). Cumulative comprehensive indoor air quality index (CCIAI) is also proposed to compare the values of cumulative concentrations of indoor air pollutants. From the results, it is clear that the cumulative assessment approach of indoor air quality (IAQ) is useful for monitoring the values of total amounts of indoor air pollutants emitted, in case of exposure to indoor air pollutants for a long time. Also, the values of CCIAI are influenced more by the values of concentration of NO2, which is released due to the use of air conditioners and combustion of the fuel. The results obtained in this study confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well. Nowadays, subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in the indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, this paper presents a new methodology for monitoring and assessing total amounts of indoor air pollutants emitted inside underground spaces and subway stations. A new methodology for the calculation of cumulative amounts of indoor air pollutants based on integration concept is proposed. The results suggest that the cumulative assessment approach of IAQ is useful for monitoring the values of total amounts of indoor air pollutants, if indoor air pollutants accumulated for a long time, especially NO2 pollutants. The results obtained here confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.
The Design and Implementation of Indoor Localization System Using Magnetic Field Based on Smartphone
NASA Astrophysics Data System (ADS)
Liu, J.; Jiang, C.; Shi, Z.
2017-09-01
Sufficient signal nodes are mostly required to implement indoor localization in mainstream research. Magnetic field take advantage of high precision, stable and reliability, and the reception of magnetic field signals is reliable and uncomplicated, it could be realized by geomagnetic sensor on smartphone, without external device. After the study of indoor positioning technologies, choose the geomagnetic field data as fingerprints to design an indoor localization system based on smartphone. A localization algorithm that appropriate geomagnetic matching is designed, and present filtering algorithm and algorithm for coordinate conversion. With the implement of plot geomagnetic fingerprints, the indoor positioning of smartphone without depending on external devices can be achieved. Finally, an indoor positioning system which is based on Android platform is successfully designed, through the experiments, proved the capability and effectiveness of indoor localization algorithm.
Network coding multiuser scheme for indoor visible light communications
NASA Astrophysics Data System (ADS)
Zhang, Jiankun; Dang, Anhong
2017-12-01
Visible light communication (VLC) is a unique alternative for indoor data transfer and developing beyond point-to-point. However, for realizing high-capacity networks, VLC is facing challenges including the constrained bandwidth of the optical access point and random occlusion. A network coding scheme for VLC (NC-VLC) is proposed, with increased throughput and system robustness. Based on the Lambertian illumination model, theoretical decoding failure probability of the multiuser NC-VLC system is derived, and the impact of the system parameters on the performance is analyzed. Experiments demonstrate the proposed scheme successfully in the indoor multiuser scenario. These results indicate that the NC-VLC system shows a good performance under the link loss and random occlusion.
Kumar, Amit; Chauhan, R P; Joshi, Manish; Sahoo, B K
2014-01-01
Building materials are the second major source of indoor radon after soil. The contribution of building materials towards indoor radon depends upon the radium content and exhalation rates and can be used as a primary index for radon levels in the dwellings. The radon flux data from the building materials was used for calculation of the indoor radon concentrations and doses by many researchers using one and two dimensional model suggested by various researchers. In addition to radium content, the radon wall flux from a surface strongly depends upon the radon diffusion length (L) and thickness of the wall (2d). In the present work the indoor radon concentrations from the measured radon exhalation rate of building materials calculated using different models available in literature and validation of models was made through measurement. The variation in the predicted radon flux from different models was compared with d/L value for wall and roofs of different dwellings. The results showed that the radon concentrations predicted by models agree with experimental value. The applicability of different model with d/L ratio was discussed. The work aims to select a more appropriate and general model among available models in literature for the prediction of indoor radon. Copyright © 2013 Elsevier Ltd. All rights reserved.
Interactive computation of coverage regions for indoor wireless communication
NASA Astrophysics Data System (ADS)
Abbott, A. Lynn; Bhat, Nitin; Rappaport, Theodore S.
1995-12-01
This paper describes a system which assists in the strategic placement of rf base stations within buildings. Known as the site modeling tool (SMT), this system allows the user to display graphical floor plans and to select base station transceiver parameters, including location and orientation, interactively. The system then computes and highlights estimated coverage regions for each transceiver, enabling the user to assess the total coverage within the building. For single-floor operation, the user can choose between distance-dependent and partition- dependent path-loss models. Similar path-loss models are also available for the case of multiple floors. This paper describes the method used by the system to estimate coverage for both directional and omnidirectional antennas. The site modeling tool is intended to be simple to use by individuals who are not experts at wireless communication system design, and is expected to be very useful in the specification of indoor wireless systems.
NASA Astrophysics Data System (ADS)
Heo, J.; Yi, S. M.
2016-12-01
Paired indoor-outdoor fine particulate matter (PM2.5) samples were collected at subway stations, underground shopping centers, and schools in Seoul metropolitan over a 4-year period between 2004 and 2007. Relationships between indoor and outdoor PM2.5 chemical species were determined and source contributions to indoor and outdoor PM2.5 mass were estimated using a positive matrix factorization (PMF) model. The PM2.5 samples were analyzed for major chemical components including organic carbon and elemental carbon, ions, and metals, and the results were used in the PMF model. The levels of the PM2.5 mass and its chemical components observed at the indoor sites were higher than those at the outdoor sites. Indoor levels of ions (i.e. sulfate, nitrate, ammonium), elemental carbon, and several metals (i.e. Fe, Zn, and Cu) were found to be significantly affected by outdoor sources. Very high indoor-to-outdoor mass ratio of these chemical components, in particular, were observed, representing the significant impacts of outdoor sources on indoor levels of them. Seven sources (secondary sulfate, secondary nitrate, mobile, biomass burning, roadway emissions, dust, and sea salt) were resolved by the PMF model at both of the indoor and outdoor sites. The secondary inorganic aerosol (i.e. secondary sulfate and nitrate) and the mobile sources were major contributors to the indoor and outdoor PM2.5, accounting for 47% and 27% of the outdoor PM2.5 and 40% and 25% of the indoor PM2.5, respectively. Furthermore, the contributions of the secondary inorganic aerosol and the mobile sources to the indoor PM2.5 were very comparable to its corresponding contributions to the outdoor PM2.5 levels. The spatial and temporal characteristics of each of sources resolved by the PMF model across the sites were examined using summary statistics, correlation analysis, and coefficient of variation and divergence analysis and the detailed results will be discussed in the presentation.
Integration of Thermal Indoor Conditions into Operational Heat Health Warning Systems
NASA Astrophysics Data System (ADS)
Koppe, C.; Becker, P.; Pfafferott, J.
2009-09-01
The 2003 heat wave in Western Europe with altogether 35,000 to 50,000 deaths in Europe, several thousands of which occurred in Germany, has clearly pointed out the danger arising from long periods with high heat load. As a consequence, Germany, as many other European countries, has started to implement a Heat Health Warning System (HHWS). The German HHWS is based on the ‘Perceived Temperature'. The 'Perceived Temperature' is determined through a heat budget model of the human organism which includes the main thermophysiologically relevant mechanisms of heat exchange with the atmosphere. The most important meteorological ambience parameters included in the model are air temperature, humidity, wind speed and radiation fluxes in the short-wave and long-wave ranges. In addition to using a heat budget model for the assessment of the thermal load, the German HHWS also takes into account that the human body reacts in different ways to its thermal environment due to physiological adaptation (short-term acclimatisation) and short-term behavioural adaptation. The restriction of such an approach, like the majority of approaches used to issue heat warnings, is that the threshold for a warning is generally derived from meteorological observations and that warnings are issued on the basis of weather forecasts. Both, the observed data and the weather forecasts are only available for outside conditions. The group of people who are most at risk of suffering from a heat wave, however, are the elderly and frail who mainly stay inside. The indoor situation, which varies largely from the conditions outside, is not taken into account by most of the warning systems. To overcome this limitation the DWD, in co-operation with the Fraunhofer Institute for Solar Energy Systems, has developed a model which simulates the thermal conditions in the indoor environment. As air-conditioning in private housing in Germany is not very common, the thermal indoor conditions depend on the outside conditions, on the building characteristics, and on the inhabitants' behaviour. The thermal building simulation model estimates the indoor heat load based of the predicted meteorological outside conditions by calculating the operative indoor temperature. The building types prevailing in Germany are quite heterogeneous. It was therefore decided to use for the thermal simulation a so-called "realistic worst-case” building type. In addition, a differentiation is made between two types of user behaviour: the active user opens the windows during the cold hours of the day and uses shading devices whereas the passive user does nothing to keep the heat outside. Since 2007, the DWD has been using the simulation of the indoor thermal conditions as an additional source of information for heat warnings. The information on the indoor conditions has proved very valuable for the decision whether to issue a heat warning or not.
Liao, C M; Liang, H M
2000-05-01
Two models for evaluating the contents and advection of manure moisture on odor causing volatile organic compounds (VOC-odor) volatilization from stored swine manure were studied for their ability to predict the volatilization rate (indoor air concentration) and cumulative exposure dose: a MJ-I model and a MJ-II model. Both models simulating depletion of source contaminant via volatilization and degradation based on an analytical model adapted from the behavior assessment model of Jury et al. In the MJ-I model, manure moisture movement was negligible, whereas in the MJ-II model, time-dependent indoor air concentrations was a function of constant manure moisture contents and steady-state moisture advection. Predicted indoor air concentrations and inhaled doses for the study VOC-odors of p-cresol, toluene, and p-xylene varied by up to two to three orders of magnitude depending on the manure moisture conditions. The sensitivity analysis of both models suggests that when manure moisture movement exists, simply MJ-I model is inherently not sufficient to represent a more generally volatilization process, which can even become stringent as moisture content increases. The conclusion illustrates how one needs to include a wide variety of manure moisture values in order to fully assess the complex volatilization mechanisms that are present in a real situation.
[Impact of air fresheners and deodorizers on the indoor total volatile organic compounds].
Jinno, Hideto; Tanaka-Kagawa, Toshiko; Obama, Tomoko; Miyagawa, Makoto; Yoshikawa, Jun; Komatsu, Kazuhiro; Tokunaga, Hiroshi
2007-01-01
Indoor air quality is a growing health concern because of the increased incidence of the building-related illness, such as sick-building syndrome and multiple chemical sensitivity/idiopathic environmental intolerance. In order to effectively reduce the unnecessary chemical exposure in the indoor environment, it would be important to quantitatively compare the emissions from many types of sources. Besides the chemical emissions from the building materials, daily use of household products may contribute at significant levels to the indoor volatile organic compounds (VOCs). In this study, we investigated the emission rate of VOCs and carbonyl compounds for 30 air fresheners and deodorizers by the standard small chamber test method (JIS A 1901). The total VOC (TVOC) emission rates of these household products ranged from the undetectable level (< 20 microg/unit/h) to 6,900 microg/unit/h. The mean TVOC emission rate of the air fresheners for indoor use (16 products) was 1,400 microg/unit/ h and that of the deodorizers for indoor use (6 products) was 58 microg/unit/h, indicating that the fragrances in the products account for the major part of the TVOC emissions. Based on the emission rates, the impacts on the indoor TVOC were estimated by the simple model with a volume of 17.4 m3 and a ventilation frequency of 0.5 times/h. The mean of the TVOC increment for the indoor air fresheners was 170 microg/m3, accounting for 40% of the current provisional target value, 400 microg/m3. These results suggest that daily use of household products can significantly influence the indoor air quality.
The influence of mosquito resting behaviour and associated microclimate for malaria risk
2011-01-01
Background The majority of the mosquito and parasite life-history traits that combine to determine malaria transmission intensity are temperature sensitive. In most cases, the process-based models used to estimate malaria risk and inform control and prevention strategies utilize measures of mean outdoor temperature. Evidence suggests, however, that certain malaria vectors can spend large parts of their adult life resting indoors. Presentation of hypothesis If significant proportions of mosquitoes are resting indoors and indoor conditions differ markedly from ambient conditions, simple use of outdoor temperatures will not provide reliable estimates of malaria transmission intensity. To date, few studies have quantified the differential effects of indoor vs outdoor temperatures explicitly, reflecting a lack of proper understanding of mosquito resting behaviour and associated microclimate. Testing the hypothesis Published records from 8 village sites in East Africa revealed temperatures to be warmer indoors than outdoors and to generally show less daily variation. Exploring the effects of these temperatures on malaria parasite development rate suggested indoor-resting mosquitoes could transmit malaria between 0.3 and 22.5 days earlier than outdoor-resting mosquitoes. These differences translate to increases in transmission risk ranging from 5 to approaching 3,000%, relative to predictions based on outdoor temperatures. The pattern appears robust for low- and highland areas, with differences increasing with altitude. Implications of the hypothesis Differences in indoor vs outdoor environments lead to large differences in the limits and the intensity of malaria transmission. This finding highlights a need to better understand mosquito resting behaviour and the associated microclimate, and to broaden assessments of transmission ecology and risk to consider the potentially important role of endophily. PMID:21736735
Indoor Modelling Benchmark for 3D Geometry Extraction
NASA Astrophysics Data System (ADS)
Thomson, C.; Boehm, J.
2014-06-01
A combination of faster, cheaper and more accurate hardware, more sophisticated software, and greater industry acceptance have all laid the foundations for an increased desire for accurate 3D parametric models of buildings. Pointclouds are the data source of choice currently with static terrestrial laser scanning the predominant tool for large, dense volume measurement. The current importance of pointclouds as the primary source of real world representation is endorsed by CAD software vendor acquisitions of pointcloud engines in 2011. Both the capture and modelling of indoor environments require great effort in time by the operator (and therefore cost). Automation is seen as a way to aid this by reducing the workload of the user and some commercial packages have appeared that provide automation to some degree. In the data capture phase, advances in indoor mobile mapping systems are speeding up the process, albeit currently with a reduction in accuracy. As a result this paper presents freely accessible pointcloud datasets of two typical areas of a building each captured with two different capture methods and each with an accurate wholly manually created model. These datasets are provided as a benchmark for the research community to gauge the performance and improvements of various techniques for indoor geometry extraction. With this in mind, non-proprietary, interoperable formats are provided such as E57 for the scans and IFC for the reference model. The datasets can be found at: http://indoor-bench.github.io/indoor-bench.
Magnetic field feature extraction and selection for indoor location estimation.
Galván-Tejada, Carlos E; García-Vázquez, Juan Pablo; Brena, Ramon F
2014-06-20
User indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices, which allows us to exploit not only infrastructures made for everyday use, such as WiFi, but also natural infrastructure, as is the case of natural magnetic field. In this paper we present an extension and improvement of our current indoor localization model based on the feature extraction of 46 magnetic field signal features. The extension adds a feature selection phase to our methodology, which is performed through Genetic Algorithm (GA) with the aim of optimizing the fitness of our current model. In addition, we present an evaluation of the final model in two different scenarios: home and office building. The results indicate that performing a feature selection process allows us to reduce the number of signal features of the model from 46 to 5 regardless the scenario and room location distribution. Further, we verified that reducing the number of features increases the probability of our estimator correctly detecting the user's location (sensitivity) and its capacity to detect false positives (specificity) in both scenarios.
NASA Astrophysics Data System (ADS)
Guan, Weipeng; Wu, Yuxiang; Xie, Canyu; Chen, Hao; Cai, Ye; Chen, Yingcong
2017-10-01
An indoor positioning algorithm based on visible light communication (VLC) is presented. This algorithm is used to calculate a three-dimensional (3-D) coordinate of an indoor optical wireless environment, which includes sufficient orders of multipath reflections from reflecting surfaces of the room. Leveraging the global optimization ability of the genetic algorithm (GA), an innovative framework for 3-D position estimation based on a modified genetic algorithm is proposed. Unlike other techniques using VLC for positioning, the proposed system can achieve indoor 3-D localization without making assumptions about the height or acquiring the orientation angle of the mobile terminal. Simulation results show that an average localization error of less than 1.02 cm can be achieved. In addition, in most VLC-positioning systems, the effect of reflection is always neglected and its performance is limited by reflection, which makes the results not so accurate for a real scenario and the positioning errors at the corners are relatively larger than other places. So, we take the first-order reflection into consideration and use artificial neural network to match the model of a nonlinear channel. The studies show that under the nonlinear matching of direct and reflected channels the average positioning errors of four corners decrease from 11.94 to 0.95 cm. The employed algorithm is emerged as an effective and practical method for indoor localization and outperform other existing indoor wireless localization approaches.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dutton, Spencer M.; Chan, Wanyu R.; Mendell, Mark J.
California's building efficiency standards (Title 24) mandate minimum prescribed ventilation rates (VRs) for commercial buildings. Title 24 standards currently include a prescriptive procedure similar to ASHRAE’s prescriptive “ventilation rate procedure”, but does not include an alternative procedure, akin to ASHRAE’s non-prescriptive “indoor air quality procedure” (IAQP). The IAQP determines minimum VRs based on objectively and subjectively evaluated indoor air quality (IAQ). The first primary goal of this study was to determine, in a set of California retail stores, the adequacy of Title 24 VRs and observed current measured VRs in providing the level of IAQ specified through an IAQP process,more » The second primary goal was to evaluate whether several VRs implemented experimentally in a big box store would achieve adequate IAQ, assessed objectively and subjectively. For the first goal, a list of contaminants of concern (CoCs) and reference exposure levels (RELs) were selected for evaluating IAQ. Ventilation rates and indoor and outdoor CoC concentrations were measured in 13 stores, including one “big box” store. Mass balance models were employed to calculate indoor contaminant source strengths for CoCs in each store. Using these source strengths and typical outdoor air contaminant concentrations, mass balance models were again used to calculate for each store the “IAQP” VR that would maintain indoor CoC concentrations below selected RELs. These IAQP VRs were compared to the observed VRs and to the Title 24- prescribed VRs. For the second goal, a VR intervention study was performed in the big box store to determine how objectively assessed indoor contaminant levels and subjectively assessed IAQ varied with VR. The three intervention study VRs included an approximation of the store’s current VR [0.24 air changes per hour (ACH)], the Title 24-prescribed VR [0.69 ACH], and the calculated IAQPbased VR [1.51 ACH]). Calculations of IAQP-based VRs showed that for the big box store and 11 of the 12 other stores, neither current measured VRs nor the Title 24-prescribed VRs would be sufficient to maintain indoor concentrations of all CoCs below RELs. In the intervention study, with the IAQP-based VR applied in the big box store, all CoCs were controlled below RELs (within margins of error). Also, at all three VRs in this store, the percentage of subjects reporting acceptable air quality exceeded an 80% criterion of acceptability. The IAQP allows consideration of outdoor air ventilation as just one of several possible tools for achieving adequate IAQ. In two of the 13 surveyed buildings, applying the IAQP to allow lower VRs could have saved energy whilst still maintaining acceptable indoor air quality. In the remaining 11 buildings, saving energy through lower VRs would require combination with other strategies, either reducing indoor sources of CoCs such as formaldehyde, or use of gas phase air cleaning technologies. Based on the findings from applying the IAQP calculations to retail stores and the IAQP-based intervention study, recommendations are made regarding the potential introduction of a comparable procedure in Title 24.« less
Goyal, Radha; Khare, Mukesh
2011-05-01
Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student's health and performance as they spend a substantial amount of their time (6-7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants' health. The objectives of the present study are twofold, one, to measure the concentrations of PM(10) (<10 microm), PM(2.5) (<2.5 microm), and PM(1.0) (<1.0 microm) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM(10) (NVIAQM(pm10)), PM(2.5) (NVIAQM(pm2.5)), and PM(1.0) (NVIAQM(pm1.0)) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO(2) concentrations have also been monitored during school hours. Predicted indoor PM(10) concentrations show poor correlations with observed indoor PM(10) concentrations (R (2) = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM(pm2.5) and NVIAQM(pm1.0) results show good correlations with observed concentrations of PM(2.5) (R(2) = 0.87 for weekdays and 0.9 for weekends) and PM(1.0) (R(2) = 0.86 for weekdays and 0.87 for weekends). NVIAQM(pm10) shows the tendency to underpredict indoor PM(10) concentrations during weekdays as it does not take into account the occupant's activities and its effects on the indoor concentrations during the class hours. Intense occupant's activities cause resuspension or delayed deposition of PM(10). The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant's activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R(c). The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R(c) (0.001 to 0.500) significantly affects the model performance.
We developed a numerical model to predict chemical concentrations in indoor environments resulting from soil vapor intrusion and volatilization from groundwater. The model, which integrates new and existing algorithms for chemical fate and transport, was originally...
NASA Astrophysics Data System (ADS)
Haagmans, G. G.; Verhagen, S.; Voûte, R. L.; Verbree, E.
2017-09-01
Since GPS tends to fail for indoor positioning purposes, alternative methods like indoor positioning systems (IPS) based on Bluetooth low energy (BLE) are developing rapidly. Generally, IPS are deployed in environments covered with obstacles such as furniture, walls, people and electronics influencing the signal propagation. The major factor influencing the system performance and to acquire optimal positioning results is the geometry of the beacons. The geometry of the beacons is limited to the available infrastructure that can be deployed (number of beacons, basestations and tags), which leads to the following challenge: Given a limited number of beacons, where should they be placed in a specified indoor environment, such that the geometry contributes to optimal positioning results? This paper aims to propose a statistical model that is able to select the optimal configuration that satisfies the user requirements in terms of precision. The model requires the definition of a chosen 3D space (in our case 7 × 10 × 6 meter), number of beacons, possible user tag locations and a performance threshold (e.g. required precision). For any given set of beacon and receiver locations, the precision, internal- and external reliability can be determined on forehand. As validation, the modeled precision has been compared with observed precision results. The measurements have been performed with an IPS of BlooLoc at a chosen set of user tag locations for a given geometric configuration. Eventually, the model is able to select the optimal geometric configuration out of millions of possible configurations based on a performance threshold (e.g. required precision).
NASA Astrophysics Data System (ADS)
Chen, Chun; Zhao, Bin
2011-01-01
Epidemiologic evidence indicates a relationship between outdoor particle exposure and adverse health effects, while most people spend 85-90% of their time indoors, thus understanding the relationship between indoor and outdoor particles is quite important. This paper aims to provide an up-to-date revision for both experiment and modeling on relationship between indoor and outdoor particles. The use of three different parameters: indoor/outdoor (I/O) ratio, infiltration factor and penetration factor, to assess the relationship between indoor and outdoor particles were reviewed. The experimental data of the three parameters measured both in real houses and laboratories were summarized and analyzed. The I/O ratios vary considerably due to the difference in size-dependent indoor particle emission rates, the geometry of the cracks in building envelopes, and the air exchange rates. Thus, it is difficult to draw uniform conclusions as detailed information, which make I/O ratio hardly helpful for understanding the indoor/outdoor relationship. Infiltration factor represents the equilibrium fraction of ambient particles that penetrates indoors and remains suspended, which avoids the mixture with indoor particle sources. Penetration factor is the most relevant parameter for the particle penetration mechanism through cracks and leaks in the building envelope. We investigate the methods used in previously published studies to both measure and model the infiltration and penetration factors. We also discuss the application of the penetration factor models and provide recommendations for improvement.
Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus
Buechler, Elizabeth D.; Pallin, Simon B.; Boudreaux, Philip R.; ...
2017-04-25
The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The
NASA Astrophysics Data System (ADS)
Huang, Kuo-Tsang
2013-04-01
Natural ventilation (NV) is considered one of the passive building strategies used for reducing cooling energy demand. The utilization of nature wind for cooling down indoor thermal environment to reach thermal comfort requires knowledge of adequately positioning the building fenestrations, designing inlet-outlet related opening ratios, planning unobstructed cross ventilation paths, and, the most important, assessing the utilization feasibility base on local climatic variables. Furthermore, factors that influence the indoor thermal condition include building envelope heat gain, indoor air velocity, indoor heat gain (e.g. heat discharges from occupant's body, lighting fixture, electrical appliances), and outdoor climate. Among the above, the indoor thermal performance of NV building is significantly dependent to outdoor climate conditions. In hot and humid Taiwan, under college school classrooms are usually operated in natural ventilation mode and are more vulnerable to climate change in regard to maintain indoor thermal comfort. As climate changes in progress, NV classrooms would expect to encounter more events of overheating in the near future, which result in more severe heat stress, and would risk the utilization of natural ventilation. To evaluate the overheating risk under the influence of recent climate change, an actual top floor elementary school classroom with 30 students located at north Taiwan was modeled. Long-term local hourly meteorological data were gathered and further constructed into EnergyPlus Weather Files (EPWs) format for building thermal dynamic simulation to discuss the indoor thermal environmental variation during the period of 1998 to 2012 by retrospective simulation. As indoor thermal environment is an overall condition resulting from a series combination of various factors, sub-hourly building simulation tool, EnergyPlus, coupled with the above fifteen years' EPWs was adopted to predict hourly indoor parameters of mean radiant temperature, air velocity, dry-bulb temperature and relative humidity. These physical quantities are crucial for calculating the thermal indices such as Physiological Equivalent Temperature (PET), New Standard Effective Temperature (SET*), and operative temperature (OT), which were subsequently being used for assessing thermal discomfort. Occurrences and the severity of overheating were assessed by observing the number of hours that surmount the upper limit of the adaptive thermal model proposed by ASHRAE Standard 55 (American Society of Heating, Refrigerating and Air-conditioning Engineers Standard) base on ISO 7730 method to characterize long term indoor thermal discomfort. Preliminary result show that although the degree of increase in overheating risk of NV classrooms was mild, there is a trend revealing that both the occurrences and the severity of thermal discomfort were gradually rising. The study also proposed several building renovation strategies for adapting the climate change to alleviate overheating situation. Efficiencies of these recommended strategies were also analyzed by simulating with the hottest year in comparison with the coldest year.
FUGACITY-BASED INDOOR RESIDENTIAL PESTICIDE FATE MODEL
Dermal and non-dietary pathways are possibly important for exposure to pesticides used in residences. Limited data have been collected on pesticide concentrations in residential air and surfaces following application. Models may be useful for interpreting these data and to make...
Vibration Penalty Estimates for Indoor Annoyance Caused by Sonic Boom
NASA Technical Reports Server (NTRS)
Rathsam, Jonathan; Klos, Jacob
2016-01-01
Commercial supersonic flight is currently forbidden over land because sonic booms have historically caused unacceptable annoyance levels in overflown communities. NASA is providing data and expertise to noise regulators as they consider relaxing the ban for future quiet supersonic aircraft. One key objective is a predictive model for indoor annoyance based on factors such as noise and indoor vibration levels. The current study quantified the increment in indoor sonic boom annoyance when sonic booms can be felt directly through structural vibrations in addition to being heard. A shaker mounted below each chair in the sonic boom simulator emulated vibrations transmitting through the structure to that chair. The vibration amplitudes were determined from numeric models of a large range of residential structures excited by the same sonic boom waveforms used in the experiment. The analysis yielded vibration penalties, which are the increments in sound level needed to increase annoyance as much as the vibration does. For sonic booms at acoustic levels from 75 to 84 dB Perceived Level, vibration signals with lower amplitudes (+1 sigma) yielded penalties from 0 to 5 dB, and vibration signals with higher amplitudes (+3 sigma) yielded penalties from 6 to 10 dB.
Indoor Tanning within UK Young Adults: An Extended Theory of Planned Behaviour Approach.
Dodd, Lorna J; Forshaw, Mark J; Williams, Stella
2013-01-01
The indoor tanning industry poses a long-term public health risk. Despite the adverse health effects, indoor tanning seems to be gaining considerable popularity. The study examined indoor tanning intentions and behaviour within UK young adults using an extended theory of planned behaviour model, which included variables on "appearance reasons to tan," "perceived susceptibility to damaging appearance," "perceived susceptibility to health consequences," and "tanning knowledge." The model was successful in predicting indoor tanning intentions and behaviour (explained 17% and 71%, resp.). An interesting outcome was the magnitude of the variable "appearance reasons to tan." A current tanned appearance therefore seemed to outweigh any adverse future appearance or health consequences caused by indoor tanning. Appearance-focused interventions to reduce such behaviour may now prove to be efficacious within a UK sample.
NASA Astrophysics Data System (ADS)
Gens, Alexandra; Hurley, J. Fintan; Tuomisto, Jouni T.; Friedrich, Rainer
2014-02-01
The insulation of residential buildings affects human exposure to fine particles. According to current EU guidelines, insulation is regulated for energy saving reasons. As buildings become tighter, the air exchange rate is reduced and, thus, the indoor concentration of pollutants is increased if there are significant indoor sources. While usually the effects of heat insulation and increase of the air-tightness of buildings on greenhouse gas emissions are highlighted, the negative impacts on human health due to higher indoor concentrations are not addressed. Thus, we investigated these impacts using scenarios in three European countries, i. e. Czech Republic, Switzerland and Greece. The assessment was based on modelling the human exposure to fine particles originating from sources of particles within outdoor and indoor air, including environmental tobacco smoke. Exposure response relationships were derived to link (adverse) health effects to the exposure. Furthermore, probable values for the parameters influencing the infiltration of fine particles into residential buildings were modelled. Results show that the insulation and increase of the air-tightness of residential buildings leads to an overall increase of the mean population exposure - and consequently adverse health effects - in all considered countries (ranging for health effects from 0.4% in Czech Republic to 11.8% in Greece for 100% insulated buildings) due to an accumulation of particles indoors, especially from environmental tobacco smoke. Considering only the emission reductions in outdoor air (omitting changes in infiltration parameters) leads to a decrease of adverse health effects. This study highlights the importance of ensuring a sufficient air exchange rate when insulating buildings, e. g. by prescribing heat ventilation and air conditioning systems in new buildings and information campaigns on good airing practice in renovated buildings. It also shows that assessing policy measures based on the exposure may provide different recommendations compared to an assessment based on only the outdoor air concentration.
The Development and Validation of the Mood-based Indoor Tanning Scale.
Carcioppolo, Nick; Chen, Yixin; John, Kevin K; Gonzalez, Andrea Martinez; King, Andy J; Morgan, Susan E; Hu, Shasa
2017-01-01
Research indicates that mood-based motivations may be an important predictor of indoor tanning bed use and may be related to indoor tanning dependence. Problematically, little research has been conducted to develop a psychometric measure of mood-based tanning motivations. The current study seeks to develop and validate the moodbased indoor tanning scale (MITS). Two studies were conducted to identify and verify the MITS factor structure as well as assess construct validity. Study 1 was conducted at 5 geographically diverse universities in the United States. Study 2 was conducted by using a national online sample in the United States. Results from study 1 specified the factor structure of the MITS. Results from study 2 suggest that a one-point increase in the MITS measure corresponds with using indoor tanning beds 11 more times in the past year. These findings demonstrate that moodbased tanning motivations are a strong predictor of indoor tanning intentions and behavior. Further, they suggest that health behavior researchers and healthcare practitioners can use the MITS to assess the extent to which mood-based motivations impact indoor tanning bed use.
A Self-Adaptive Model-Based Wi-Fi Indoor Localization Method.
Tuta, Jure; Juric, Matjaz B
2016-12-06
This paper presents a novel method for indoor localization, developed with the main aim of making it useful for real-world deployments. Many indoor localization methods exist, yet they have several disadvantages in real-world deployments-some are static, which is not suitable for long-term usage; some require costly human recalibration procedures; and others require special hardware such as Wi-Fi anchors and transponders. Our method is self-calibrating and self-adaptive thus maintenance free and based on Wi-Fi only. We have employed two well-known propagation models-free space path loss and ITU models-which we have extended with additional parameters for better propagation simulation. Our self-calibrating procedure utilizes one propagation model to infer parameters of the space and the other to simulate the propagation of the signal without requiring any additional hardware beside Wi-Fi access points, which is suitable for real-world usage. Our method is also one of the few model-based Wi-Fi only self-adaptive approaches that do not require the mobile terminal to be in the access-point mode. The only input requirements of the method are Wi-Fi access point positions, and positions and properties of the walls. Our method has been evaluated in single- and multi-room environments, with measured mean error of 2-3 and 3-4 m, respectively, which is similar to existing methods. The evaluation has proven that usable localization accuracy can be achieved in real-world environments solely by the proposed Wi-Fi method that relies on simple hardware and software requirements.
NASA Astrophysics Data System (ADS)
Tashakkori, H.; Rajabifard, A.; Kalantari, M.
2016-10-01
Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.
Shiue, Ivy
2015-09-01
A recent systematic review and meta-analysis has shown the effect of indoor mildew odour on allergic rhinitis risk, but its relation to other common chronic health outcomes in adults has not been investigated. Therefore, it was aimed to examine the relationship of indoor mildew odour and common health outcomes in adults in a national and population-based setting. Data was retrieved from the United States National Health and Nutrition Examination Surveys, 2005-2006, including the available information on demographics, housing characteristics, self-reported health conditions and urinary concentrations of environmental chemicals. T test, chi-squared test and survey-weighted logistic regression modelling were performed. Of all American adults (n = 4979), 744 (15.1%) reported indoor mildew odour or musty smell in their households. People who reported indoor mildew odour or musty smell also reported poorer self-rated health, sleep complaints, chronic bronchitis, asthma attack, itchy rash, sneezing and poor vision. In addition, people who reported indoor mildew odour or musty smell also tended to reside in older housing that were built 20 years earlier. However, there were no significant statistical associations found between indoor mildew odour or musty smell and urinary concentrations of environmental chemicals, which was also found to be associated with old housing. People who lived in older housing with indoor mildew odour or musty smell tended to have chronic health problems. To protect occupants in old housing from chronic illnesses associated with indoor mildew odour, elimination of the odour sources should be explored in future research and therefore public health and housing programs. Graphical abstract Pathway from old housing to musty smell, environmental chemicals and then health outcomes.
Tong, Zheming; Chen, Yujiao; Malkawi, Ali; Adamkiewicz, Gary; Spengler, John D
2016-01-01
Improper natural ventilation practices may deteriorate indoor air quality when in close proximity to roadways, although the intention is often to reduce energy consumption. In this study, we employed a CFD-based air quality model to quantify the impact of traffic-related air pollution on the indoor air quality of a naturally ventilated building. Our study found that the building envelope restricts dispersion and dilution of particulate matter. The indoor concentration in the baseline condition located 10m away from the roadway is roughly 16-21% greater than that at the edge of the roadway. The indoor flow recirculation creates a well-mixed zone with little variation in fine particle concentration (i.e., 253nm). For ultrafine particles (<100nm), a noticeable decrease in particle concentrations indoors with increasing distance from the road is observed due to Brownian and turbulent diffusion. In addition, the indoor concentration strongly depends on the distance between the roadway and building, particle size, wind condition, and window size and location. A break-even point is observed at D'~2.1 (normalized distance from the roadway by the width of the road). The indoor particle concentration is greater than that at the highway where D'<2.1, and vice versa. For new building planning, the distance from the roadway and the ambient wind condition need to be considered at the early design stage whereas the size and location of the window openings, the interior layout, and the placement of fresh air intakes are important to the indoor air quality of existing buildings adjacent to roadways. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Wunderlich, S.; Welpot, M.; Gaspard, I.
2014-11-01
The markets for smart home products and services are expected to grow over the next years, driven by the increasing demands of homeowners considering energy monitoring, management, environmental controls and security. Many of these new systems will be installed in existing homes and offices and therefore using radio based systems for cost reduction. A drawback of radio based systems in indoor environments are fading effects which lead to a high variance of the received signal strength and thereby to a difficult predictability of the encountered path loss of the various communication links. For that reason it is necessary to derive a statistical path loss model which can be used to plan a reliable and cost effective radio network. This paper presents the results of a measurement campaign, which was performed in six buildings to deduce realistic radio channel models for a high variety of indoor radio propagation scenarios in the short range devices (SRD) band at 868 MHz. Furthermore, a potential concept to reduce the variance of the received signal strength using a circular polarized (CP) patch antenna in combination with a linear polarized antenna in an one-to-one communication link is presented.
Stapleton, Jerod L; Manne, Sharon L; Darabos, Katie; Greene, Kathryn; Ray, Anne E; Turner, Amber L; Coups, Elliot J
2015-12-01
This article describes the acceptability and preliminary behavioral outcomes of a pilot randomized control trial of a web-based indoor tanning intervention for young adult women. The intervention targets indoor tanning users' perceptions of the benefits and value of tanning and addresses the role of body image-related constructs in indoor tanning. Participants were 186 young adult women who reported indoor tanning at least once in the past 12 months. The study design was a 2-arm randomized controlled trial with pre- and postintervention assessments and random assignment to an intervention or control condition. Intervention acceptability was assessed by obtaining participants' evaluation of the intervention. Regression analyses were used to test for intervention condition differences in preliminary behavioral outcomes measured at 6 weeks postintervention. Participants provided favorable evaluations of the intervention on several dimensions and a highly positive overall rating. Intervention participants were more likely to report abstaining from indoor tanning and indicated a lower likelihood of using indoor tanning in the future compared with control participants on the postintervention assessment. No differences were found for sunburns. The results of this pilot randomized controlled trial provide evidence that the indoor tanning intervention is acceptable to participants and may encourage cessation of indoor tanning behavior. The findings provide preliminary support for an indoor tanning intervention that engages tanners to challenge their beliefs about the benefits of indoor tanning. The use of a web-based indoor tanning intervention is unique and provides strong potential for dissemination. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
Cong, X C; Zhao, J J; Jing, Z; Wang, Q G; Ni, P F
2018-05-09
Recently, the problem of indoor particulate matter pollution has received much attention. An increasing number of epidemiological studies show that the concentration of atmospheric particulate matter has a significant effect on human health, even at very low concentrations. Most of these investigations have relied upon outdoor particle concentrations as surrogates of human exposures. However, considering that the concentration distribution of the indoor particulate matter is largely dependent on the extent to which these particles penetrate the building and on the degree of suspension in the indoor air, human exposures to particles of outdoor origin may not be equal to outdoor particle concentration levels. Therefore, it is critical to understand the relationship between the particle concentrations found outdoors and those found in indoor micro-environments. In this study, experiments were conducted using a naturally ventilated office located in Qingdao, China. The indoor and outdoor particle concentrations were measured at the same time using an optical counter with four size ranges. The particle size distribution ranged from 0.3 to 2.5 μm, and the experimental period was from April to September, 2016. Based on the experimental data, the dynamic and mass balance model based on time was used to estimate the penetration rate and deposition rate at air exchange rates of 0.03-0.25 h -1 . The values of the penetration rate and deposition velocity of indoor particles were determined to range from 0.45 to 0.82 h -1 and 1.71 to 2.82 m/h, respectively. In addition, the particulate pollution exposure in the indoor environment was analyzed to estimate the exposure hazard from indoor particulate matter pollution, which is important for human exposure to particles and associated health effects. The conclusions from this study can serve to provide a better understanding the dynamics and behaviors of airborne particle entering into buildings. And they will also highlight effective methods to reduce exposure to particles in office buildings.
Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including: air pollution concentrations; human activity patterns, such as the amount of time spent outdoors vs. indoors, commuting, wal...
NASA Astrophysics Data System (ADS)
Walikewitz, Nadine; Jänicke, Britta; Langner, Marcel; Endlicher, Wilfried
2018-01-01
Humans spend most of their time in confined spaces and are hence primarily exposed to the direct influence of indoor climate. The Universal Thermal Climate Index (UTCI) was obtained in 31 rooms (eight buildings) in Berlin, Germany, during summer 2013 and 2014. The indoor UTCI was determined from measurements of both air temperature and relative humidity and from data of mean radiant temperature and air velocity, which were either measured or modeled. The associated outdoor UTCI was obtained through facade measurements of air temperature and relative humidity, simulation of mean radiant temperature, and wind data from a central weather station. The results show that all rooms experienced heat stress according to UTCI levels, especially during heat waves. Indoor UTCI varied up to 6.6 K within the city and up to 7 K within building. Heat stress either during day or at night occurred on 35 % of all days. By comparing the day and night thermal loads, we identified maximum values above the 32 °C threshold for strong heat stress during the nighttime. Outdoor UTCI based on facade measurements provided no better explanation of indoor UTCI variability than the central weather station. In contrast, we found a stronger relationship of outdoor air temperature and indoor air temperature. Building characteristics, such as the floor level or window area, influenced indoor heat stress ambiguously. We conclude that indoor heat stress is a major hazard, and more effort toward understanding the causes and creating effective countermeasures is needed.
A variety of common activities in the home, such as smoking and cooking, generate indoor particle concentrations. Mathematical indoor air quality models permit predictions of indoor pollutant concentrations in homes, provided that parameter values such as source strengths and ...
Hourly indoor radon measurements in a research house.
Sesana, Lucia; Begnini, Stefania
2004-01-01
This paper reports and discusses the behaviour of radon concentration with time in an uninhabited dwelling. The relationship between variations in radon concentrations and indoor-outdoor temperatures and wind intensity has also been discussed. Radon concentration was measured hourly in a house located at a height of 800 m in the Lombard Prealps, at the top of the Valassina valley. The wind velocity and indoor-outdoor temperatures were measured by means of a meteorological station located on the terrace of the house. The data were analysed using the LBL model for indoor-outdoor air exchange and the models for the indoor accumulation of radon due to exhalation from building materials and pressure-driven infiltrations located underground. The role of wind and indoor-outdoor temperatures were analysed. The agreement of measurements with modelling clearly demonstrates the importance of the different sources of indoor radon. As the investigation was conducted in an uninhabited house, the measurements were not affected by the behaviour of people, e.g. opening and closing of windows. Measurements of the outdoor atmospheric concentrations of (222)Rn provide an index of the atmospheric stability, the formation of thermal inversions and convective turbulence.
Shiue, Ivy
2014-03-13
Passive smoking has contributed increased risks of cardiovascular disease, mental health, and mortality, but the cumulative effects from work or other households were less studied. Therefore, it was aimed to model the effects of indoor passive smoking from own home, work, and other households in a country-wide, population-based setting. Data in the Scottish Health Survey between 2008 and 2011 after the law banning smoking in public places were analyzed. Information including demographics, lifestyle factors, and self-reported cardiovascular disease and mental health was obtained by household interview. Analyses included chi-square test and survey-weighted logistic regression modeling. After full adjustment, it was observed that being exposed to indoor passive smoking, in particular in more than two places of exposure, was significantly associated with risks of stroke, angina, heart attack, abnormal heart rhythms, and GHQ ≥ 12. The significance remained for angina, GHQ ≥ 12 and probably heart attack in never smokers. The cumulative risks also impacted on sleep problems, self-recognition, making decisions, self-confidence, under strain constantly, depressed, happiness and self-worth. The significance remained for sleep problems, self-confidence, under strain constantly, depressed, and happiness in never smokers. Elimination of indoor passive smoking from different sources should still be a focus in future public health programs.
Hierarchy-associated semantic-rule inference framework for classifying indoor scenes
NASA Astrophysics Data System (ADS)
Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei
2016-03-01
Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.
Performance Analysis of Classification Methods for Indoor Localization in Vlc Networks
NASA Astrophysics Data System (ADS)
Sánchez-Rodríguez, D.; Alonso-González, I.; Sánchez-Medina, J.; Ley-Bosch, C.; Díaz-Vilariño, L.
2017-09-01
Indoor localization has gained considerable attention over the past decade because of the emergence of numerous location-aware services. Research works have been proposed on solving this problem by using wireless networks. Nevertheless, there is still much room for improvement in the quality of the proposed classification models. In the last years, the emergence of Visible Light Communication (VLC) brings a brand new approach to high quality indoor positioning. Among its advantages, this new technology is immune to electromagnetic interference and has the advantage of having a smaller variance of received signal power compared to RF based technologies. In this paper, a performance analysis of seventeen machine leaning classifiers for indoor localization in VLC networks is carried out. The analysis is accomplished in terms of accuracy, average distance error, computational cost, training size, precision and recall measurements. Results show that most of classifiers harvest an accuracy above 90 %. The best tested classifier yielded a 99.0 % accuracy, with an average error distance of 0.3 centimetres.
Indoor Pedestrian Navigation Using Foot-Mounted IMU and Portable Ultrasound Range Sensors
Girard, Gabriel; Côté, Stéphane; Zlatanova, Sisi; Barette, Yannick; St-Pierre, Johanne; van Oosterom, Peter
2011-01-01
Many solutions have been proposed for indoor pedestrian navigation. Some rely on pre-installed sensor networks, which offer good accuracy but are limited to areas that have been prepared for that purpose, thus requiring an expensive and possibly time-consuming process. Such methods are therefore inappropriate for navigation in emergency situations since the power supply may be disturbed. Other types of solutions track the user without requiring a prepared environment. However, they may have low accuracy. Offline tracking has been proposed to increase accuracy, however this prevents users from knowing their position in real time. This paper describes a real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods. The system uses a combination of four techniques: foot-mounted IMU (Inertial Motion Unit), ultrasonic ranging, particle filtering and model-based navigation. The very purpose of the project is to combine these four well-known techniques in a novel way to provide better indoor tracking results for pedestrians. PMID:22164034
A review of air exchange rate models for air pollution exposure assessments.
Breen, Michael S; Schultz, Bradley D; Sohn, Michael D; Long, Thomas; Langstaff, John; Williams, Ronald; Isaacs, Kristin; Meng, Qing Yu; Stallings, Casson; Smith, Luther
2014-11-01
A critical aspect of air pollution exposure assessments is estimation of the air exchange rate (AER) for various buildings where people spend their time. The AER, which is the rate of exchange of indoor air with outdoor air, is an important determinant for entry of outdoor air pollutants and for removal of indoor-emitted air pollutants. This paper presents an overview and critical analysis of the scientific literature on empirical and physically based AER models for residential and commercial buildings; the models highlighted here are feasible for exposure assessments as extensive inputs are not required. Models are included for the three types of airflows that can occur across building envelopes: leakage, natural ventilation, and mechanical ventilation. Guidance is provided to select the preferable AER model based on available data, desired temporal resolution, types of airflows, and types of buildings included in the exposure assessment. For exposure assessments with some limited building leakage or AER measurements, strategies are described to reduce AER model uncertainty. This review will facilitate the selection of AER models in support of air pollution exposure assessments.
Extended Maptree: a Representation of Fine-Grained Topology and Spatial Hierarchy of Bim
NASA Astrophysics Data System (ADS)
Wu, Y.; Shang, J.; Hu, X.; Zhou, Z.
2017-09-01
Spatial queries play significant roles in exchanging Building Information Modeling (BIM) data and integrating BIM with indoor spatial information. However, topological operators implemented for BIM spatial queries are limited to qualitative relations (e.g. touching, intersecting). To overcome this limitation, we propose an extended maptree model to represent the fine-grained topology and spatial hierarchy of indoor spaces. The model is based on a maptree which consists of combinatorial maps and an adjacency tree. Topological relations (e.g., adjacency, incidence, and covering) derived from BIM are represented explicitly and formally by extended maptrees, which can facilitate the spatial queries of BIM. To construct an extended maptree, we first use a solid model represented by vertical extrusion and boundary representation to generate the isolated 3-cells of combinatorial maps. Then, the spatial relationships defined in IFC are used to sew them together. Furthermore, the incremental edges of extended maptrees are labeled as removed 2-cells. Based on this, we can merge adjacent 3-cells according to the spatial hierarchy of IFC.
Control of asthma triggers in indoor air with air cleaners: a modeling analysis.
Myatt, Theodore A; Minegishi, Taeko; Allen, Joseph G; Macintosh, David L
2008-08-06
Reducing exposure to environmental agents indoors shown to increase asthma symptoms or lead to asthma exacerbations is an important component of a strategy to manage asthma for individuals. Numerous investigations have demonstrated that portable air cleaning devices can reduce concentrations of asthma triggers in indoor air; however, their benefits for breathing problems have not always been reproducible. The potential exposure benefits of whole house high efficiency in-duct air cleaners for sensitive subpopulations have yet to be evaluated. We used an indoor air quality modeling system (CONTAM) developed by NIST to examine peak and time-integrated concentrations of common asthma triggers present in indoor air over a year as a function of natural ventilation, portable air cleaners, and forced air ventilation equipped with conventional and high efficiency filtration systems. Emission rates for asthma triggers were based on experimental studies published in the scientific literature. Forced air systems with high efficiency filtration were found to provide the best control of asthma triggers: 30-55% lower cat allergen levels, 90-99% lower risk of respiratory infection through the inhalation route of exposure, 90-98% lower environmental tobacco smoke (ETS) levels, and 50-75% lower fungal spore levels than the other ventilation/filtration systems considered. These results indicate that the use of high efficiency in-duct air cleaners provide an effective means of controlling allergen levels not only in a single room, like a portable air cleaner, but the whole house. These findings are useful for evaluating potential benefits of high efficiency in-duct filtration systems for controlling exposure to asthma triggers indoors and for the design of trials of environmental interventions intended to evaluate their utility in practice.
Control of asthma triggers in indoor air with air cleaners: a modeling analysis
Myatt, Theodore A; Minegishi, Taeko; Allen, Joseph G; MacIntosh, David L
2008-01-01
Background Reducing exposure to environmental agents indoors shown to increase asthma symptoms or lead to asthma exacerbations is an important component of a strategy to manage asthma for individuals. Numerous investigations have demonstrated that portable air cleaning devices can reduce concentrations of asthma triggers in indoor air; however, their benefits for breathing problems have not always been reproducible. The potential exposure benefits of whole house high efficiency in-duct air cleaners for sensitive subpopulations have yet to be evaluated. Methods We used an indoor air quality modeling system (CONTAM) developed by NIST to examine peak and time-integrated concentrations of common asthma triggers present in indoor air over a year as a function of natural ventilation, portable air cleaners, and forced air ventilation equipped with conventional and high efficiency filtration systems. Emission rates for asthma triggers were based on experimental studies published in the scientific literature. Results Forced air systems with high efficiency filtration were found to provide the best control of asthma triggers: 30–55% lower cat allergen levels, 90–99% lower risk of respiratory infection through the inhalation route of exposure, 90–98% lower environmental tobacco smoke (ETS) levels, and 50–75% lower fungal spore levels than the other ventilation/filtration systems considered. These results indicate that the use of high efficiency in-duct air cleaners provide an effective means of controlling allergen levels not only in a single room, like a portable air cleaner, but the whole house. Conclusion These findings are useful for evaluating potential benefits of high efficiency in-duct filtration systems for controlling exposure to asthma triggers indoors and for the design of trials of environmental interventions intended to evaluate their utility in practice. PMID:18684328
Blocquet, M; Guo, F; Mendez, M; Ward, M; Coudert, S; Batut, S; Hecquet, C; Blond, N; Fittschen, C; Schoemaecker, C
2018-05-01
The characteristics of indoor light (intensity, spectral, spatial distribution) originating from outdoors have been studied using experimental and modeling tools. They are influenced by many parameters such as building location, meteorological conditions, and the type of window. They have a direct impact on indoor air quality through a change in chemical processes by varying the photolysis rates of indoor pollutants. Transmittances of different windows have been measured and exhibit different wavelength cutoffs, thus influencing the potential of different species to be photolysed. The spectral distribution of light entering indoors through the windows was measured under different conditions and was found to be weakly dependent on the time of day for indirect cloudy, direct sunshine, partly cloudy conditions contrary to the light intensity, in agreement with calculations of the transmittance as a function of the zenithal angle and the calculated outdoor spectral distribution. The same conclusion can be drawn concerning the position within the room. The impact of these light characteristics on the indoor chemistry has been studied using the INCA-Indoor model by considering the variation in the photolysis rates of key indoor species. Depending on the conditions, photolysis processes can lead to a significant production of radicals and secondary species. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
INDOOR AIR QUALITY MODELING (CHAPTER 58)
The chapter discussses indoor air quality (IAQ) modeling. Such modeling provides a way to investigate many IAQ problems without the expense of large field experiments. Where experiments are planned, IAQ models can be used to help design experiments by providing information on exp...
Mi, Jian; Takahashi, Yasutake
2016-01-01
Radio frequency identification (RFID) technology has already been explored for efficient self-localization of indoor mobile robots. A mobile robot equipped with RFID readers detects passive RFID tags installed on the floor in order to locate itself. The Monte-Carlo localization (MCL) method enables the localization of a mobile robot equipped with an RFID system with reasonable accuracy, sufficient robustness and low computational cost. The arrangements of RFID readers and tags and the size of antennas are important design parameters for realizing accurate and robust self-localization using a low-cost RFID system. The design of a likelihood model of RFID tag detection is also crucial for the accurate self-localization. This paper presents a novel design and arrangement of RFID readers and tags for indoor mobile robot self-localization. First, by considering small-sized and large-sized antennas of an RFID reader, we show how the design of the likelihood model affects the accuracy of self-localization. We also design a novel likelihood model by taking into consideration the characteristics of the communication range of an RFID system with a large antenna. Second, we propose a novel arrangement of RFID tags with eight RFID readers, which results in the RFID system configuration requiring much fewer readers and tags while retaining reasonable accuracy of self-localization. We verify the performances of MCL-based self-localization realized using the high-frequency (HF)-band RFID system with eight RFID readers and a lower density of RFID tags installed on the floor based on MCL in simulated and real environments. The results of simulations and real environment experiments demonstrate that our proposed low-cost HF-band RFID system realizes accurate and robust self-localization of an indoor mobile robot. PMID:27483279
Mi, Jian; Takahashi, Yasutake
2016-07-29
Radio frequency identification (RFID) technology has already been explored for efficient self-localization of indoor mobile robots. A mobile robot equipped with RFID readers detects passive RFID tags installed on the floor in order to locate itself. The Monte-Carlo localization (MCL) method enables the localization of a mobile robot equipped with an RFID system with reasonable accuracy, sufficient robustness and low computational cost. The arrangements of RFID readers and tags and the size of antennas are important design parameters for realizing accurate and robust self-localization using a low-cost RFID system. The design of a likelihood model of RFID tag detection is also crucial for the accurate self-localization. This paper presents a novel design and arrangement of RFID readers and tags for indoor mobile robot self-localization. First, by considering small-sized and large-sized antennas of an RFID reader, we show how the design of the likelihood model affects the accuracy of self-localization. We also design a novel likelihood model by taking into consideration the characteristics of the communication range of an RFID system with a large antenna. Second, we propose a novel arrangement of RFID tags with eight RFID readers, which results in the RFID system configuration requiring much fewer readers and tags while retaining reasonable accuracy of self-localization. We verify the performances of MCL-based self-localization realized using the high-frequency (HF)-band RFID system with eight RFID readers and a lower density of RFID tags installed on the floor based on MCL in simulated and real environments. The results of simulations and real environment experiments demonstrate that our proposed low-cost HF-band RFID system realizes accurate and robust self-localization of an indoor mobile robot.
Indoor-to-outdoor particle concentration ratio model for human exposure analysis
NASA Astrophysics Data System (ADS)
Lee, Jae Young; Ryu, Sung Hee; Lee, Gwangjae; Bae, Gwi-Nam
2016-02-01
This study presents an indoor-to-outdoor particle concentration ratio (IOR) model for improved estimates of indoor exposure levels. This model is useful in epidemiological studies with large population, because sampling indoor pollutants in all participants' house is often necessary but impractical. As a part of a study examining the association between air pollutants and atopic dermatitis in children, 16 parents agreed to measure the indoor and outdoor PM10 and PM2.5 concentrations at their homes for 48 h. Correlation analysis and multi-step multivariate linear regression analysis was performed to develop the IOR model. Temperature and floor level were found to be powerful predictors of the IOR. Despite the simplicity of the model, it demonstrated high accuracy in terms of the root mean square error (RMSE). Especially for long-term IOR estimations, the RMSE was as low as 0.064 and 0.063 for PM10 and PM2.5, respectively. When using a prediction model in an epidemiological study, understanding the consequence of the modeling error and justifying the use of the model is very important. In the last section, this paper discussed the impact of the modeling error and developed a novel methodology to justify the use of the model.
Yuan, Ye; Luo, Zhiwen; Liu, Jing; Wang, Yaowu; Lin, Yaoyu
2018-06-01
China is confronted with serious PM 2.5 pollution, especially in the capital city of Beijing. Exposure to PM 2.5 could lead to various negative health impacts including premature mortality. As people spend most of their time indoors, the indoor exposure to PM 2.5 from both indoor and outdoor origins constitutes the majority of personal exposure to PM 2.5 pollution. Different building interventions have been introduced to mitigate indoor PM 2.5 exposure, but always at the cost of energy expenditure. In this study, the health and economic benefits of different ventilation intervention strategies for reducing indoor PM 2.5 exposure are modeled using a representative urban residence in Beijing, with consideration of different indoor PM 2.5 emission strengths and outdoor pollution. Our modeling results show that the increase of envelope air-tightness can achieve significant economic benefits when indoor PM 2.5 emissions are absent; however, if an indoor PM 2.5 source is present, the benefits only increase slightly in mechanically ventilated buildings, but may show negative benefit without mechanical ventilation. Installing mechanical ventilation in Beijing can achieve annual economic benefits ranging from 200yuan/capita to 800yuan/capita if indoor PM 2.5 sources exist. If there is no indoor emission, the annual benefits above 200yuan/capita can be achieved only when the PM 2.5 filtration efficiency is no <90% and the envelope air-tightness is above Chinese National Standard Level 7. Introducing mechanical ventilation with low PM 2.5 filtration efficiency to current residences in urban Beijing will increase the indoor PM 2.5 exposure and result in excess costs to the residents. Copyright © 2018 Elsevier B.V. All rights reserved.
Occurrence, sources and human exposure assessment of SCCPs in indoor dust of northeast China.
Liu, Li-Hua; Ma, Wan-Li; Liu, Li-Yan; Huo, Chun-Yan; Li, Wen-Long; Gao, Chong-Jing; Li, Hai-Ling; Li, Yi-Fan; Chan, Hing Man
2017-06-01
Short-chain chlorinated paraffins (SCCPs) are widely used chemicals in household products and might cause adverse human health effects. However, limited information is available on the occurrence of SCCPs in indoor environments and their exposure risks on humans. In this study the concentrations, profiles and human exposure of SCCPs in indoor dust from five different indoor environments, including commercial stores, residential apartments, dormitories, offices and laboratories were characterized. The SCCPs levels ranged from 10.1 to 173.0 μg/g, with the median and mean concentration of 47.2 and 53.6 μg/g, respectively. No significant difference was found on concentrations among the five microenvironments. The most abundant compounds in indoor dust samples were homologues of C 13 group, Cl 7 group and N 20 (N is the total number of C and Cl) group. In the five microenvironments, commercial stores were more frequently exposed to shorter carbon chained and higher chlorinated homologues. Three potential sources for SCCPs were identified by the multiple linear regression of factor score model and correspondence analysis. The major sources of SCCPs in indoor dust were technical mixtures of CP-42 (42% chlorine, w/w) and CP-52 b (52% chlorine, w/w). The total daily exposure doses and hazard quotients (HQ) were calculated by the human exposure models, and they were all below the reference doses and threshold values, respectively. Monte Carlo simulation was applied to predict the human exposure risk of SCCPs. Infants and toddlers were at risk of SCCPs based on predicted HQ values, which were exceeded the threshold for neoplastic effects in the worst case. Our results on the occurrences, sources and human exposures of SCCPs will be useful to provide a better understanding of SCCPs behaviors in indoor environment in China, and to support environmental risk evaluation and regulation of SCCPs in the world. Copyright © 2017. Published by Elsevier Ltd.
Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings
NASA Astrophysics Data System (ADS)
Elbayoumi, Maher; Ramli, Nor Azam; Md Yusof, Noor Faizah Fitri; Yahaya, Ahmad Shukri Bin; Al Madhoun, Wesam; Ul-Saufie, Ahmed Zia
2014-09-01
In this study the concentrations of PM10, PM2.5, CO and CO2 concentrations and meteorological variables (wind speed, air temperature, and relative humidity) were employed to predict the annual and seasonal indoor concentration of PM10 and PM2.5 using multivariate statistical methods. The data have been collected in twelve naturally ventilated schools in Gaza Strip (Palestine) from October 2011 to May 2012 (academic year). The bivariate correlation analysis showed that the indoor PM10 and PM2.5 were highly positive correlated with outdoor concentration of PM10 and PM2.5. Further, Multiple linear regression (MLR) was used for modelling and R2 values for indoor PM10 were determined as 0.62 and 0.84 for PM10 and PM2.5 respectively. The Performance indicators of MLR models indicated that the prediction for PM10 and PM2.5 annual models were better than seasonal models. In order to reduce the number of input variables, principal component analysis (PCA) and principal component regression (PCR) were applied by using annual data. The predicted R2 were 0.40 and 0.73 for PM10 and PM2.5, respectively. PM10 models (MLR and PCR) show the tendency to underestimate indoor PM10 concentrations as it does not take into account the occupant's activities which highly affect the indoor concentrations during the class hours.
VLC-based indoor location awareness using LED light and image sensors
NASA Astrophysics Data System (ADS)
Lee, Seok-Ju; Yoo, Jong-Ho; Jung, Sung-Yoon
2012-11-01
Recently, indoor LED lighting can be considered for constructing green infra with energy saving and additionally providing LED-IT convergence services such as visible light communication (VLC) based location awareness and navigation services. For example, in case of large complex shopping mall, location awareness to navigate the destination is very important issue. However, the conventional navigation using GPS is not working indoors. Alternative location service based on WLAN has a problem that the position accuracy is low. For example, it is difficult to estimate the height exactly. If the position error of the height is greater than the height between floors, it may cause big problem. Therefore, conventional navigation is inappropriate for indoor navigation. Alternative possible solution for indoor navigation is VLC based location awareness scheme. Because indoor LED infra will be definitely equipped for providing lighting functionality, indoor LED lighting has a possibility to provide relatively high accuracy of position estimation combined with VLC technology. In this paper, we provide a new VLC based positioning system using visible LED lights and image sensors. Our system uses location of image sensor lens and location of reception plane. By using more than two image sensor, we can determine transmitter position less than 1m position error. Through simulation, we verify the validity of the proposed VLC based new positioning system using visible LED light and image sensors.
Indoor air quality of low and middle income urban households in Durban, South Africa.
Jafta, Nkosana; Barregard, Lars; Jeena, Prakash M; Naidoo, Rajen N
2017-07-01
Elevated levels of indoor air pollutants may cause cardiopulmonary disease such as lower respiratory infection, chronic obstructive lung disease and lung cancer, but the association with tuberculosis (TB) is unclear. So far the risk estimates of TB infection or/and disease due to indoor air pollution (IAP) exposure are based on self-reported exposures rather than direct measurements of IAP, and these exposures have not been validated. The aim of this paper was to characterize and develop predictive models for concentrations of three air pollutants (PM 10 , NO 2 and SO 2 ) in homes of children participating in a childhood TB study. Children younger than 15 years living within the eThekwini Municipality in South Africa were recruited for a childhood TB case control study. The homes of these children (n=246) were assessed using a walkthrough checklist, and in 114 of them monitoring of three indoor pollutants was also performed (sampling period: 24h for PM 10 , and 2-3 weeks for NO 2 and SO 2 ). Linear regression models were used to predict PM 10 and NO 2 concentrations from household characteristics, and these models were validated using leave out one cross validation (LOOCV). SO 2 concentrations were not modeled as concentrations were very low. Mean indoor concentrations of PM 10 (n=105) , NO 2 (n=82) and SO 2 (n=82) were 64μg/m 3 (range 6.6-241); 19μg/m 3 (range 4.5-55) and 0.6μg/m 3 (range 0.005-3.4) respectively with the distributions for all three pollutants being skewed to the right. Spearman correlations showed weak positive correlations between the three pollutants. The largest contributors to the PM 10 predictive model were type of housing structure (formal or informal), number of smokers in the household, and type of primary fuel used in the household. The NO 2 predictive model was influenced mostly by the primary fuel type and by distance from the major roadway. The coefficients of determination (R 2 ) for the models were 0.41 for PM 10 and 0.31 for NO 2 . Spearman correlations were significant between measured vs. predicted PM 10 and NO 2 with coefficients of 0.66 and 0.55 respectively. Indoor PM 10 levels were relatively high in these households. Both PM 10 and NO 2 can be modeled with a reasonable validity and these predictive models can decrease the necessary number of direct measurements that are expensive and time consuming. Copyright © 2017 Elsevier Inc. All rights reserved.
Towards fish-eye camera based in-home activity assessment.
Bas, Erhan; Erdogmus, Deniz; Ozertem, Umut; Pavel, Misha
2008-01-01
Indoors localization, activity classification, and behavioral modeling are increasingly important for surveillance applications including independent living and remote health monitoring. In this paper, we study the suitability of fish-eye cameras (high-resolution CCD sensors with very-wide-angle lenses) for the purpose of monitoring people in indoors environments. The results indicate that these sensors are very useful for automatic activity monitoring and people tracking. We identify practical and mathematical problems related to information extraction from these video sequences and identify future directions to solve these issues.
NASA Astrophysics Data System (ADS)
Peng, Qi; Guan, Weipeng; Wu, Yuxiang; Cai, Ye; Xie, Canyu; Wang, Pengfei
2018-01-01
This paper proposes a three-dimensional (3-D) high-precision indoor positioning strategy using Tabu search based on visible light communication. Tabu search is a powerful global optimization algorithm, and the 3-D indoor positioning can be transformed into an optimal solution problem. Therefore, in the 3-D indoor positioning, the optimal receiver coordinate can be obtained by the Tabu search algorithm. For all we know, this is the first time the Tabu search algorithm is applied to visible light positioning. Each light-emitting diode (LED) in the system broadcasts a unique identity (ID) and transmits the ID information. When the receiver detects optical signals with ID information from different LEDs, using the global optimization of the Tabu search algorithm, the 3-D high-precision indoor positioning can be realized when the fitness value meets certain conditions. Simulation results show that the average positioning error is 0.79 cm, and the maximum error is 5.88 cm. The extended experiment of trajectory tracking also shows that 95.05% positioning errors are below 1.428 cm. It can be concluded from the data that the 3-D indoor positioning based on the Tabu search algorithm achieves the requirements of centimeter level indoor positioning. The algorithm used in indoor positioning is very effective and practical and is superior to other existing methods for visible light indoor positioning.
Unsupervised Indoor Localization Based on Smartphone Sensors, iBeacon and Wi-Fi.
Chen, Jing; Zhang, Yi; Xue, Wei
2018-04-28
In this paper, we propose UILoc, an unsupervised indoor localization scheme that uses a combination of smartphone sensors, iBeacons and Wi-Fi fingerprints for reliable and accurate indoor localization with zero labor cost. Firstly, compared with the fingerprint-based method, the UILoc system can build a fingerprint database automatically without any site survey and the database will be applied in the fingerprint localization algorithm. Secondly, since the initial position is vital to the system, UILoc will provide the basic location estimation through the pedestrian dead reckoning (PDR) method. To provide accurate initial localization, this paper proposes an initial localization module, a weighted fusion algorithm combined with a k-nearest neighbors (KNN) algorithm and a least squares algorithm. In UILoc, we have also designed a reliable model to reduce the landmark correction error. Experimental results show that the UILoc can provide accurate positioning, the average localization error is about 1.1 m in the steady state, and the maximum error is 2.77 m.
EVALUATING SOURCES OF INDOOR AIR POLLUTION
The article discusses a three-phase approach, employing environmental chambers, indoor air quality (IAQ) models, and test house experiments, that is effective in linking sources of indoor pollutants to measured concentrations. mission factors developed in test chambers can be use...
A model to estimate the cost effectiveness of the indoorenvironment improvements in office work
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seppanen, Olli; Fisk, William J.
2004-06-01
Deteriorated indoor climate is commonly related to increases in sick building syndrome symptoms, respiratory illnesses, sick leave, reduced comfort and losses in productivity. The cost of deteriorated indoor climate for the society is high. Some calculations show that the cost is higher than the heating energy costs of the same buildings. Also building-level calculations have shown that many measures taken to improve indoor air quality and climate are cost-effective when the potential monetary savings resulting from an improved indoor climate are included as benefits gained. As an initial step towards systemizing these building level calculations we have developed a conceptualmore » model to estimate the cost-effectiveness of various measures. The model shows the links between the improvements in the indoor environment and the following potential financial benefits: reduced medical care cost, reduced sick leave, better performance of work, lower turn over of employees, and lower cost of building maintenance due to fewer complaints about indoor air quality and climate. The pathways to these potential benefits from changes in building technology and practices go via several human responses to the indoor environment such as infectious diseases, allergies and asthma, sick building syndrome symptoms, perceived air quality, and thermal environment. The model also includes the annual cost of investments, operation costs, and cost savings of improved indoor climate. The conceptual model illustrates how various factors are linked to each other. SBS symptoms are probably the most commonly assessed health responses in IEQ studies and have been linked to several characteristics of buildings and IEQ. While the available evidence indicates that SBS symptoms can affect these outcomes and suspects that such a linkage exists, at present we can not quantify the relationships sufficiently for cost-benefit modeling. New research and analyses of existing data to quantify the financial importance of SBS symptoms would enable more widespread consideration of the effects of IEQ in cost benefit calculations.« less
Impacts of Changes of Indoor Air Pressure and Air Exchange Rate in Vapor Intrusion Scenarios
Shen, Rui; Suuberg, Eric M.
2016-01-01
There has, in recent years, been increasing interest in understanding the transport processes of relevance in vapor intrusion of volatile organic compounds (VOCs) into buildings on contaminated sites. These studies have included fate and transport modeling. Most such models have simplified the prediction of indoor air contaminant vapor concentrations by employing a steady state assumption, which often results in difficulties in reconciling these results with field measurements. This paper focuses on two major factors that may be subject to significant transients in vapor intrusion situations, including the indoor air pressure and the air exchange rate in the subject building. A three-dimensional finite element model was employed with consideration of daily and seasonal variations in these factors. From the results, the variations of indoor air pressure and air exchange rate are seen to contribute to significant variations in indoor air contaminant vapor concentrations. Depending upon the assumptions regarding the variations in these parameters, the results are only sometimes consistent with the reports of several orders of magnitude in indoor air concentration variations from field studies. The results point to the need to examine more carefully the interplay of these factors in order to quantitatively understand the variations in potential indoor air exposures. PMID:28090133
Impacts of Changes of Indoor Air Pressure and Air Exchange Rate in Vapor Intrusion Scenarios.
Shen, Rui; Suuberg, Eric M
2016-02-01
There has, in recent years, been increasing interest in understanding the transport processes of relevance in vapor intrusion of volatile organic compounds (VOCs) into buildings on contaminated sites. These studies have included fate and transport modeling. Most such models have simplified the prediction of indoor air contaminant vapor concentrations by employing a steady state assumption, which often results in difficulties in reconciling these results with field measurements. This paper focuses on two major factors that may be subject to significant transients in vapor intrusion situations, including the indoor air pressure and the air exchange rate in the subject building. A three-dimensional finite element model was employed with consideration of daily and seasonal variations in these factors. From the results, the variations of indoor air pressure and air exchange rate are seen to contribute to significant variations in indoor air contaminant vapor concentrations. Depending upon the assumptions regarding the variations in these parameters, the results are only sometimes consistent with the reports of several orders of magnitude in indoor air concentration variations from field studies. The results point to the need to examine more carefully the interplay of these factors in order to quantitatively understand the variations in potential indoor air exposures.
Image-Based Localization for Indoor Environment Using Mobile Phone
NASA Astrophysics Data System (ADS)
Huang, Y.; Wang, H.; Zhan, K.; Zhao, J.; Gui, P.; Feng, T.
2015-05-01
Real-time indoor localization based on supporting infrastructures like wireless devices and QR codes are usually costly and labor intensive to implement. In this study, we explored a cheap alternative approach based on images for indoor localization. A user can localize him/herself by just shooting a photo of the surrounding indoor environment using the mobile phone. No any other equipment is required. This is achieved by employing image-matching and searching techniques with a dataset of pre-captured indoor images. In the beginning, a database of structured images of the indoor environment is constructed by using image matching and the bundle adjustment algorithm. Then each image's relative pose (its position and orientation) is estimated and the semantic locations of images are tagged. A user's location can then be determined by comparing a photo taken by the mobile phone to the database. This is done by combining quick image searching, matching and the relative orientation. This study also try to explore image acquisition plans and the processing capacity of off-the-shell mobile phones. During the whole pipeline, a collection of indoor images with both rich and poor textures are examined. Several feature detectors are used and compared. Pre-processing of complex indoor photo is also implemented on the mobile phone. The preliminary experimental results prove the feasibility of this method. In the future, we are trying to raise the efficiency of matching between indoor images and explore the fast 4G wireless communication to ensure the speed and accuracy of the localization based on a client-server framework.
Mitigation of building-related polychlorinated biphenyls in indoor air of a school
2012-01-01
Background Sealants and other building materials sold in the U.S. from 1958 - 1971 were commonly manufactured with polychlorinated biphenyls (PCBs) at percent quantities by weight. Volatilization of PCBs from construction materials has been reported to produce PCB levels in indoor air that exceed health protective guideline values. The discovery of PCBs in indoor air of schools can produce numerous complications including disruption of normal operations and potential risks to health. Understanding the dynamics of building-related PCBs in indoor air is needed to identify effective strategies for managing potential exposures and risks. This paper reports on the efficacy of selected engineering controls implemented to mitigate concentrations of PCBs in indoor air. Methods Three interventions (ventilation, contact encapsulation, and physical barriers) were evaluated in an elementary school with PCB-containing caulk and elevated PCB concentrations in indoor air. Fluorescent light ballasts did not contain PCBs. Following implementation of the final intervention, measurements obtained over 14 months were used to assess the efficacy of the mitigation methods over time as well as temporal variability of PCBs in indoor air. Results Controlling for air exchange rates and temperature, the interventions produced statistically significant (p < 0.05) reductions in concentrations of PCBs in indoor air of the school. The mitigation measures remained effective over the course of the entire follow-up period. After all interventions were implemented, PCB levels in indoor air were associated with indoor temperature. In a "broken-stick" regression model with a node at 20°C, temperature explained 79% of the variability of indoor PCB concentrations over time (p < 0.001). Conclusions Increasing outdoor air ventilation, encapsulating caulk, and constructing a physical barrier over the encapsulated material were shown to be effective at reducing exposure concentrations of PCBs in indoor air of a school and also preventing direct contact with PCB caulk. In-place management methods such as these avoid the disruption and higher costs of demolition, disposal and reconstruction required when PCB-containing building materials are removed from a school. Because of the influence of temperature on indoor air PCB levels, risk assessment results based on short-term measurements, e.g., a single day or season, may be erroneous and could lead to sub-optimal allocation of resources. PMID:22490055
Gao, Xiaolei; Wei, Jianjian; Lei, Hao; Xu, Pengcheng; Cowling, Benjamin J; Li, Yuguo
2016-01-01
Emerging diseases may spread rapidly through dense and large urban contact networks, especially they are transmitted by the airborne route, before new vaccines can be made available. Airborne diseases may spread rapidly as people visit different indoor environments and are in frequent contact with others. We constructed a simple indoor contact model for an ideal city with 7 million people and 3 million indoor spaces, and estimated the probability and duration of contact between any two individuals during one day. To do this, we used data from actual censuses, social behavior surveys, building surveys, and ventilation measurements in Hong Kong to define eight population groups and seven indoor location groups. Our indoor contact model was integrated with an existing epidemiological Susceptible, Exposed, Infectious, and Recovered (SEIR) model to estimate disease spread and with the Wells-Riley equation to calculate local infection risks, resulting in an integrated indoor transmission network model. This model was used to estimate the probability of an infected individual infecting others in the city and to study the disease transmission dynamics. We predicted the infection probability of each sub-population under different ventilation systems in each location type in the case of a hypothetical airborne disease outbreak, which is assumed to have the same natural history and infectiousness as smallpox. We compared the effectiveness of controlling ventilation in each location type with other intervention strategies. We conclude that increasing building ventilation rates using methods such as natural ventilation in classrooms, offices, and homes is a relatively effective strategy for airborne diseases in a large city.
Meng, Qing Yu; Turpin, Barbara J; Korn, Leo; Weisel, Clifford P; Morandi, Maria; Colome, Steven; Zhang, Junfeng Jim; Stock, Thomas; Spektor, Dalia; Winer, Arthur; Zhang, Lin; Lee, Jong Hoon; Giovanetti, Robert; Cui, William; Kwon, Jaymin; Alimokhtari, Shahnaz; Shendell, Derek; Jones, Jennifer; Farrar, Corice; Maberti, Silvia
2005-01-01
The Relationship of Indoor, Outdoor and Personal Air (RIOPA) study was designed to investigate residential indoor, outdoor and personal exposures to several classes of air pollutants, including volatile organic compounds, carbonyls and fine particles (PM2.5). Samples were collected from summer, 1999 to spring, 2001 in Houston (TX), Los Angeles (CA) and Elizabeth (NJ). Indoor, outdoor and personal PM2.5 samples were collected at 212 nonsmoking residences, 162 of which were sampled twice. Some homes were chosen due to close proximity to ambient sources of one or more target analytes, while others were farther from sources. Median indoor, outdoor and personal PM2.5 mass concentrations for these three sites were 14.4, 15.5 and 31.4 microg/m3, respectively. The contributions of ambient (outdoor) and nonambient sources to indoor and personal concentrations were quantified using a single compartment box model with measured air exchange rate and a random component superposition (RCS) statistical model. The median contribution of ambient sources to indoor PM2.5 concentrations using the mass balance approach was estimated to be 56% for all study homes (63%, 52% and 33% for California, New Jersey and Texas study homes, respectively). Reasonable variations in model assumptions alter median ambient contributions by less than 20%. The mean of the distribution of ambient contributions across study homes agreed well for the mass balance and RCS models, but the distribution was somewhat broader when calculated using the mass balance model with measured air exchange rates.
Jan, Shau-Shiun; Hsu, Li-Ta; Tsai, Wen-Ming
2010-01-01
In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system.
Jan, Shau-Shiun; Hsu, Li-Ta; Tsai, Wen-Ming
2010-01-01
In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system. PMID:22319282
An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor.
Xu, He; Ding, Ye; Li, Peng; Wang, Ruchuan; Li, Yizhu
2017-08-05
The Global Positioning System (GPS) is widely used in outdoor environmental positioning. However, GPS cannot support indoor positioning because there is no signal for positioning in an indoor environment. Nowadays, there are many situations which require indoor positioning, such as searching for a book in a library, looking for luggage in an airport, emergence navigation for fire alarms, robot location, etc. Many technologies, such as ultrasonic, sensors, Bluetooth, WiFi, magnetic field, Radio Frequency Identification (RFID), etc., are used to perform indoor positioning. Compared with other technologies, RFID used in indoor positioning is more cost and energy efficient. The Traditional RFID indoor positioning algorithm LANDMARC utilizes a Received Signal Strength (RSS) indicator to track objects. However, the RSS value is easily affected by environmental noise and other interference. In this paper, our purpose is to reduce the location fluctuation and error caused by multipath and environmental interference in LANDMARC. We propose a novel indoor positioning algorithm based on Bayesian probability and K -Nearest Neighbor (BKNN). The experimental results show that the Gaussian filter can filter some abnormal RSS values. The proposed BKNN algorithm has the smallest location error compared with the Gaussian-based algorithm, LANDMARC and an improved KNN algorithm. The average error in location estimation is about 15 cm using our method.
Development and validation of the Comprehensive Indoor Tanning Expectations Scale.
Noar, Seth M; Myrick, Jessica Gall; Morales-Pico, Brenda; Thomas, Nancy E
2014-05-01
Strong links between indoor tanning behavior and skin cancer have been demonstrated across several studies. Understanding the complex belief systems that underlie indoor tanning in young women is a crucial first step in developing interventions to deter this behavior. To develop and validate a comprehensive, multidimensional, theory-based outcome expectations measure to advance an understanding of the sets of beliefs that underlie indoor tanning behavior among young women. Cross-sectional study comprising a web-based survey of 11 sororities at a large university in the southeastern United States. Study participants (n = 706) were aged 18 to 25 years; 45.3% had tanned indoors in their lifetime and 30.3% in the past year. Intention to tan indoors, frequency of indoor tanning behavior in the past year, and indoor tanner type (nontanner, former tanner, or current tanner). A comprehensive scale assessing indoor tanning outcome expectations was developed. In total, 6 positive outcome expectations factors and 5 negative outcome expectations factors were identified. These subscales were reliable (coefficient α range, 0.86-0.95) and were significantly (mostly at P < .001) correlated with a set of established measures, including appearance motivation, indoor tanning attitudes and norms, and intention to tan indoors. Examination of subscales across the 3 indoor tanning groups also revealed significant (P < .001) differences on all 11 subscales. Current tanners had the most positive and least negative perceptions about indoor tanning, while nontanners had the most negative and least positive perceptions. Former tanners tended to fall in between these 2 groups. The 2 subscales with the largest differences across the groups were mood enhancement (positive outcome expectation) and psychological/physical discomfort (negative outcome expectation). Multiple linear regression analyses demonstrated several outcome expectations subscales to be significantly associated with intention to tan indoors and frequency of indoor tanning behavior. Results suggest that the Comprehensive Indoor Tanning Expectations (CITE) Scale provides a reliable and valid assessment of the complex sets of beliefs that underlie indoor tanning, including positive (motivational) and negative (deterrent) beliefs. This new scale may further advance research on indoor tanning beliefs and can guide health communications to prevent and deter indoor tanning behavior.
Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots
Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro
2013-01-01
This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments. PMID:24152933
Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots.
Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro
2013-10-21
This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments.
TESTS OF INDOOR AIR QUALITY SINKS
Experiments were conducted in a room-size test chamber to determine the sink effects of selected materials on indoor air concentrations of p-dichlorobenzene (PDCB). hese effects might alter pollutant behavior from that predicted using similar indoor air quality models, by reducin...
Information on where and how individuals spend their time is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure assessors have relied on time-use surveys in order to obtain information on exposure-related b...
Assessment of zero-equation SGS models for simulating indoor environment
NASA Astrophysics Data System (ADS)
Taghinia, Javad; Rahman, Md Mizanur; Tse, Tim K. T.
2016-12-01
The understanding of air-flow in enclosed spaces plays a key role to designing ventilation systems and indoor environment. The computational fluid dynamics aspects dictate that the large eddy simulation (LES) offers a subtle means to analyze complex flows with recirculation and streamline curvature effects, providing more robust and accurate details than those of Reynolds-averaged Navier-Stokes simulations. This work assesses the performance of two zero-equation sub-grid scale models: the Rahman-Agarwal-Siikonen-Taghinia (RAST) model with a single grid-filter and the dynamic Smagorinsky model with grid-filter and test-filter scales. This in turn allows a cross-comparison of the effect of two different LES methods in simulating indoor air-flows with forced and mixed (natural + forced) convection. A better performance against experiments is indicated with the RAST model in wall-bounded non-equilibrium indoor air-flows; this is due to its sensitivity toward both the shear and vorticity parameters.
The effect of e-cigarette indoor vaping restrictions on adult prenatal smoking and birth outcomes.
Cooper, Michael T; Pesko, Michael F
2017-12-01
We estimate the effect of county-level e-cigarette indoor vaping restrictions on adult prenatal smoking and birth outcomes using United States birth record data for 7 million pregnant women living in places already comprehensively banning the indoor use of traditional cigarettes. We use both cross-sectional and panel data to estimate our difference-in-difference models. Our panel model results suggest that adoption of a comprehensive indoor vaping restriction increased prenatal smoking by 2.0 percentage points, which is double the estimate obtained from a cross-sectional model. We also document heterogeneity in effect sizes along lines of age, education, and type of insurance. Copyright © 2017 Elsevier B.V. All rights reserved.
Darling, E; Corsi, R L
2017-05-01
Ozone reacts readily with many indoor materials, as well as with compounds in indoor air. These reactions lead to lower indoor than outdoor ozone concentrations when outdoor air is the major contributor to indoor ozone. However, the products of indoor ozone reactions may be irritating or harmful to building occupants. While active technologies exist to reduce indoor ozone concentrations (i.e, in-duct filtration using activated carbon), they can be cost-prohibitive for some and/or infeasible for dwellings that do not have heating, ventilating, and air-conditioning systems. In this study, the potential for passive reduction of indoor ozone by two different clay-based interior surface coatings was explored. These coatings were exposed to occupied residential indoor environments and tested bimonthly in environmental chambers for quantification of ozone reaction probabilities and reaction product emission rates over a 6-month period. Results indicate that clay-based coatings may be effective as passive removal materials, with relatively low by-product emission rates that decay rapidly within 2 months. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
FIAM-pwp-Formaldehyde Indoor Air Model – Pressed Wood Products
The Formaldehyde Indoor Air Model-pressed wood products (FIAM-pwp) user guide contains information on the equations and defaults used to estimate exposure from formaldehye emitted from pressed wood products.
Impact of surface ozone interactions on indoor air chemistry: A modeling study.
Kruza, M; Lewis, A C; Morrison, G C; Carslaw, N
2017-09-01
An INdoor air Detailed Chemical Model was developed to investigate the impact of ozone reactions with indoor surfaces (including occupants), on indoor air chemistry in simulated apartments subject to ambient air pollution. The results are consistent with experimental studies showing that approximately 80% of ozone indoors is lost through deposition to surfaces. The human body removes ozone most effectively from indoor air per square meter of surface, but the most significant surfaces for C 6 -C 10 aldehyde formation are soft furniture and painted walls owing to their large internal surfaces. Mixing ratios of between 8 and 11 ppb of C 6 -C 10 aldehydes are predicted to form in apartments in various locations in summer, the highest values are when ozone concentrations are enhanced outdoors. The most important aldehyde formed indoors is predicted to be nonanal (5-7 ppb), driven by oxidation-derived emissions from painted walls. In addition, ozone-derived emissions from human skin were estimated for a small bedroom at nighttime with concentrations of nonanal, decanal, and 4-oxopentanal predicted to be 0.5, 0.7, and 0.7 ppb, respectively. A detailed chemical analysis shows that ozone-derived surface aldehyde emissions from materials and people change chemical processing indoors, through enhanced formation of nitrated organic compounds and decreased levels of oxidants. © 2017 The Authors. Indoor Air Published by John Wiley & Sons Ltd.
Lopez-Iturri, Peio; de Miguel-Bilbao, Silvia; Aguirre, Erik; Azpilicueta, Leire; Falcone, Francisco; Ramos, Victoria
2015-01-01
The electromagnetic field leakage levels of nonionizing radiation from a microwave oven have been estimated within a complex indoor scenario. By employing a hybrid simulation technique, based on coupling full wave simulation with an in-house developed deterministic 3D ray launching code, estimations of the observed electric field values can be obtained for the complete indoor scenario. The microwave oven can be modeled as a time- and frequency-dependent radiating source, in which leakage, basically from the microwave oven door, is propagated along the complete indoor scenario interacting with all of the elements present in it. This method can be of aid in order to assess the impact of such devices on expected exposure levels, allowing adequate minimization strategies such as optimal location to be applied. PMID:25705676
Smartphone-based integrated PDR/GPS/Bluetooth pedestrian location
NASA Astrophysics Data System (ADS)
Li, Xianghong; Wei, Dongyan; Lai, Qifeng; Xu, Ying; Yuan, Hong
2017-02-01
Typical indoor location method is fingerprint and traditional outdoor location system is GPS. Both of them are of poor accuracy and limited only for indoor or outdoor environments. As the smartphones are equipped with MEMS sensors, it means PDR can be widely used. In this paper, an algorithm of smartphone-based integrated PDR/GPS/Bluetooth for pedestrian location in the indoor/outdoor is proposed, which can be highly expected to realize seamless indoor/outdoor localization of the pedestrian. In addition, we also provide technologies to estimate orientation with Magnetometer and Gyroscope and detect context with output of sensors. The extensive experimental results show that the proposed algorithm can realize seamless indoor/outdoor localization.
REVIEW OF INDOOR EMISSION SOURCE MODELS: PART 2. PARAMETER ESTIMATION
This review consists of two sections. Part I provides an overview of 46 indoor emission source models. Part 2 (this paper) focuses on parameter estimation, a topic that is critical to modelers but has never been systematically discussed. A perfectly valid model may not be a usefu...
The Lawrence Berkeley National Laboratory Population Impact Assessment Modeling Framework (PIAMF) was expanded to enable determination of indoor PM2.5 concentrations and exposures in a set of 50,000 homes representing the US housing stock. A mass-balance model is used to calculat...
Myrick, Jessica Gall; Noar, Seth M; Kelley, Dannielle; Zeitany, Alexandra E; Morales-Pico, Brenda M; Thomas, Nancy E
2017-01-01
In order to better understand drivers of dangerous indoor tanning behaviors, researchers developed the Comprehensive Indoor Tanning Expectations scale. To examine the longitudinal effectiveness of Comprehensive Indoor Tanning Expectations, we surveyed young women in the Southeastern United States at two time points ( N = 553). The scale demonstrated strong test-retest reliability. Participants who believed indoor tanning would improve their mood and afford social approval were significantly more likely to tan 6 months later, while participants who believed indoor tanning leads to psychological/physical discomfort were significantly less likely to tan 6 months later. Knowing the psychological bases for indoor tanning can inform intervention and message design.
Air-Sense: indoor environment monitoring evaluation system based on ZigBee network
NASA Astrophysics Data System (ADS)
Huang, Yang; Hu, Liang; Yang, Disheng; Liu, Hengchang
2017-08-01
In the modern life, people spend most of their time indoors. However, indoor environmental quality problems have always been affecting people’s social activities. In general, indoor environmental quality is also related to our indoor activities. Since most of the organic irritants and volatile gases are colorless, odorless and too tiny to be seen, because we have been unconsciously overlooked indoor environment quality. Consequently, our body suffer a great health problem. In this work, we propose Air-Sense system which utilizes the platform of ZigBee Network to collect and detect the real-time indoor environment quality. What’s more, Air-Sense system can also provide data analysis, and visualizing the results of the indoor environment to the user.
Liagkouridis, Ioannis; Cousins, Anna Palm; Cousins, Ian T
2015-08-15
Several groups of flame retardants (FRs) have entered the market in recent years as replacements for polybrominated diphenyl ethers (PBDEs), but little is known about their physical-chemical properties or their environmental transport and fate. Here we make best estimates of the physical-chemical properties and undertake evaluative modelling assessments (indoors and outdoors) for 35 so-called 'novel' and 'emerging' brominated flame retardants (BFRs) and 22 organophosphorus flame retardants (OPFRs). A QSPR (Quantitative Structure-Property Relationship) based technique is used to reduce uncertainty in physical-chemical properties and to aid property selection for modelling, but it is evident that more, high quality property data are required for improving future assessments. Evaluative modelling results show that many of the alternative FRs, mainly alternative BFRs and some of the halogenated OPFRs, behave similarly to the PBDEs both indoors and outdoors. These alternative FRs exhibit high overall persistence (Pov), long-range transport potential (LRTP) and POP-like behaviour and on that basis cannot be regarded as suitable replacements to PBDEs. A group of low molecular weight alternative BFRs and non-halogenated OPFRs show a potentially better environmental performance based on Pov and LRTP metrics. Results must be interpreted with caution though since there are significant uncertainties and limited data to allow for thorough model evaluation. Additional environmental parameters such as toxicity and bioaccumulative potential as well as functionality issues should be considered in an industrial substitution strategy. Copyright © 2015 Elsevier B.V. All rights reserved.
Impact of particle emissions of new laser printers on modeled office room
NASA Astrophysics Data System (ADS)
Koivisto, Antti J.; Hussein, Tareq; Niemelä, Raimo; Tuomi, Timo; Hämeri, Kaarle
2010-06-01
In this study, we present how an indoor aerosol model can be used to characterize particle emitter and predict influence of the source on indoor air quality. Particle size-resolved emission rates were quantified and the source's influence on indoor air quality was estimated by using office model simulations. We measured particle emissions from three modern laser printers in a flow-through chamber. Measured parameters were used as input parameters for an indoor aerosol model, which we then used to quantify the particle emission rates. The same indoor aerosol model was used to simulate the effect of the particle emission source inside an office model. The office model consists of a mechanically ventilated empty room and the particle source. The aerosol from the ventilation air was a filtered urban background aerosol. The effect of the ventilation rate was studied using three different ventilation ratios 1, 2 and 3 h -1. According to the model, peak emission rates of the printers exceeded 7.0 × 10 8 s -1 (2.5 × 10 12 h -1), and emitted mainly ultrafine particles (diameter less than 100 nm). The office model simulation results indicate that a print job increases ultrafine particle concentration to a maximum of 2.6 × 10 5 cm -3. Printer-emitted particles increased 6-h averaged particle concentration over eleven times compared to the background particle concentration.
Kendall, G M; Wakeford, R; Athanson, M; Vincent, T J; Carter, E J; McColl, N P; Little, M P
2016-03-01
Gamma radiation from natural sources (including directly ionising cosmic rays) is an important component of background radiation. In the present paper, indoor measurements of naturally occurring gamma rays that were undertaken as part of the UK Childhood Cancer Study are summarised, and it is shown that these are broadly compatible with an earlier UK National Survey. The distribution of indoor gamma-ray dose rates in Great Britain is approximately normal with mean 96 nGy/h and standard deviation 23 nGy/h. Directly ionising cosmic rays contribute about one-third of the total. The expanded dataset allows a more detailed description than previously of indoor gamma-ray exposures and in particular their geographical variation. Various strategies for predicting indoor natural background gamma-ray dose rates were explored. In the first of these, a geostatistical model was fitted, which assumes an underlying geologically determined spatial variation, superimposed on which is a Gaussian stochastic process with Matérn correlation structure that models the observed tendency of dose rates in neighbouring houses to correlate. In the second approach, a number of dose-rate interpolation measures were first derived, based on averages over geologically or administratively defined areas or using distance-weighted averages of measurements at nearest-neighbour points. Linear regression was then used to derive an optimal linear combination of these interpolation measures. The predictive performances of the two models were compared via cross-validation, using a randomly selected 70 % of the data to fit the models and the remaining 30 % to test them. The mean square error (MSE) of the linear-regression model was lower than that of the Gaussian-Matérn model (MSE 378 and 411, respectively). The predictive performance of the two candidate models was also evaluated via simulation; the OLS model performs significantly better than the Gaussian-Matérn model.
Using Openstreetmap Data to Generate Building Models with Their Inner Structures for 3d Maps
NASA Astrophysics Data System (ADS)
Wang, Z.; Zipf, A.
2017-09-01
With the development of Web 2.0, more and more data related to indoor environments has been collected within the volunteered geographic information (VGI) framework, which creates a need for construction of indoor environments from VGI. In this study, we focus on generating 3D building models from OpenStreetMap (OSM) data, and provide an approach to support construction and visualization of indoor environments on 3D maps. In this paper, we present an algorithm which can extract building information from OSM data, and can construct building structures as well as inner building components (e.g., doors, rooms, and windows). A web application is built to support the processing and visualization of the building models on a 3D map. We test our approach with an indoor dataset collected from the field. The results show the feasibility of our approach and its potentials to provide support for a wide range of applications, such as indoor and outdoor navigation, urban planning, and incident management.
NASA Astrophysics Data System (ADS)
Bartolomei, V.; Gomez Alvarez, E.; Glor, M.; Gligorovski, S.; Temime-Roussel, B.; Quivet, E.; Strekowski, R.; Zetzsch, C.; Held, A. B.; Wortham, H.
2013-12-01
Hydroxyl radical (OH) is one of the most important oxidant species in the atmosphere controlling its self-oxidizing capacity. The main sources of OH radicals are photolysis of ozone and photolysis of nitrous acid (HONO), among the others. In the indoor air, the ozonolysis of alkenes has been suggested as the main OH formation pathway. The possibility for OH formation through photolytic pathways in the indoor environment has been, up to now, ignored (Gómez Alvarez et al., 2012). Models and indirect measurements to the present time predicted concentrations of OH radicals in the order of 104 -105 cm-3. Recently, by direct measurements we have detected high OH radical concentrations of 1.8 106 cm-3 in a classroom in Marseille and we demonstrated that its main source is the photolysis of HONO (Gómez Alvarez et al., 2013). The concentrations of HONO are quite high indoors, reaching levels in the order of a few tens of ppbV (Gómez Alvarez et al., 2013). This is mainly due to 1) direct combustion sources and 2) heterogeneous reactions of NO2 on the numerous surfaces present in the indoor environment. HONO levels of 30 ppb were measured in a previous campaign carried out in Bayreuth in July 2012 as direct emissions from the combustion of a candle. The combination between so high concentrations of HONO and higher than expected light transmissions indoors (or indoor artificial lighting) could have a significant impact on the OH concentrations indoors which could feasibly become considerably higher than we measured in our school campaign (Gomez Alvarez et al., 2013). In order to evaluate these upper limits under combustion conditions in the indoor environment, we have carried out a campaign in the LOTASC chamber (Bayreuth, Germany). For this aim, the exhaust fumes from the burning of a commonly used domestic candle have been introduced in the chamber. The chamber was irradiated under well research indoor lighting conditions. A thorough characterization of light intensities and span (wavelength distribution) indoors have been performed, which had been identified as a clear flaw in our knowledge restricting the advancement of indoor air quality models. OH concentration levels have been determined using d9-butanol as tracer, using the OH clock determination procedure by PTR-MS-TOF. The OH radical concentration was investigated using different light intensities representative from indoor conditions, both natural and artificial and also different levels of RH. The PSS model has been performed in order to evaluate the contribution of different sources to the OH radical concentrations indoors under these conditions. The obtained results from the PSS model clearly indicate that the main source of OH radical indoors under combustion conditions is the photolysis of HONO under typical indoor irradiation conditions. REFERENCES Gómez Alvarez E, Wortham H, Strekowski R, Zetzsch C, Gligorovski S (2012) Atmospheric photo-sensitized heterogeneous and multiphase reactions: From outdoors to indoors, Environ. Sci. Technol. 46, 1955-1963. Gómez Alvarez, E.; Amedro, D.; Afif, C. ; Gligorovski, S.; Schoemacker , C.; Fittschen, C. ; Doussin, J. F.; Wortham, H. (2013) Unexpectedly high indoor hydroxyl radical concentrations associated with nitrous acid. Proc. Natl. Acad. Sci. USA Accepted.
i-SVOC -- A simulation program for indoor SVOCs (Version 1.0)
Program i-SVOC estimates the emissions, transport, and sorption of semivolatile organic compounds (SVOCs) in the indoor environment as functions of time when a series of initial conditions is given. This program implements a framework for dynamic modeling of indoor SVOCs develope...
Measurement and modeling of indoor radon concentrations in residential buildings.
Park, Ji Hyun; Whang, Sungim; Lee, Hyun Young; Lee, Cheol-Min; Kang, Dae Ryong
2018-01-01
Radon, the primary constituent of natural radiation, is the second leading environmental cause of lung cancer after smoking. To confirm a relationship between indoor radon exposure and lung cancer, estimating cumulative levels of exposure to indoor radon for an individual or population is necessary. This study sought to develop a model for estimate indoor radon concentrations in Korea. Especially, our model and method may have wider application to other residences, not to specific site, and can be used in situations where actual measurements for input variables are lacking. In order to develop a model, indoor radon concentrations were measured at 196 ground floor residences using passive alpha-track detectors between January and April 2016. The arithmetic mean (AM) and geometric mean (GM) means of indoor radon concentrations were 117.86±72.03 and 95.13±2.02 Bq/m 3 , respectively. Questionnaires were administered to assess the characteristics of each residence, the environment around the measuring equipment, and lifestyles of the residents. Also, national data on indoor radon concentrations at 7643 detached houses for 2011-2014 were reviewed to determine radon concentrations in the soil, and meteorological data on temperature and wind speed were utilized to approximate ventilation rates. The estimated ventilation rates and radon exhalation rates from the soil varied from 0.18 to 0.98/hr (AM, 0.59±0.17/hr) and 326.33 to 1392.77 Bq/m 2 /hr (AM, 777.45±257.39; GM, 735.67±1.40 Bq/m 2 /hr), respectively. With these results, the developed model was applied to estimate indoor radon concentrations for 157 residences (80% of all 196 residences), which were randomly sampled. The results were in better agreement for Gyeonggi and Seoul than for other regions of Korea. Overall, the actual and estimated radon concentrations were in better agreement, except for a few low-concentration residences.
Sorption and reemission of formaldehyde by gypsum wallboard. Report for June 1990-August 1992
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chang, J.C.S.
1993-01-01
The paper gives results of an analysis of the sorption and desorption of formaldehyde by unpainted wallboard, using a mass transfer model based on the Langmuir sorption isotherm. The sorption and desorption rate constants are determined by short-term experimental data. Long-term sorption and desorption curves are developed by the mass transfer model without any adjustable parameters. Compared with other empirically developed models, the mass transfer model has more extensive applicability and provides an elucidation of the sorption and desorption mechanism that empirical models cannot. The mass transfer model is also more feasible and accurate than empirical models for applications suchmore » as scale-up and exposure assessment. For a typical indoor environment, the model predicts that gypsum wallboard is a much stronger sink for formaldehyde than for other indoor air pollutants such as tetrachloroethylene and ethylbenzene. The strong sink effects are reflected by the high equilibrium capacity and slow decay of the desorption curve.« less
Ha, Mina; Hwang, Seung-sik; Kang, Sungchan; Park, No-Wook; Chang, Byung-Uck; Kim, Yongjae
2017-01-01
Indoor radon is the second most important risk factor for lung cancer and may also be a risk factor for hematopoietic cancers, particularly in children and adolescents. The present study measured indoor radon concentration nationwide at 5553 points during 1989–2009 and spatially interpolated using lognormal kriging. The incidences of lung cancer, non-Hodgkin’s lymphoma (NHL), and leukemia, stratified by sex and five-year age groups in each of the 234 administrative regions in the country during 1999–2008, were obtained from the National Cancer Registry and used to calculate the standardized incidence ratios. After considering regional deprivation index values and smoking rates by sex in each region as confounding variables, the cancer risks were estimated based on Bayesian hierarchical modeling. We found that a 10 Bq/m3 increase in indoor radon concentration was associated with a 1% increase in the incidence of lung cancer in male and a 7% increase in NHL in female children and adolescents in Korea aged less than 20 years. Leukemia was not associated with indoor radon concentration. The increase in NHL risk among young women requires confirmation in future studies, and the radon control program should consider children and adolescents. PMID:28338643
Ha, Mina; Hwang, Seung-Sik; Kang, Sungchan; Park, No-Wook; Chang, Byung-Uck; Kim, Yongjae
2017-03-24
Indoor radon is the second most important risk factor for lung cancer and may also be a risk factor for hematopoietic cancers, particularly in children and adolescents. The present study measured indoor radon concentration nationwide at 5553 points during 1989-2009 and spatially interpolated using lognormal kriging. The incidences of lung cancer, non-Hodgkin's lymphoma (NHL), and leukemia, stratified by sex and five-year age groups in each of the 234 administrative regions in the country during 1999-2008, were obtained from the National Cancer Registry and used to calculate the standardized incidence ratios. After considering regional deprivation index values and smoking rates by sex in each region as confounding variables, the cancer risks were estimated based on Bayesian hierarchical modeling. We found that a 10 Bq/m³ increase in indoor radon concentration was associated with a 1% increase in the incidence of lung cancer in male and a 7% increase in NHL in female children and adolescents in Korea aged less than 20 years. Leukemia was not associated with indoor radon concentration. The increase in NHL risk among young women requires confirmation in future studies, and the radon control program should consider children and adolescents.
Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels
Olama, Mohammed M.; Djouadi, Seddik M.; Li, Yanyan; ...
2013-01-01
Stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean-square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and nonresolvable multipath received signals are considered and represented as small-scaled Nakagami fading. Themore » proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method’s viability and the results are presented.« less
NASA Astrophysics Data System (ADS)
Gonzales, Melissa
To evaluate those factors which influence the assignment of ozone ( O3) exposures in an epidemiologic context a field study was conducted in the South Coast Air Basin (SoCAB) during the summer of 19% in which time, location, activity (TLA) information and direct measurements of personal O3 exposure were concurrently collected on a group of college students. Current and past O3 exposures were modeled and evaluated as a function of ambient O 3, activity and mobility patterns, indoor ventilation, and recalled TLA information collected one year later. The effect of these factors on the within- and between-subject exposure variability assigned by ecologic (EC) and microenvironment (MEV) models were examined by two-hour intervals, on weekends and weekdays, and by monitoring week compared to personal exposures measured with a passive sampling device (PSD). The students reported spending 85% of their time inside, 7% outside and 8% in- transit. More time was spent outdoors on weekends than on weekdays. Ambient O3 levels were also higher on weekends. In the study area, where a dense O3 monitoring network and the appropriate topography exist fixed-site O3 accurately assigned ambient O3 levels within a 10 mile radius. The variation in the ecologic exposure assignments was low compared to the estimated variation among PSD-measured and MEV-modeled estimates due to the low spatial variation of ambient O3 levels across the SoCAB areas visited by the students. MEV and PSD exposure estimates better captured the variability of personal exposure in any given ambient spatial regimen compared to ecologic exposure assignments. MEV exposure estimates based on recalled TLA patterns, were similar to the MEV estimates based on diary-recorded TLA patterns. For this study population, PSD-measured O3 exposures were estimated to average 32% lower than ``true'' exposure levels due to indoor/outdoor differences in the PSD collection rate. The level of detail obtained from the TLA diary is not necessary for the assignment of current of past O3 exposures in epidemiologic studies. It may be more adventitious to characterize the locations visited, and indoor and outdoor time with the greatest accuracy possible and to use these data to estimate exposure from nearest-monitor ambient O 3 measurements and sets of indoor/outdoor O3 ratios validated to reflect personal exposure within indoor microenvironments.
A Context-Recognition-Aided PDR Localization Method Based on the Hidden Markov Model
Lu, Yi; Wei, Dongyan; Lai, Qifeng; Li, Wen; Yuan, Hong
2016-01-01
Indoor positioning has recently become an important field of interest because global navigation satellite systems (GNSS) are usually unavailable in indoor environments. Pedestrian dead reckoning (PDR) is a promising localization technique for indoor environments since it can be implemented on widely used smartphones equipped with low cost inertial sensors. However, the PDR localization severely suffers from the accumulation of positioning errors, and other external calibration sources should be used. In this paper, a context-recognition-aided PDR localization model is proposed to calibrate PDR. The context is detected by employing particular human actions or characteristic objects and it is matched to the context pre-stored offline in the database to get the pedestrian’s location. The Hidden Markov Model (HMM) and Recursive Viterbi Algorithm are used to do the matching, which reduces the time complexity and saves the storage. In addition, the authors design the turn detection algorithm and take the context of corner as an example to illustrate and verify the proposed model. The experimental results show that the proposed localization method can fix the pedestrian’s starting point quickly and improves the positioning accuracy of PDR by 40.56% at most with perfect stability and robustness at the same time. PMID:27916922
A Self-Adaptive Model-Based Wi-Fi Indoor Localization Method
Tuta, Jure; Juric, Matjaz B.
2016-01-01
This paper presents a novel method for indoor localization, developed with the main aim of making it useful for real-world deployments. Many indoor localization methods exist, yet they have several disadvantages in real-world deployments—some are static, which is not suitable for long-term usage; some require costly human recalibration procedures; and others require special hardware such as Wi-Fi anchors and transponders. Our method is self-calibrating and self-adaptive thus maintenance free and based on Wi-Fi only. We have employed two well-known propagation models—free space path loss and ITU models—which we have extended with additional parameters for better propagation simulation. Our self-calibrating procedure utilizes one propagation model to infer parameters of the space and the other to simulate the propagation of the signal without requiring any additional hardware beside Wi-Fi access points, which is suitable for real-world usage. Our method is also one of the few model-based Wi-Fi only self-adaptive approaches that do not require the mobile terminal to be in the access-point mode. The only input requirements of the method are Wi-Fi access point positions, and positions and properties of the walls. Our method has been evaluated in single- and multi-room environments, with measured mean error of 2–3 and 3–4 m, respectively, which is similar to existing methods. The evaluation has proven that usable localization accuracy can be achieved in real-world environments solely by the proposed Wi-Fi method that relies on simple hardware and software requirements. PMID:27929453
Huang, Lihui; Pu, Zhongnan; Li, Mu; Sundell, Jan
2015-01-01
Objective Ambient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM2.5 mass concentrations for urban residences in Beijing. Methods In this study, 24-h real-time indoor and ambient PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM2.5 mass concentration. Results Hourly ambient PM2.5 mass concentrations were 3–280 μg/m3 with a median of 58 μg/m3, and hourly indoor counterpart were 4–193 μg/m3 with a median of 34 μg/m3. The median indoor/ambient ratio of PM2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM2.5 mass concentrations on the community basis (coefficients: r≥0.90, p<0.0001), and the ambient data explained ≥84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM2.5 mass concentrations. Conclusions PM2.5 of ambient origin made dominant contribution to residential indoor PM2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM2.5 raised the concern of exposure misclassification when using ambient PM2.5 mass concentrations as exposure surrogates. PM2.5 of indoor origin still had minor influence on indoor PM2.5 mass concentrations, particularly at 11:00–13:00 and 22:00–0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models. PMID:26397734
Goldberg, Mark S; Wheeler, Amanda J; Burnett, Richard T; Mayo, Nancy E; Valois, Marie-France; Brophy, James M; Giannetti, Nadia
2015-01-01
We carried out this daily diary panel study in Montreal, Quebec, to determine whether oxygen saturation, pulse rate, blood pressure, self-rated health, and shortness of breath at night were associated with concentrations of indoor carbon monoxide (CO), and indoor and outdoor fine particles (PM2.5), temperature, and relative humidity. Over a 2-month consecutive period between 2008 and 2010, we measured daily indoor and outdoor levels of the air pollutants and weather variables and 55 subjects measured their daily health and other variables. To estimate the associations between the health outcomes and the environmental exposures, we used a mixed effects regression model using an autoregressive model of order-one and we adjusted for month and day and personal variables. The general pattern of associations can be summarized as follows: oxygen saturation was reduced for increases in indoor- and outdoor-PM2.5 and temperature. Pulse rate increased on the concurrent day for increases in indoor CO and PM2.5. Diastolic blood pressure increased with increasing indoor and outdoor PM2.5 and relative humidity. Systolic blood pressure increased with indoor PM2.5 and decreased with increasing indoor and outdoor temperature. Self-rated health diminished with increases in outdoor PM2.5 and indoor and outdoor temperature. Self-reported shortness of breath at night increased with increasing indoor and outdoor temperatures. Health in heart failure is affected in the short term by personal and environmental conditions that are manifest in intermediate physiological parameters.
Become an Indoor airPLUS Verifier
With the Indoor airPLUS Program, 3rd-party verifiers help ensure that EPA's high standards, based on leading building science, are applied by the builder during home design and construction to meet the Indoor airPLUS Construction Specifications.
VERIFICATION AND USES OF THE ENVIRONMENTAL PROTECTION AGENCY (EPA) INDOOR AIR QUALITY MODEL
The paper describes a set of experiments used to verify an indoor air quality (IAQ) model for estimating the impact of various pollution sources on IAQ in a multiroom building. he model treats each room as a well-mixed chamber that contains pollution sources and sinks. he model a...
NASA Astrophysics Data System (ADS)
Poerbo, Heru W.; Martokusumo, Widjaja; Donny Koerniawan, M.; Aulia Ardiani, Nissa; Krisanti, Susan
2017-12-01
The Local Government of Bandung city has stipulated a Green Building regulation through the Peraturan Walikota Number 1023/2016. Signed by the mayor in October 2016, Bandung became the first city in Indonesia that put green building as mandatory requirement in the building permit (IMB) process. Green Building regulation is intended to have more efficient consumption of energy and water, improved indoor air quality, management of liquid and solid waste etc. This objective is attained through various design method in building envelope, ventilation and air conditioning system, lighting, indoor transportation system, and electrical system. To minimize energy consumption of buildings that have large openings, sun shading device is often utilized together with low-E glass panes. For buildings in hot humid tropical climate, this method reduces indoor air temperature and thus requires less energy for air conditioning. Indoor air quality is often done by monitoring the carbon dioxide levels. Application of algae as part of building system façade has recently been introduced as replacement of large glass surface in the building façade. Algae are not yet included in the green building regulation because it is relatively new. The research will investigate, with the help of the modelling process and extensive literature, how effective is the implementation of algae in building façade to reduce energy consumption and improve its indoor air quality. This paper is written based on the design of ITB Innovation Park as an ongoing architectural design-based research how the algae-integrated building façade affects the energy consumption.
Jung, Jaehoon; Yoon, Sanghyun; Ju, Sungha; Heo, Joon
2015-01-01
The growing interest and use of indoor mapping is driving a demand for improved data-acquisition facility, efficiency and productivity in the era of the Building Information Model (BIM). The conventional static laser scanning method suffers from some limitations on its operability in complex indoor environments, due to the presence of occlusions. Full scanning of indoor spaces without loss of information requires that surveyors change the scanner position many times, which incurs extra work for registration of each scanned point cloud. Alternatively, a kinematic 3D laser scanning system, proposed herein, uses line-feature-based Simultaneous Localization and Mapping (SLAM) technique for continuous mapping. Moreover, to reduce the uncertainty of line-feature extraction, we incorporated constrained adjustment based on an assumption made with respect to typical indoor environments: that the main structures are formed of parallel or orthogonal line features. The superiority of the proposed constrained adjustment is its reduction for uncertainties of the adjusted lines, leading to successful data association process. In the present study, kinematic scanning with and without constrained adjustment were comparatively evaluated in two test sites, and the results confirmed the effectiveness of the proposed system. The accuracy of the 3D mapping result was additionally evaluated by comparison with the reference points acquired by a total station: the Euclidean average distance error was 0.034 m for the seminar room and 0.043 m for the corridor, which satisfied the error tolerance for point cloud acquisition (0.051 m) according to the guidelines of the General Services Administration for BIM accuracy. PMID:26501292
About the Subdivision of Indoor Spaces in Indoorgml
NASA Astrophysics Data System (ADS)
Diakité, A. A.; Zlatanova, S.; Li, K.-J.
2017-10-01
Boosted by the dynamic urbanization of cities, indoor environments are getting more and more complex in order to be able to host people properly. While most of our time is spent inside buildings, the need of GIS tools to assist our daily activities that can become tedious, such as indoor navigation or facility management, became more and more urgent. In that perspective, the IndoorGML standard is aiming to address the gaps left by other standards regarding the spatial modelling for indoor navigation. It includes several concepts such as the organization of the spaces into cells along with their network representation and the possibility to represent multiple connected layers. However, being at its first stage, several concepts of the standard could be improved. One of these is the cell subspacing that is not enough discussed in the current version of the standard. In this paper, we explore all the aspects involved in the subdivision process, from the identification of the navigable and non-navigable space cells to the generation of a navigation graph. We propose several criteria on which the indoor sub-spacing can rely to be automatically performed and and illustrate them on a 3D indoor model.
Koprivica, Mladen; Petrić, Majda; Nešković, Nataša; Nešković, Aleksandar
2016-01-01
To determine the level of radiofrequency radiation generated by base stations of Global System for Mobile Communications and Universal Mobile Telecommunication System, extensive electromagnetic field strength measurements were carried out in the vicinity of 664 base station locations. These were classified into three categories: indoor, masts, and locations with installations on buildings. Although microcell base stations with antennas installed indoors typically emit less power than outdoor macrocell base stations, the fact that people can be found close to antennas requires exposure originating from these base stations to be carefully considered. Measurement results showed that maximum recorded value of electric field strength exceeded International Commission on Non-Ionizing Radiation Protection reference levels at 7% of indoor base station locations. At the same time, this percentage was much lower in the case of masts and installations on buildings (0% and 2.5%, respectively). © 2015 Wiley Periodicals, Inc.
WSN based indoor air quality monitoring in classrooms
NASA Astrophysics Data System (ADS)
Wang, S. K.; Chew, S. P.; Jusoh, M. T.; Khairunissa, A.; Leong, K. Y.; Azid, A. A.
2017-03-01
Indoor air quality monitoring is essential as the human health is directly affected by indoor air quality. This paper presents the investigations of the impact of undergraduate students' concentration during lecture due to the indoor air quality in classroom. Three environmental parameters such as temperature, relative humidity and concentration of carbon dioxide are measured using wireless sensor network based air quality monitoring system. This simple yet reliable system is incorporated with DHT-11 and MG-811 sensors. Two classrooms were selected to install the monitoring system. The level of indoor air quality were measured and students' concentration was assessed using intelligent test during normal lecturing section. The test showed significant correlation between the collected environmental parameters and the students' level of performances in their study.
Wi-Fi/MARG Integration for Indoor Pedestrian Localization.
Tian, Zengshan; Jin, Yue; Zhou, Mu; Wu, Zipeng; Li, Ze
2016-12-10
With the wide deployment of Wi-Fi networks, Wi-Fi based indoor localization systems that are deployed without any special hardware have caught significant attention and have become a currently practical technology. At the same time, the Magnetic, Angular Rate, and Gravity (MARG) sensors installed in commercial mobile devices can achieve highly-accurate localization in short time. Based on this, we design a novel indoor localization system by using built-in MARG sensors and a Wi-Fi module. The innovative contributions of this paper include the enhanced Pedestrian Dead Reckoning (PDR) and Wi-Fi localization approaches, and an Extended Kalman Particle Filter (EKPF) based fusion algorithm. A new Wi-Fi/MARG indoor localization system, including an Android based mobile client, a Web page for remote control, and a location server, is developed for real-time indoor pedestrian localization. The extensive experimental results show that the proposed system is featured with better localization performance, with the average error 0.85 m, than the one achieved by using the Wi-Fi module or MARG sensors solely.
Secure positioning technique based on encrypted visible light map for smart indoor service
NASA Astrophysics Data System (ADS)
Lee, Yong Up; Jung, Gillyoung
2018-03-01
Indoor visible light (VL) positioning systems for smart indoor services are negatively affected by both cochannel interference from adjacent light sources and VL reception position irregularity in the three-dimensional (3-D) VL channel. A secure positioning methodology based on a two-dimensional (2-D) encrypted VL map is proposed, implemented in prototypes of the specific positioning system, and analyzed based on performance tests. The proposed positioning technique enhances the positioning performance by more than 21.7% compared to the conventional method in real VL positioning tests. Further, the pseudonoise code is found to be the optimal encryption key for secure VL positioning for this smart indoor service.
Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including air pollution concentrations; human activity patterns, such as the amount of time spent outdoors versus indoors, commuting, w...
INDOOR AIR QUALITY MODEL VERSION 1.0 DOCUMENTATION
The report presents a multiroom model for estimating the impact of various sources on indoor air quality (IAQ). The model is written for use on IBM-PC and compatible microcomputers. It is easy to use with a menu-driven user interface. Data are entered using a fill-in-a-form inter...
Shiue, Ivy
2015-07-01
It has been known that second-hand smoking and deprivation could cluster together affecting child health. However, little is known on the role of household smoking rules. Therefore, it was aimed to study the relationships among indoor second-hand smoking, household smoking rules, deprivation level and children mental health in a country-wide and population-based setting. Data was retrieved from and analysed in Scottish Health Survey, 2013. Information on demographics, indoor second-hand smoking status, household smoking rules, deprivation level and child mental health by Strengths and Difficulties Questionnaire was obtained by household interview through parents. Statistical analysis included chi-square test and survey-weighted logistic regression modelling. Of 1019 children aged 4-12, 17.9% (n = 182) lived in the 15% most deprivation areas. Deprived areas tended to be where indoor smoking occurred (p < 0.001). The top three sub-regions of the 15% most deprivation for Scottish children are greater Glasgow, Ayrshire & Arran and Forth Valley while the top three sub-regions of exposure to the indoor second-hand smoking are Fife, Forth Valley and Ayrshire & Arran. The top three sub-regions with indoor smoking allowed are greater Glasgow, Western Isles and Borders. Children emotional and behavioural problems were reduced when the strict household smoking rules (not allowed or outdoor areas) applied. One in six Scottish children lived in the 15% most deprivation areas and exposed to indoor second-hand smoking that could have led to emotional and behavioural problems. Public health programs promoting strict household smoking rules should be encouraged in order to optimise children mental health.
ERIC Educational Resources Information Center
Jon Schneller, Andrew; Schofield, Casey A.; Frank, Jenna; Hollister, Eliza; Mamuszka, Lauren
2015-01-01
This article reports on a mixed methods evaluation of an indoor garden-based learning curriculum for 5th and 6th graders which incorporated aquaponics and hydroponics technologies. This study provides a better understanding of the extent to which indoor gardening technologies can be used within the formal curriculum as an effective teaching tool.…
Simulation study on the impact of air distribution on formaldehyde pollutant distribution in room
NASA Astrophysics Data System (ADS)
Wu, Jingtao; Wang, Jun; Cheng, Zhu
2017-01-01
In this paper, physical and mathematical model of a room was established based on the Airpak software. The velocity distribution, air age distribution, formaldehyde concentration distribution and Predicted Mean Vote(PMV), Predicted Percentage Dissatisfied(PPD) distribution in the ward of a hospital were simulated. In addition, the air volume was doubled, the change of indoor pollutant concentration distribution was simulated. And further, the change of air age was simulated. Through the simulation, it can help arrange the position of the air supply port, so it is very necessary to increase the comfort of the staff in the room. Finally, through the simulation of pollutant concentration distribution, it can be seen that when concentration of indoor pollutants was high, the supply air flow rate should be increased appropriately. Indoor pollutant will be discharged as soon as possible, which is very beneficial to human body health.
A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass.
Sánchez, Jesús M; Carrera, Álvaro; Iglesias, Carlos Á; Serrano, Emilio
2016-08-24
Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation combines scenario-guided agents and humans equipped with Google Glass that coexist in a shared virtual space and jointly perform simulations. The paper proposes an architecture for participatory multiagent simulation in order to combine devices (Google Glass and/or smartphones) with an agent-based social simulator and indoor tracking services.
Kim, Sangmin; Kim, Jeonghyun; Jung, Jaehoon; Heo, Joon
2015-12-09
The cadastral system provides land ownership information by registering and representing land boundaries on a map. The current cadastral system in Korea, however, focuses mainly on the management of 2D land-surface boundaries. It is not yet possible to provide efficient or reliable land administration, as this 2D system cannot support or manage land information on 3D properties (including architectures and civil infrastructures) for both above-ground and underground facilities. A geometrical model of the 3D parcel, therefore, is required for registration of 3D properties. This paper, considering the role of the cadastral system, proposes a framework for a 3D underground cadastral system that can register various types of 3D underground properties using indoor mapping for as-built Building Information Modeling (BIM). The implementation consists of four phases: (1) geometric modeling of a real underground infrastructure using terrestrial laser scanning data; (2) implementation of as-built BIM based on geometric modeling results; (3) accuracy assessment for created as-built BIM using reference points acquired by total station; and (4) creation of three types of 3D underground cadastral map to represent underground properties. The experimental results, based on indoor mapping for as-built BIM, show that the proposed framework for a 3D underground cadastral system is able to register the rights, responsibilities, and restrictions corresponding to the 3D underground properties. In this way, clearly identifying the underground physical situation enables more reliable and effective decision-making in all aspects of the national land administration system.
Calibrated energy simulations of potential energy savings in actual retail buildings
NASA Astrophysics Data System (ADS)
Alhafi, Zuhaira
Retail stores are commercial buildings with high energy consumption due to their typically large volumes and long hours of operation. This dissertation assesses heating, ventilating and air conditioning saving strategies based on energy simulations with input parameters from actual retail buildings. The dissertation hypothesis is that "Retail store buildings will save a significant amount of energy by (1) modifying ventilation rates, and/or (2) resetting set point temperatures. These strategies have shown to be beneficial in previous studies. As presented in the literature review, potential energy savings ranged from 0.5% to 30% without compromising indoor thermal comfort and indoor air quality. The retail store buildings can be ventilated at rates significantly lower than rates called for in the ASHRAE Standard 62.1-2010 while maintaining acceptable indoor air quality. Therefore, two dissertation objectives are addressed: (1) Investigate opportunities to reduce ventilation rates that do not compromise indoor air quality in retail stores located in Central Pennsylvania, (2) Investigate opportunities to increase (in summer) and decrease (in winter) set point temperatures that do not compromise thermal comfort. This study conducted experimental measurements of ventilation rates required to maintain acceptable air quality and indoor environmental conditions requirements for two retail stores using ASHRAE Standard 62.1_2012. More specifically, among other parameters, occupancy density, indoor and outdoor pollutant concentrations, and indoor temperatures were measured continuously for one week interval. One of these retail stores were tested four times for a yearlong time period. Pollutants monitored were formaldehyde, carbon dioxide, particle size distributions and concentrations, as well as total volatile organic compounds. As a part of the base protocol, the number of occupants in each store was hourly counted during the test, and the results reveal that the occupant densities were approximately 20% to 30% of that called by ASHRAE 62.1. Formaldehyde was the most important contaminant of concern in retail stores investigated. Both stores exceeded the most conservative health guideline for formaldehyde (OEHHA TWA REL = 7.3 ppb). This study found that source removal and reducing the emission rate, as demonstrated in retail stores sampled in this study, is a viable strategy to meet the health guideline. Total volatile compound were present in retail stores at low concentrations well below health guidelines suggested by Molhave (1700microg /m 2) and Bridges (1000 microg /m2). Based on these results and through mass--balance modeling, different ventilation rate reduction scenarios were proposed, and for these scenarios the differences in energy consumption were estimated. Findings of all phases of this desertion have contributed to understanding (a) the trade-off between energy savings and ventilation rates that do not compromise indoor air quality, and (b) the trade-off between energy savings and resets of indoor air temperature that do not compromise thermal comfort. Two models for retail stores were built and calibrated and validated against actual utility bills. Energy simulation results indicated that by lowering the ventilation rates from measured and minimum references would reduce natural gas energy use by estimated values of 6% to 19%. Also, this study found that the electrical cooling energy consumption was not significantly sensitive to different ventilation rates. However, increasing indoor air temperature by 3°C in summer had a significant effect on the energy savings. In winter, both energy savings strategies, ventilation reduction and decrease in set points, had a significant effect on natural gas consumption. Specially, when the indoor air temperature 21°C was decreased to 19.4°C with the same amount of ventilation rate of Molhaves guideline for both cases. Interestingly, the temperature of 23.8°C (75°F), which is the lowest value of ASHRAE 55 thermal comfort for sedentary people (cashiers) and the highest value for thermal comfort adjustments due to activity level (customers and workers) that are calculated by using empirical equation, was the optimum temperature for sedentary and active people in Retail store buildings.
This program serves two purposes: (1) as a general-purpose indoor exposure model in buildings with multiple zones, multiple chemicals and multiple sources and sinks, and (2) as a special-purpose concentration model
AN INDOOR PESTICIDE AIR AND SURFACE CONCENTRATION MODEL
A thorough assessment of human exposure to environmental chemicals requires consideration of all processes in the sequence from source to dose. For assessment of exposure to pesticides following their use indoors, data and models are needed to estimate pesticide concentrations...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Buechler, Elizabeth D.; Pallin, Simon B.; Boudreaux, Philip R.
The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The
A FUGACITY-BASED INDOOR RESIDENTIAL PESTICIDE FATE MODEL
Dermal and non-dietary pathways are potentially significant exposure pathways to pesticides used in the home. Exposure pathways include dermal contact of pesticide residues with the hands and skin, ingestion from hand-to-mouth activities, ingestion through contact with toys an...
Mays, Darren; Tercyak, Kenneth P
2015-08-01
We investigated the impact of indoor tanning device warnings that communicate the risks associated with indoor tanning (i.e., loss framed) or the benefits of avoiding indoor tanning (i.e., gain framed). A convenience sample of non-Hispanic White women aged 18 to 30 years who tanned indoors at least once in the past year (n = 682) participated in a within-subjects experiment. Participants completed baseline measures and reported indoor tanning intentions and intentions to quit indoor tanning in response to 5 warning messages in random order. A text-only control warning was based on Food and Drug Administration-required warnings for indoor tanning devices. Experimental warnings included graphic content and were either gain or loss framed. In multivariable analyses, gain-framed warnings did not differ from the control warning on women's intentions to tan indoors, but they prompted stronger intentions to quit than the control message. Loss-framed warnings significantly reduced intentions to tan indoors and increased intentions to quit indoor tanning compared with control and gain-framed warnings. The public health impact of indoor tanning device warnings can be enhanced by incorporating graphic content and leveraging gain- and loss-framed messaging.
Ozone and limonene in indoor air: a source of submicron particle exposure.
Wainman, T; Zhang, J; Weschler, C J; Lioy, P J
2000-01-01
Little information currently exists regarding the occurrence of secondary organic aerosol formation in indoor air. Smog chamber studies have demonstrated that high aerosol yields result from the reaction of ozone with terpenes, both of which commonly occur in indoor air. However, smog chambers are typically static systems, whereas indoor environments are dynamic. We conducted a series of experiments to investigate the potential for secondary aerosol in indoor air as a result of the reaction of ozone with d-limonene, a compound commonly used in air fresheners. A dynamic chamber design was used in which a smaller chamber was nested inside a larger one, with air exchange occurring between the two. The inner chamber was used to represent a model indoor environment and was operated at an air exchange rate below 1 exchange/hr, while the outer chamber was operated at a high air exchange rate of approximately 45 exchanges/hr. Limonene was introduced into the inner chamber either by the evaporation of reagent-grade d-limonene or by inserting a lemon-scented, solid air freshener. A series of ozone injections were made into the inner chamber during the course of each experiment, and an optical particle counter was used to measure the particle concentration. Measurable particle formation and growth occurred almost exclusively in the 0.1-0.2 microm and 0.2-0.3 microm size fractions in all of the experiments. Particle formation in the 0.1-0.2 microm size range occurred as soon as ozone was introduced, but the formation of particles in the 0.2-0.3 microm size range did not occur until at least the second ozone injection occurred. The results of this study show a clear potential for significant particle concentrations to be produced in indoor environments as a result of secondary particle formation via the ozone-limonene reaction. Because people spend the majority of their time indoors, secondary particles formed in indoor environments may make a significant contribution to overall particle exposure. This study provides data for assessing the impact of outdoor ozone on indoor particles. This is important to determine the efficacy of the mass-based particulate matter standards in protecting public health because the indoor secondary particles can vary coincidently with the variations of outdoor fine particles in summer. PMID:11133393
Ozone and limonene in indoor air: a source of submicron particle exposure.
Wainman, T; Zhang, J; Weschler, C J; Lioy, P J
2000-12-01
Little information currently exists regarding the occurrence of secondary organic aerosol formation in indoor air. Smog chamber studies have demonstrated that high aerosol yields result from the reaction of ozone with terpenes, both of which commonly occur in indoor air. However, smog chambers are typically static systems, whereas indoor environments are dynamic. We conducted a series of experiments to investigate the potential for secondary aerosol in indoor air as a result of the reaction of ozone with d-limonene, a compound commonly used in air fresheners. A dynamic chamber design was used in which a smaller chamber was nested inside a larger one, with air exchange occurring between the two. The inner chamber was used to represent a model indoor environment and was operated at an air exchange rate below 1 exchange/hr, while the outer chamber was operated at a high air exchange rate of approximately 45 exchanges/hr. Limonene was introduced into the inner chamber either by the evaporation of reagent-grade d-limonene or by inserting a lemon-scented, solid air freshener. A series of ozone injections were made into the inner chamber during the course of each experiment, and an optical particle counter was used to measure the particle concentration. Measurable particle formation and growth occurred almost exclusively in the 0.1-0.2 microm and 0.2-0.3 microm size fractions in all of the experiments. Particle formation in the 0.1-0.2 microm size range occurred as soon as ozone was introduced, but the formation of particles in the 0.2-0.3 microm size range did not occur until at least the second ozone injection occurred. The results of this study show a clear potential for significant particle concentrations to be produced in indoor environments as a result of secondary particle formation via the ozone-limonene reaction. Because people spend the majority of their time indoors, secondary particles formed in indoor environments may make a significant contribution to overall particle exposure. This study provides data for assessing the impact of outdoor ozone on indoor particles. This is important to determine the efficacy of the mass-based particulate matter standards in protecting public health because the indoor secondary particles can vary coincidently with the variations of outdoor fine particles in summer.
Three Dimensional Vapor Intrusion Modeling: Model Validation and Uncertainty Analysis
NASA Astrophysics Data System (ADS)
Akbariyeh, S.; Patterson, B.; Rakoczy, A.; Li, Y.
2013-12-01
Volatile organic chemicals (VOCs), such as chlorinated solvents and petroleum hydrocarbons, are prevalent groundwater contaminants due to their improper disposal and accidental spillage. In addition to contaminating groundwater, VOCs may partition into the overlying vadose zone and enter buildings through gaps and cracks in foundation slabs or basement walls, a process termed vapor intrusion. Vapor intrusion of VOCs has been recognized as a detrimental source for human exposures to potential carcinogenic or toxic compounds. The simulation of vapor intrusion from a subsurface source has been the focus of many studies to better understand the process and guide field investigation. While multiple analytical and numerical models were developed to simulate the vapor intrusion process, detailed validation of these models against well controlled experiments is still lacking, due to the complexity and uncertainties associated with site characterization and soil gas flux and indoor air concentration measurement. In this work, we present an effort to validate a three-dimensional vapor intrusion model based on a well-controlled experimental quantification of the vapor intrusion pathways into a slab-on-ground building under varying environmental conditions. Finally, a probabilistic approach based on Monte Carlo simulations is implemented to determine the probability distribution of indoor air concentration based on the most uncertain input parameters.
Hillhouse, Joel; Turrisi, Rob; Cleveland, Michael J.; Scaglione, Nichole M.; Baker, Katie; Florence, L. Carter
2015-01-01
Background Younger indoor tanning initiation leads to greater melanoma risk due to more frequent and persistent behavior. Despite this, there are no published studies exploring the predictors of indoor tanning initiation in teen populations. Purpose This longitudinal study uses latent profile analysis to examine indoor tanning initiation in indoor tanning risk subgroups from a national sample of female adolescents. Methods Latent profile analysis used indoor tanning beliefs and perceptions to identify indoor tanning initiation risk subgroups. The teens in each subgroup were reassessed on indoor tanning initiation after a year. Results Three subgroups were identified: a low-risk, Anti-Tanning subgroup (18.6%) characterized by low scores on positive indoor tanning belief scales and high scores on beliefs about indoor tanning dangers; a moderate-risk Aware Social Tanner subgroup (47.2%) characterized by high scores on positive indoor tanning belief scales but also high scores on beliefs about indoor tanning dangers; and a high-risk Risky Relaxation Tanner subgroup (34.2%) characterized by high scores on positive indoor tanning belief scales and low scores on beliefs about indoor tanning dangers. Teens in the Aware Social Tanner and Risky Relaxation Tanner subgroups were significantly more likely to initiate indoor tanning in the following year. Conclusions These findings highlight the need to identify teens at risk for indoor tanning initiation and develop tailored interventions that will move them to the lowest risk subgroup. Subgroup correlates suggest parent and peer-based interventions may be successful. PMID:26370893
Hillhouse, Joel; Turrisi, Rob; Cleveland, Michael J; Scaglione, Nichole M; Baker, Katie; Florence, L Carter
2016-02-01
Younger indoor tanning initiation leads to greater melanoma risk due to more frequent and persistent behavior. Despite this, there are no published studies exploring the predictors of indoor tanning initiation in teen populations. This longitudinal study uses latent profile analysis to examine indoor tanning initiation in indoor tanning risk subgroups from a national sample of female adolescents. Latent profile analysis used indoor tanning beliefs and perceptions to identify indoor tanning initiation risk subgroups. The teens in each subgroup were reassessed on indoor tanning initiation after a year. Three subgroups were identified: a low risk, anti-tanning subgroup (18.6 %) characterized by low scores on positive indoor tanning belief scales and high scores on beliefs about indoor tanning dangers; a moderate risk aware social tanner subgroup (47.2 %) characterized by high scores on positive indoor tanning belief scales but also high scores on beliefs about indoor tanning dangers; and a high risk risky relaxation tanner subgroup (34.2 %) characterized by high scores on positive indoor tanning belief scales and low scores on beliefs about indoor tanning dangers. Teens in the aware social tanner and risky relaxation tanner subgroups were significantly more likely to initiate indoor tanning in the following year. These findings highlight the need to identify teens at risk for indoor tanning initiation and develop tailored interventions that will move them to the lowest risk subgroup. Subgroup correlates suggest parent and peer-based interventions may be successful.
High blood pressure and long-term exposure to indoor noise and air pollution from road traffic.
Foraster, Maria; Künzli, Nino; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Vila, Joan; Bouso, Laura; Deltell, Alexandre; Marrugat, Jaume; Ramos, Rafel; Sunyer, Jordi; Elosua, Roberto; Basagaña, Xavier
2014-11-01
Traffic noise has been associated with prevalence of hypertension, but reports are inconsistent for blood pressure (BP). To ascertain noise effects and to disentangle them from those suspected to be from traffic-related air pollution, it may be essential to estimate people's noise exposure indoors in bedrooms. We analyzed associations between long-term exposure to indoor traffic noise in bedrooms and prevalent hypertension and systolic (SBP) and diastolic (DBP) BP, considering long-term exposure to outdoor nitrogen dioxide (NO2). We evaluated 1,926 cohort participants at baseline (years 2003-2006; Girona, Spain). Outdoor annual average levels of nighttime traffic noise (Lnight) and NO2 were estimated at postal addresses with a detailed traffic noise model and a land-use regression model, respectively. Individual indoor traffic Lnight levels were derived from outdoor Lnight with application of insulations provided by reported noise-reducing factors. We assessed associations for hypertension and BP with multi-exposure logistic and linear regression models, respectively. Median levels were 27.1 dB(A) (indoor Lnight), 56.7 dB(A) (outdoor Lnight), and 26.8 μg/m3 (NO2). Spearman correlations between outdoor and indoor Lnight with NO2 were 0.75 and 0.23, respectively. Indoor Lnight was associated both with hypertension (OR = 1.06; 95% CI: 0.99, 1.13) and SBP (β = 0.72; 95% CI: 0.29, 1.15) per 5 dB(A); and NO2 was associated with hypertension (OR = 1.16; 95% CI: 0.99, 1.36), SBP (β = 1.23; 95% CI: 0.21, 2.25), and DBP (β⊇= 0.56; 95% CI: -0.03, 1.14) per 10 μg/m3. In the outdoor noise model, Lnight was associated only with hypertension and NO2 with BP only. The indoor noise-SBP association was stronger and statistically significant with a threshold at 30 dB(A). Long-term exposure to indoor traffic noise was associated with prevalent hypertension and SBP, independently of NO2. Associations were less consistent for outdoor traffic Lnight and likely affected by collinearity.
Analysis of the impact of sources on indoor pollutant concentrations and occupant exposure to indoor pollutants requires knowledge of the emission rates from the sources. Emission rates are often determined by chamber testing and the data from the chamber test are fitted to an em...
Ott, Wayne R; Klepeis, Neil E; Switzer, Paul
2003-08-01
This paper derives the analytical solutions to multi-compartment indoor air quality models for predicting indoor air pollutant concentrations in the home and evaluates the solutions using experimental measurements in the rooms of a single-story residence. The model uses Laplace transform methods to solve the mass balance equations for two interconnected compartments, obtaining analytical solutions that can be applied without a computer. Environmental tobacco smoke (ETS) sources such as the cigarette typically emit pollutants for relatively short times (7-11 min) and are represented mathematically by a "rectangular" source emission time function, or approximated by a short-duration source called an "impulse" time function. Other time-varying indoor sources also can be represented by Laplace transforms. The two-compartment model is more complicated than the single-compartment model and has more parameters, including the cigarette or combustion source emission rate as a function of time, room volumes, compartmental air change rates, and interzonal air flow factors expressed as dimensionless ratios. This paper provides analytical solutions for the impulse, step (Heaviside), and rectangular source emission time functions. It evaluates the indoor model in an unoccupied two-bedroom home using cigars and cigarettes as sources with continuous measurements of carbon monoxide (CO), respirable suspended particles (RSP), and particulate polycyclic aromatic hydrocarbons (PPAH). Fine particle mass concentrations (RSP or PM3.5) are measured using real-time monitors. In our experiments, simultaneous measurements of concentrations at three heights in a bedroom confirm an important assumption of the model-spatial uniformity of mixing. The parameter values of the two-compartment model were obtained using a "grid search" optimization method, and the predicted solutions agreed well with the measured concentration time series in the rooms of the home. The door and window positions in each room had considerable effect on the pollutant concentrations observed in the home. Because of the small volumes and low air change rates of most homes, indoor pollutant concentrations from smoking activity in a home can be very high and can persist at measurable levels indoors for many hours.
Research on Knowledge-Based Optimization Method of Indoor Location Based on Low Energy Bluetooth
NASA Astrophysics Data System (ADS)
Li, C.; Li, G.; Deng, Y.; Wang, T.; Kang, Z.
2017-09-01
With the rapid development of LBS (Location-based Service), the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1) The establishment and application of a priori and posterior knowledge base. 2) Primary selection of signal source. 3) Elimination of positioning gross error. 4) Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.
Penn, Lauren A.; Qian, Meng; Zhang, Enhan; Ng, Elise; Shao, Yongzhao; Berwick, Marianne; Lazovich, DeAnn; Polsky, David
2014-01-01
Background Identifying individuals at increased risk for melanoma could potentially improve public health through targeted surveillance and early detection. Studies have separately demonstrated significant associations between melanoma risk, melanocortin receptor (MC1R) polymorphisms, and indoor ultraviolet light (UV) exposure. Existing melanoma risk prediction models do not include these factors; therefore, we investigated their potential to improve the performance of a risk model. Methods Using 875 melanoma cases and 765 controls from the population-based Minnesota Skin Health Study we compared the predictive ability of a clinical melanoma risk model (Model A) to an enhanced model (Model F) using receiver operating characteristic (ROC) curves. Model A used self-reported conventional risk factors including mole phenotype categorized as “none”, “few”, “some” or “many” moles. Model F added MC1R genotype and measures of indoor and outdoor UV exposure to Model A. We also assessed the predictive ability of these models in subgroups stratified by mole phenotype (e.g. nevus-resistant (“none” and “few” moles) and nevus-prone (“some” and “many” moles)). Results Model A (the reference model) yielded an area under the ROC curve (AUC) of 0.72 (95% CI = 0.69, 0.74). Model F was improved with an AUC = 0.74 (95% CI = 0.71–0.76, p<0.01). We also observed substantial variations in the AUCs of Models A & F when examined in the nevus-prone and nevus-resistant subgroups. Conclusions These results demonstrate that adding genotypic information and environmental exposure data can increase the predictive ability of a clinical melanoma risk model, especially among nevus-prone individuals. PMID:25003831
Martínez-Sánchez, Jose M; Ballbè, Montse; Fu, Marcela; Martín-Sánchez, Juan C; Gottlieb, Mark; Saltó, Esteve; Vardavas, Constantine I; Daynard, Richard; Connolly, Gregory N; Fernández, Esteve
2014-01-01
Currently, there is an intensive debate about the regulation of the use of electronic cigarettes (e-cigarettes) in indoor places. The aim of this study was to assess the attitudes toward e-cigarette use in indoor workplaces and selected public and private venues among the general population in Barcelona (Spain) in 2013-2014. This is a cross-sectional study of a representative sample of the population of Barcelona (n = 736). The field work was conducted between May 2013 and February 2014. We computed the prevalence and the adjusted odds ratios (OR) derived from multivariable logistic regression models. The awareness of e-cigarettes was 82.3%. Forty five percent of respondents did not agree with the use of e-cigarettes in public places and 52.3% in workplaces. The proportion of disapproval of the use of e-cigarettes in indoor places was higher at 71.5% for schools and 65.8% for hospitals and health care centers; while the prevalence of disapproval of e-cigarette use in homes and cars was lower (18.0% and 32.5%, respectively). Respondents who disagreed on the use of e-cigarettes in indoor workplaces were more likely to be older (OR = 1.64 and 1.97 for groups 45-64 and ≧65 years old, respectively), those with a high educational level (OR = 1.60), and never and former smokers (OR = 2.34 and 2.16, respectively). Increased scores in the Fagerström test for cigarette dependence were also related to increased support for their use. Based on this population based study, half of the general population of Barcelona does not support the use of e-cigarettes in indoor workplaces and public places, with the percentage reaching 65% for use in schools, hospitals and health care centers. Consequently, there is good societal support in Spain for the politicians and legislators to promote policies restricting e-cigarettes use in workplaces and public places, including hospitality venues.
Martínez-Sánchez, Jose M.; Ballbè, Montse; Fu, Marcela; Martín-Sánchez, Juan C.; Gottlieb, Mark; Saltó, Esteve; Vardavas, Constantine I.; Daynard, Richard; Connolly, Gregory N.; Fernández, Esteve
2014-01-01
Background Currently, there is an intensive debate about the regulation of the use of electronic cigarettes (e-cigarettes) in indoor places. The aim of this study was to assess the attitudes toward e-cigarette use in indoor workplaces and selected public and private venues among the general population in Barcelona (Spain) in 2013–2014. Methods This is a cross-sectional study of a representative sample of the population of Barcelona (n = 736). The field work was conducted between May 2013 and February 2014. We computed the prevalence and the adjusted odds ratios (OR) derived from multivariable logistic regression models. Results The awareness of e-cigarettes was 82.3%. Forty five percent of respondents did not agree with the use of e-cigarettes in public places and 52.3% in workplaces. The proportion of disapproval of the use of e-cigarettes in indoor places was higher at 71.5% for schools and 65.8% for hospitals and health care centers; while the prevalence of disapproval of e-cigarette use in homes and cars was lower (18.0% and 32.5%, respectively). Respondents who disagreed on the use of e-cigarettes in indoor workplaces were more likely to be older (OR = 1.64 and 1.97 for groups 45–64 and ≧65 years old, respectively), those with a high educational level (OR = 1.60), and never and former smokers (OR = 2.34 and 2.16, respectively). Increased scores in the Fagerström test for cigarette dependence were also related to increased support for their use. Conclusions Based on this population based study, half of the general population of Barcelona does not support the use of e-cigarettes in indoor workplaces and public places, with the percentage reaching 65% for use in schools, hospitals and health care centers. Consequently, there is good societal support in Spain for the politicians and legislators to promote policies restricting e-cigarettes use in workplaces and public places, including hospitality venues. PMID:25469996
INDOOR AIR QUALITY AND INHALATION EXPOSURE - SIMULATION TOOL KIT
A Microsoft Windows-based indoor air quality (IAQ) simulation software package is presented. Named Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure, or IAQX for short, this package complements and supplements existing IAQ simulation programs and is desi...
Wei, Wenjuan; Xiong, Jianyin; Zhang, Yinping
2013-01-01
Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs) and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0), the diffusion coefficient (D), and the partition coefficient (K), can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.
Human Exposure Assessment for Air Pollution.
Han, Bin; Hu, Li-Wen; Bai, Zhipeng
2017-01-01
Assessment of human exposure to air pollution is a fundamental part of the more general process of health risk assessment. The measurement methods for exposure assessment now include personal exposure monitoring, indoor-outdoor sampling, mobile monitoring, and exposure assessment modeling (such as proximity models, interpolation model, air dispersion models, and land-use regression (LUR) models). Among these methods, personal exposure measurement is considered to be the most accurate method of pollutant exposure assessment until now, since it can better quantify observed differences and better reflect exposure among smaller groups of people at ground level. And since the great differences of geographical environment, source distribution, pollution characteristics, economic conditions, and living habits, there is a wide range of differences between indoor, outdoor, and individual air pollution exposure in different regions of China. In general, the indoor particles in most Chinese families comprise infiltrated outdoor particles, particles generated indoors, and a few secondary organic aerosol particles, and in most cases, outdoor particle pollution concentrations are a major contributor to indoor concentrations in China. Furthermore, since the time, energy, and expense are limited, it is difficult to measure the concentration of pollutants for each individual. In recent years, obtaining the concentration of air pollutants by using a variety of exposure assessment models is becoming a main method which could solve the problem of the increasing number of individuals in epidemiology studies.
Indoor anti-occlusion visible light positioning systems based on particle filtering
NASA Astrophysics Data System (ADS)
Jiang, Meng; Huang, Zhitong; Li, Jianfeng; Zhang, Ruqi; Ji, Yuefeng
2015-04-01
As one of the most popular categories of mobile services, a rapid growth of indoor location-based services has been witnessed over the past decades. Indoor positioning methods based on Wi-Fi, radio-frequency identification or Bluetooth are widely commercialized; however, they have disadvantages such as low accuracy or high cost. An emerging method using visible light is under research recently. The existed visible light positioning (VLP) schemes using carrier allocation, time allocation and multiple receivers all have limitations. This paper presents a novel mechanism using particle filtering in VLP system. By this method no additional devices are needed and the occlusion problem in visible light would be alleviated which will effectively enhance the flexibility for indoor positioning.
Kang, Hyun Gu; Quach, Lien; Li, Wenjun; Lipsitz, Lewis A
2013-09-01
Outdoor fallers differ from indoor fallers substantially in demographics, lifestyle, health condition and physical function. Biomechanical predictors of outdoor falls have not been well characterized. Current validated measures of postural deficits, which describe only the overall postural behavior, are predictive of indoor falls but not outdoor falls. We hypothesized that a model-based description of postural muscle tone and reflexes, particularly during dual tasking, would predict outdoor falls. We tested whether postural stiffness and damping from an inverted pendulum model were predictive of future indoor and outdoor falls among older adults from the MOBILIZE Boston Study. The center of pressure data during standing were obtained from 717 participants aged 77.9±5.3 years. Participants stood barefoot with eyes open for 30s per trial, in two sets of five standing trials. One set included a serial subtractions task. Postural stiffness and damping values were determined from the postural sway data. After the postural measurements, falls were monitored prospectively using a monthly mail-in calendar over 6-36 months. Associations of postural measures with fall rates were determined using negative binomial regressions. After covariate adjustments, postural stiffness (p=0.02-0.05) and damping (p=0.007-0.1) were associated with lower outdoor falls risk, but not with indoor falls. Results were invariant by direction (anteroposterior versus mediolateral) or by condition (quiet standing versus dual task). Outdoor fall risk may be tied to postural control more so than indoor falls. Dual tasking is likely related to fall risk among older and sicker older adults, but not those relatively healthy. Copyright © 2013 Elsevier B.V. All rights reserved.
Kang, Hyun Gu; Quach, Lien; Li, Wenjun; Lipsitz, Lewis A.
2013-01-01
Outdoor fallers differ from indoor fallers substantially in demographics, lifestyle, health condition and physical function. Biomechanical predictors of outdoor falls have not been well characterized. Current validated measures of postural deficits, which describe only the overall postural behavior, are predictive of indoor falls but not outdoor falls. We hypothesized that a model-based description of postural muscle tone and reflexes, particularly during dual tasking, would predict outdoor falls. We tested whether postural stiffness and damping from an inverted pendulum model were predictive of future indoor and outdoor falls among older adults from the MOBILIZE Boston Study. The center of pressure data during standing were obtained from 717 participants aged 77.9±5.3 years. Participants stood barefoot with eyes open for 30 seconds per trial, in two sets of five standing trials. One set included a serial subtractions task. Postural stiffness and damping values were determined from the postural sway data. After the postural measurements, falls were monitored prospectively using a monthly mail-in calendar over 6-36 months. Associations of postural measures with fall rates were determined using negative binomial regressions. After covariate adjustments, postural stiffness (p=0.02-0.05) and damping (p=0.007-0.1) were associated with lower outdoor falls risk, but not with indoor falls. Results were invariant by direction (anteroposterior versus mediolateral) or by condition (quiet standing versus dual task). Outdoor fall risk may be tied to postural control more so than indoor falls. Dual tasking is likely related to fall risk among older and sicker older adults, but not those relatively healthy. PMID:23623606
Duff, Putu; Shoveller, Jean; Dobrer, Sabina; Ogilvie, Gina; Montaner, Julio; Chettiar, Jill; Shannon, Kate
2015-01-01
Background This study aims to: report on a newly developed ‘Safer Indoor Work Environmental Scale’ that characterizes the social, policy and physical features of indoor venues and social cohesion; and using this scale, longitudinally evaluate the association between these features on sex workers’ (SWs’) condom use for pregnancy prevention. Methods Drawing on a prospective open cohort of female SWs working in indoor venues, a newly-developed ‘Safer Indoor Work Environment Scale’ was used to build six multivariable models with generalized estimating equations (GEE), to determine the independent effects of social, policy and venue-based features and social cohesion on condom use. Results Of 588 indoor SWs, 63.6% used condoms for pregnancy prevention in the last month. In multivariable GEE analysis, the following venue-based features were significantly correlated with barrier contraceptive use for pregnancy prevention: managerial practices and venue safety policies (Adjusted Odds Ratio (AOR)=1.09; 95% Confidence Interval (95%CI) 1.01–1.17) access to sexual and reproductive health services/supplies (AOR=1.10; 95%CI 1.00–1.20) access to drug harm reduction (AOR=1.13; 95%CI 1.01–1.28), and social cohesion among workers (AOR=1.05; 95%CI 1.03–1.07). Access to security features was marginally associated with condom use (AOR=1.13; 95%CI 0.99–1.29). Conclusion The findings of the current study highlight how work environment and social cohesion among SWs are related to improved condom use. Given global calls for the decriminalization of sex work, and potential legislative reforms in Canada, this study points to the critical need for new institutional arrangements (e.g., legal and regulatory frameworks; labour standards) to support safer sex workplaces. PMID:25678713
Duff, Putu; Shoveller, Jean; Dobrer, Sabina; Ogilvie, Gina; Montaner, Julio; Chettiar, Jill; Shannon, Kate
2015-07-01
This study aims to report on a newly developed Safer Indoor Work Environmental Scale that characterises the social, policy and physical features of indoor venues and social cohesion; and using this scale, longitudinally evaluate the association between these features on sex workers' (SWs') condom use for pregnancy prevention. Drawing on a prospective open cohort of female SWs working in indoor venues, a newly developed Safer Indoor Work Environment Scale was used to build six multivariable models with generalised estimating equations (GEE), to determine the independent effects of social, policy and physical venue-based features and social cohesion on condom use. Of 588 indoor SWs, 63.6% used condoms for pregnancy prevention in the last month. In multivariable GEE analysis, the following venue-based features were significantly correlated with barrier contraceptive use for pregnancy prevention: managerial practices and venue safety policies (adjusted OR (AOR)=1.09; 95% CI 1.01 to 1.17), access to sexual and reproductive health services/supplies (AOR=1.10; 95% CI 1.00 to 1.20), access to drug harm reduction (AOR=1.13; 95% CI 1.01 to 1.28) and social cohesion among workers (AOR=1.05; 95% CI 1.03 to 1.07). Access to security features was marginally associated with condom use (AOR=1.13; 95% CI 0.99 to 1.29). The findings of the current study highlight how work environment and social cohesion among SWs are related to improved condom use. Given global calls for the decriminalisation of sex work, and potential legislative reforms in Canada, this study points to the critical need for new institutional arrangements (eg, legal and regulatory frameworks; labour standards) to support safer sex workplaces. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua
2015-01-15
Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.
Improving UWB-Based Localization in IoT Scenarios with Statistical Models of Distance Error.
Monica, Stefania; Ferrari, Gianluigi
2018-05-17
Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices is exponentially growing. One of the application scenarios envisaged for IoT technologies involves indoor localization and context awareness. In this paper, we focus on a localization approach that relies on a particular type of communication technology, namely Ultra Wide Band (UWB). UWB technology is an attractive choice for indoor localization, owing to its high accuracy. Since localization algorithms typically rely on estimated inter-node distances, the goal of this paper is to evaluate the improvement brought by a simple (linear) statistical model of the distance error. On the basis of an extensive experimental measurement campaign, we propose a general analytical framework, based on a Least Square (LS) method, to derive a novel statistical model for the range estimation error between a pair of UWB nodes. The proposed statistical model is then applied to improve the performance of a few illustrative localization algorithms in various realistic scenarios. The obtained experimental results show that the use of the proposed statistical model improves the accuracy of the considered localization algorithms with a reduction of the localization error up to 66%.
Guy, Gery P; Zhang, Yuanhui; Ekwueme, Donatus U; Rim, Sun Hee; Watson, Meg
2017-02-01
Indoor tanning is associated with an increased risk of melanoma. The US Food and Drug Administration proposed prohibiting indoor tanning among minors younger than 18 years. We sought to estimate the health and economic benefits of reducing indoor tanning in the United States. We used a Markov model to estimate the expected number of melanoma cases and deaths averted, life-years saved, and melanoma treatment costs saved by reducing indoor tanning. We examined 5 scenarios: restricting indoor tanning among minors younger than 18 years, and reducing the prevalence by 20%, 50%, 80%, and 100%. Restricting indoor tanning among minors younger than 18 years was estimated to prevent 61,839 melanoma cases, prevent 6735 melanoma deaths, and save $342.9 million in treatment costs over the lifetime of the 61.2 million youth age 14 years or younger in the United States. The estimated health and economic benefits increased as indoor tanning was further reduced. Limitations include the reliance on available data and not examining compliance to indoor tanning laws. Reducing indoor tanning has the potential to reduce melanoma incidence, mortality, and treatment costs. These findings help quantify and underscore the importance of continued efforts to reduce indoor tanning and prevent melanoma. Published by Elsevier Inc.
Indoor air quality: A psychosocial perspective
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boxer, P.A.
1990-05-01
The incidence of indoor air quality problems has increased dramatically over the past decade. Investigation of these problems has yielded a definitive cause in only one third of the cases. Psychosocial factors may play a key role in the development and propagation of symptoms attributed to poor indoor air quality. Guidelines for managing indoor air quality problems from the organizational perspective are based upon psychosocial principles and elements of risk perception.
Exposure to Indoor Tanning Without Burning and Melanoma Risk by Sunburn History
Vogel, Rachel Isaksson; Ahmed, Rehana L.; Nelson, Heather H.; Berwick, Marianne; Weinstock, Martin A.
2014-01-01
Indoor tanning is carcinogenic to humans. Individuals report that they tan indoors before planning to be in the sun to prevent sunburns, but whether skin cancer is subsequently reduced is unknown. Using a population-based case–control study, we calculated the association between melanoma and indoor tanning after excluding exposed participants reporting indoor tanning–related burns, stratified by their number of lifetime sunburns (0, 1–2, 3–5, >5). Confounding was addressed using propensity score analysis methods. All statistical tests were two-sided. We observed increased risk of melanoma across all sunburn categories for participants who had tanned indoors without burning compared with those who never tanned indoors, including those who reported zero lifetime sunburns (odds ratio = 3.87; 95% confidence interval = 1.68 to 8.91; P = .002). These data provide evidence that indoor tanning is a risk factor for melanoma even among persons who reported never experiencing burns from indoor tanning or outdoor sun exposure. PMID:25031276
Exposure to Indoor Tanning Without Burning and Melanoma Risk by Sunburn History
Vogel, Rachel Isaksson; Ahmed, Rehana L.; Nelson, Heather H.; Berwick, Marianne; Weinstock, Martin A.
2014-01-01
Indoor tanning is carcinogenic to humans. Individuals report that they tan indoors before planning to be in the sun to prevent sunburns, but whether skin cancer is subsequently reduced is unknown. Using a population-based case–control study, we calculated the association between melanoma and indoor tanning after excluding exposed participants reporting indoor tanning–related burns, stratified by their number of lifetime sunburns (0, 1–2, 3–5, >5). Confounding was addressed using propensity score analysis methods. All statistical tests were two-sided. We observed increased risk of melanoma across all sunburn categories for participants who had tanned indoors without burning compared with those who never tanned indoors, including those who reported zero lifetime sunburns (odds ratio = 3.87; 95% confidence interval = 1.68 to 8.91; P = .002). These data provide evidence that indoor tanning is a risk factor for melanoma even among persons who reported never experiencing burns from indoor tanning or outdoor sun exposure. PMID:24872541
Measurements and numerical simulations of indoor O 3 and NO x in two different cases
NASA Astrophysics Data System (ADS)
Drakou, G.; Zerefos, C.; Ziomas, I.; Voyatzaki, M.
Simultaneous indoor and outdoor measurements of O 3, NO, NO 2* (NO xsbnd NO) that lasted a lot of days, took place in two buildings and were also accompanied by other environmental measurements. The two buildings have bright natural sunlight, similar dimensions but many differences in their design and operation, as well as a different way of ventilation. The one is located in Thessaloniki (LIDAR) while the other is in Athens (PERPA), a city with a much higher level of air pollution. In the PERPA-bldg., indications of hydrocarbon intrusion from an adjacent chemical laboratory were observed. The differences between these two buildings are reflected in the change of behavior of the indoor/outdoor O 3, NO, NO 2* concentration ratios. In the LIDAR-bldg. there were elevated O 3 and NO 2* ratios combined with small NO ratios. At the PERPA-bldg. the corresponding ratios, mainly for O 3, were influenced for long period by the indoor VOCs source. The O 3 concentration ratios are representative of the building's design, operation and location in case of naturally ventilated and lighted buildings. Also they are a sensitive indicator of the existence of indoor VOCs source. The 24 h peak indoor/outdoor NO concentration ratios reflected the differences between the buildings' air exchange rate, but the 24 h averaged NO ratios seems unaffected by any indoor air quality parameter in this study. The NO 2* measurements include the contribution of other nitrogen-containing species, which seems to vary with the building characteristics and with time. With the acquired experimental data for this type of interior locations, the Nazaroff and Cass (1986) mathematical model was tested, which predicts the indoor air pollutant concentrations. The model's results were satisfactory. In addition, it was possible for the theoretical investigation into the causes of the formation of the observed indoor air pollutant concentrations to be undertaken. The indoor NO x chemistry is not affected only by homogeneous but also by heterogeneous reactions, as shown by model results.
Automatically Determining Scale Within Unstructured Point Clouds
NASA Astrophysics Data System (ADS)
Kadamen, Jayren; Sithole, George
2016-06-01
Three dimensional models obtained from imagery have an arbitrary scale and therefore have to be scaled. Automatically scaling these models requires the detection of objects in these models which can be computationally intensive. Real-time object detection may pose problems for applications such as indoor navigation. This investigation poses the idea that relational cues, specifically height ratios, within indoor environments may offer an easier means to obtain scales for models created using imagery. The investigation aimed to show two things, (a) that the size of objects, especially the height off ground is consistent within an environment, and (b) that based on this consistency, objects can be identified and their general size used to scale a model. To test the idea a hypothesis is first tested on a terrestrial lidar scan of an indoor environment. Later as a proof of concept the same test is applied to a model created using imagery. The most notable finding was that the detection of objects can be more readily done by studying the ratio between the dimensions of objects that have their dimensions defined by human physiology. For example the dimensions of desks and chairs are related to the height of an average person. In the test, the difference between generalised and actual dimensions of objects were assessed. A maximum difference of 3.96% (2.93cm) was observed from automated scaling. By analysing the ratio between the heights (distance from the floor) of the tops of objects in a room, identification was also achieved.
Developing a database for pedestrians' earthquake emergency evacuation in indoor scenarios.
Zhou, Junxue; Li, Sha; Nie, Gaozhong; Fan, Xiwei; Tan, Jinxian; Li, Huayue; Pang, Xiaoke
2018-01-01
With the booming development of evacuation simulation software, developing an extensive database in indoor scenarios for evacuation models is imperative. In this paper, we conduct a qualitative and quantitative analysis of the collected videotapes and aim to provide a complete and unitary database of pedestrians' earthquake emergency response behaviors in indoor scenarios, including human-environment interactions. Using the qualitative analysis method, we extract keyword groups and keywords that code the response modes of pedestrians and construct a general decision flowchart using chronological organization. Using the quantitative analysis method, we analyze data on the delay time, evacuation speed, evacuation route and emergency exit choices. Furthermore, we study the effect of classroom layout on emergency evacuation. The database for indoor scenarios provides reliable input parameters and allows the construction of real and effective constraints for use in software and mathematical models. The database can also be used to validate the accuracy of evacuation models.
Wi-Fi/MARG Integration for Indoor Pedestrian Localization
Tian, Zengshan; Jin, Yue; Zhou, Mu; Wu, Zipeng; Li, Ze
2016-01-01
With the wide deployment of Wi-Fi networks, Wi-Fi based indoor localization systems that are deployed without any special hardware have caught significant attention and have become a currently practical technology. At the same time, the Magnetic, Angular Rate, and Gravity (MARG) sensors installed in commercial mobile devices can achieve highly-accurate localization in short time. Based on this, we design a novel indoor localization system by using built-in MARG sensors and a Wi-Fi module. The innovative contributions of this paper include the enhanced Pedestrian Dead Reckoning (PDR) and Wi-Fi localization approaches, and an Extended Kalman Particle Filter (EKPF) based fusion algorithm. A new Wi-Fi/MARG indoor localization system, including an Android based mobile client, a Web page for remote control, and a location server, is developed for real-time indoor pedestrian localization. The extensive experimental results show that the proposed system is featured with better localization performance, with the average error 0.85 m, than the one achieved by using the Wi-Fi module or MARG sensors solely. PMID:27973412
Indoor Residence Times of Semivolatile Organic Compounds: Model Estimation and Field Evaluation
Indoor residence times of semivolatile organic compounds (SVOCs) are a major and mostly unavailable input for residential exposure assessment. We calculated residence times for a suite of SVOCs using a fugacity model applied to residential environments. Residence times depend on...
Indoor source apportionment in urban communities near industrial sites
NASA Astrophysics Data System (ADS)
Tunno, Brett J.; Dalton, Rebecca; Cambal, Leah; Holguin, Fernando; Lioy, Paul; Clougherty, Jane E.
2016-08-01
Because fine particulate matter (PM2.5) differs in chemical composition, source apportionment is frequently used for identification of relative contributions of multiple sources to outdoor concentrations. Indoor air pollution and source apportionment is often overlooked, though people in northern climates may spend up to 90% of their time inside. We selected 21 homes for a 1-week indoor sampling session during summer (July to September 2011), repeated in winter (January to March 2012). Elemental analysis was performed using inductively-coupled plasma mass spectrometry (ICP-MS), and factor analysis was used to determine constituent grouping. Multivariate modeling was run on factor scores to corroborate interpretations of source factors based on a literature review. For each season, a 5-factor solution explained 86-88% of variability in constituent concentrations. Indoor sources (i.e. cooking, smoking) explained greater variability than did outdoor sources in these industrial communities. A smoking factor was identified in each season, predicted by number of cigarettes smoked. Cooking factors were also identified in each season, explained by frequency of stove cooking and stovetop frying. Significant contributions from outdoor sources including coal and motor vehicles were also identified. Higher coal and secondary-related elemental concentrations were detected during summer than winter. Our findings suggest that source contributions to indoor concentrations can be identified and should be examined in relation to health effects.
Quantile regression and Bayesian cluster detection to identify radon prone areas.
Sarra, Annalina; Fontanella, Lara; Valentini, Pasquale; Palermi, Sergio
2016-11-01
Albeit the dominant source of radon in indoor environments is the geology of the territory, many studies have demonstrated that indoor radon concentrations also depend on dwelling-specific characteristics. Following a stepwise analysis, in this study we propose a combined approach to delineate radon prone areas. We first investigate the impact of various building covariates on indoor radon concentrations. To achieve a more complete picture of this association, we exploit the flexible formulation of a Bayesian spatial quantile regression, which is also equipped with parameters that controls the spatial dependence across data. The quantitative knowledge of the influence of each significant building-specific factor on the measured radon levels is employed to predict the radon concentrations that would have been found if the sampled buildings had possessed standard characteristics. Those normalised radon measures should reflect the geogenic radon potential of the underlying ground, which is a quantity directly related to the geological environment. The second stage of the analysis is aimed at identifying radon prone areas, and to this end, we adopt a Bayesian model for spatial cluster detection using as reference unit the building with standard characteristics. The case study is based on a data set of more than 2000 indoor radon measures, available for the Abruzzo region (Central Italy) and collected by the Agency of Environmental Protection of Abruzzo, during several indoor radon monitoring surveys. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass
Sánchez, Jesús M.; Carrera, Álvaro; Iglesias, Carlos Á.; Serrano, Emilio
2016-01-01
Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation combines scenario-guided agents and humans equipped with Google Glass that coexist in a shared virtual space and jointly perform simulations. The paper proposes an architecture for participatory multiagent simulation in order to combine devices (Google Glass and/or smartphones) with an agent-based social simulator and indoor tracking services. PMID:27563911
NASA Astrophysics Data System (ADS)
Johnson, Markey M.; Williams, Ron; Fan, Zhihua; Lin, Lin; Hudgens, Edward; Gallagher, Jane; Vette, Alan; Neas, Lucas; Özkaynak, Halûk
2010-12-01
The Mechanistic Indicators of Childhood Asthma (MICA) study in Detroit, Michigan introduced a participant-based approach to reduce the resource burden associated with collection of indoor and outdoor residential air sampling data. A subset of participants designated as MICA-Air conducted indoor and outdoor residential sampling of nitrogen dioxide (NO 2), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs). This participant-based methodology was subsequently adapted for use in the Vanguard phase of the U.S. National Children's Study. The current paper examines residential indoor and outdoor concentrations of these pollutant species among health study participants in Detroit, Michigan. Pollutants measured under MICA-Air agreed well with other studies and continuous monitoring data collected in Detroit. For example, NO 2 and BTEX concentrations reported for other Detroit area monitoring were generally within 10-15% of indoor and outdoor concentrations measured in MICA-Air households. Outdoor NO 2 concentrations were typically higher than indoor NO 2 concentration among MICA-Air homes, with a median indoor/outdoor (I/O) ratio of 0.6 in homes that were not impacted by environmental tobacco smoke (ETS) during air sampling. Indoor concentrations generally exceeded outdoor concentrations for VOC and PAH species measured among non-ETS homes in the study. I/O ratios for BTEX species (benzene, toluene, ethylbenzene, and m/p- and o-xylene) ranged from 1.2 for benzene to 3.1 for toluene. Outdoor NO 2 concentrations were approximately 4.5 ppb higher on weekdays versus weekends. As expected, I/O ratios pollutants were generally higher for homes impacted by ETS. These findings suggest that participant-based air sampling can provide a cost-effective alternative to technician-based approaches for assessing indoor and outdoor residential air pollution in community health studies. We also introduced a technique for estimating daily concentrations at each home by weighting 2- and 7-day integrated concentrations using continuous measurements from regulatory monitoring sites. This approach may be applied to estimate short-term daily or hourly pollutant concentrations in future health studies.
Talley, Anna E.; Fromme, Kim
2016-01-01
Introduction: Almost one-third of college students report recent cigarette use, primarily as “social smoking,” and often in conjunction with alcohol use. While city-wide indoor smoking bans effectively reduce the number of social opportunities to smoke (eg, bars and music clubs), little is known about how these bans may impact the smoking behaviors of college students. Furthermore, nothing is known about how indoor smoking bans may impact students’ drinking behaviors. The current study aims to determine the impact of a city-wide comprehensive indoor smoking ban on smoking and alcohol behaviors among a longitudinal sample of emerging adults. Methods: Data are from a 6-year longitudinal study (10 waves of data collection) that began the summer before college enrollment. Participants (N = 2244; 60% female) reported on their past 3-month smoking and drinking behaviors using Internet-based surveys at each wave. Piecewise linear growth modeling was used to determine how a city-wide comprehensive indoor smoking ban (implemented in the Fall of 2005 between Waves 4 and 5) impacted smoking frequency, cigarette quantity, drinking frequency, and number of binge drinking episodes. Results: Smoking and alcohol use increased from the summer before college through the semester before implementation of the city-wide smoking ban. While smoking frequency (P < .001) and cigarette quantity (P < .05) declined after the ban, drinking frequency increased (P < .001) and the number of binge drinking episodes remained stable. Conclusions: Current findings suggest that comprehensive indoor smoking bans can influence the smoking behaviors of emerging adults, whereas trajectories of drinking are relatively unchanged. PMID:25744964
An Indoor Positioning Method for Smartphones Using Landmarks and PDR.
Wang, Xi; Jiang, Mingxing; Guo, Zhongwen; Hu, Naijun; Sun, Zhongwei; Liu, Jing
2016-12-15
Recently location based services (LBS) have become increasingly popular in indoor environments. Among these indoor positioning techniques providing LBS, a fusion approach combining WiFi-based and pedestrian dead reckoning (PDR) techniques is drawing more and more attention of researchers. Although this fusion method performs well in some cases, it still has some limitations, such as heavy computation and inconvenience for real-time use. In this work, we study map information of a given indoor environment, analyze variations of WiFi received signal strength (RSS), define several kinds of indoor landmarks, and then utilize these landmarks to correct accumulated errors derived from PDR. This fusion scheme, called Landmark-aided PDR (LaP), is proved to be light-weight and suitable for real-time implementation by running an Android application designed for the experiment. We compared LaP with other PDR-based fusion approaches. Experimental results show that the proposed scheme can achieve a significant improvement with an average accuracy of 2.17 m.
An Indoor Positioning Method for Smartphones Using Landmarks and PDR †
Wang, Xi; Jiang, Mingxing; Guo, Zhongwen; Hu, Naijun; Sun, Zhongwei; Liu, Jing
2016-01-01
Recently location based services (LBS) have become increasingly popular in indoor environments. Among these indoor positioning techniques providing LBS, a fusion approach combining WiFi-based and pedestrian dead reckoning (PDR) techniques is drawing more and more attention of researchers. Although this fusion method performs well in some cases, it still has some limitations, such as heavy computation and inconvenience for real-time use. In this work, we study map information of a given indoor environment, analyze variations of WiFi received signal strength (RSS), define several kinds of indoor landmarks, and then utilize these landmarks to correct accumulated errors derived from PDR. This fusion scheme, called Landmark-aided PDR (LaP), is proved to be light-weight and suitable for real-time implementation by running an Android application designed for the experiment. We compared LaP with other PDR-based fusion approaches. Experimental results show that the proposed scheme can achieve a significant improvement with an average accuracy of 2.17 m. PMID:27983670
Automatic Construction of Wi-Fi Radio Map Using Smartphones
NASA Astrophysics Data System (ADS)
Liu, Tao; Li, Qingquan; Zhang, Xing
2016-06-01
Indoor positioning could provide interesting services and applications. As one of the most popular indoor positioning methods, location fingerprinting determines the location of mobile users by matching the received signal strength (RSS) which is location dependent. However, fingerprinting-based indoor positioning requires calibration and updating of the fingerprints which is labor-intensive and time-consuming. In this paper, we propose a visual-based approach for the construction of radio map for anonymous indoor environments without any prior knowledge. This approach collects multi-sensors data, e.g. video, accelerometer, gyroscope, Wi-Fi signals, etc., when people (with smartphones) walks freely in indoor environments. Then, it uses the multi-sensor data to restore the trajectories of people based on an integrated structure from motion (SFM) and image matching method, and finally estimates location of sampling points on the trajectories and construct Wi-Fi radio map. Experiment results show that the average location error of the fingerprints is about 0.53 m.
Tercyak, Kenneth P.
2015-01-01
Objectives. We investigated the impact of indoor tanning device warnings that communicate the risks associated with indoor tanning (i.e., loss framed) or the benefits of avoiding indoor tanning (i.e., gain framed). Methods. A convenience sample of non-Hispanic White women aged 18 to 30 years who tanned indoors at least once in the past year (n = 682) participated in a within-subjects experiment. Participants completed baseline measures and reported indoor tanning intentions and intentions to quit indoor tanning in response to 5 warning messages in random order. A text-only control warning was based on Food and Drug Administration–required warnings for indoor tanning devices. Experimental warnings included graphic content and were either gain or loss framed. Results. In multivariable analyses, gain-framed warnings did not differ from the control warning on women’s intentions to tan indoors, but they prompted stronger intentions to quit than the control message. Loss-framed warnings significantly reduced intentions to tan indoors and increased intentions to quit indoor tanning compared with control and gain-framed warnings. Conclusions. The public health impact of indoor tanning device warnings can be enhanced by incorporating graphic content and leveraging gain- and loss-framed messaging. PMID:26066932
The indoor environment has not been fully incorporated into the environmental justice dialogue. To inform strategies to reduce disparities, we developed a framework to identify the individual and place-based drivers of indoor environment quality. We reviewed empirical evidence...
Design and indoor testing of a compact optical concentrator
NASA Astrophysics Data System (ADS)
Zheng, Cheng; Li, Qiyuan; Rosengarten, Gary; Hawkes, Evatt; Taylor, Robert A.
2017-01-01
We propose and analyze designs for stationary and compact optical concentrators. The designs are based on a catadioptric assembly with a linear focus line. They have a focal distance of around 10 to 15 cm with a concentration ratio (4.5 to 5.9 times). The concentrator employs an internal linear-tracking mechanism, making it suitable for rooftop solar applications. The optical performance of the collector has been simulated with ray tracing software (Zemax), and laser-based indoor experiments were carried out to validate this model. The results show that the system is capable of achieving an average optical efficiency of around 66% to 69% during the middle 6 (sunniest) h of the day. The design process and principles described in this work will help enable a new class of rooftop solar thermal concentrators.
NASA Astrophysics Data System (ADS)
Mitilineos, Stelios A.; Argyreas, Nick D.; Thomopoulos, Stelios C. A.
2009-05-01
A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.
Adsorption of Phthalates on Impervious Indoor Surfaces.
Wu, Yaoxing; Eichler, Clara M A; Leng, Weinan; Cox, Steven S; Marr, Linsey C; Little, John C
2017-03-07
Sorption of semivolatile organic compounds (SVOCs) onto interior surfaces, often referred to as the "sink effect", and their subsequent re-emission significantly affect the fate and transport of indoor SVOCs and the resulting human exposure. Unfortunately, experimental challenges and the large number of SVOC/surface combinations have impeded progress in understanding sorption of SVOCs on indoor surfaces. An experimental approach based on a diffusion model was thus developed to determine the surface/air partition coefficient K of di-2-ethylhexyl phthalate (DEHP) on typical impervious surfaces including aluminum, steel, glass, and acrylic. The results indicate that surface roughness plays an important role in the adsorption process. Although larger data sets are needed, the ability to predict K could be greatly improved by establishing the nature of the relationship between surface roughness and K for clean indoor surfaces. Furthermore, different surfaces exhibit nearly identical K values after being exposed to kitchen grime with values that are close to those reported for the octanol/air partition coefficient. This strongly supports the idea that interactions between gas-phase DEHP and soiled surfaces have been reduced to interactions with an organic film. Collectively, the results provide an improved understanding of equilibrium partitioning of SVOCs on impervious surfaces.
NASA Astrophysics Data System (ADS)
Murga, Alicia; Sano, Yusuke; Kawamoto, Yoichi; Ito, Kazuhide
2017-10-01
Mechanical and passive ventilation strategies directly impact indoor air quality. Passive ventilation has recently become widespread owing to its ability to reduce energy demand in buildings, such as the case of natural or cross ventilation. To understand the effect of natural ventilation on indoor environmental quality, outdoor-indoor flow paths need to be analyzed as functions of urban atmospheric conditions, topology of the built environment, and indoor conditions. Wind-driven natural ventilation (e.g., cross ventilation) can be calculated through the wind pressure coefficient distributions of outdoor wall surfaces and openings of a building, allowing the study of indoor air parameters and airborne contaminant concentrations. Variations in outside parameters will directly impact indoor air quality and residents' health. Numerical modeling can contribute to comprehend these various parameters because it allows full control of boundary conditions and sampling points. In this study, numerical weather prediction modeling was used to calculate wind profiles/distributions at the atmospheric scale, and computational fluid dynamics was used to model detailed urban and indoor flows, which were then integrated into a dynamic downscaling analysis to predict specific urban wind parameters from the atmospheric to built-environment scale. Wind velocity and contaminant concentration distributions inside a factory building were analyzed to assess the quality of the human working environment by using a computer simulated person. The impact of cross ventilation flows and its variations on local average contaminant concentration around a factory worker, and inhaled contaminant dose, were then discussed.
Refining Time-Activity Classification of Human Subjects Using the Global Positioning System.
Hu, Maogui; Li, Wei; Li, Lianfa; Houston, Douglas; Wu, Jun
2016-01-01
Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well with just GPS, road and tax parcel data. However, caution is warranted when generalizing the model developed from a small number of subjects to other populations.
FUNDAMENTAL MASS TRANSFER MODEL FOR INDOOR AIR EMISSIONS FROM SURFACE COATINGS
Emissions from freshly applied paints and other coatings can cause elevated indoor concentrations of vapor-phase organics. Methods are needed to determine the emission rates over time for these products. Some success has been achieved using simple first-order decay models to eval...
COMPARISON OF DATA FROM AN IAQ TEST HOUSE WITH PREDICTIONS OF AN IAQ COMPUTER MODEL
The paper describes several experiments to evaluate the impact of indoor air pollutant sources on indoor air quality (IAQ). Measured pollutant concentrations are compared with concentrations predicted by an IAQ model. The measured concentrations are in excellent agreement with th...
The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work.
Torres-Sospedra, Joaquín; Jiménez, Antonio R; Knauth, Stefan; Moreira, Adriano; Beer, Yair; Fetzer, Toni; Ta, Viet-Cuong; Montoliu, Raul; Seco, Fernando; Mendoza-Silva, Germán M; Belmonte, Oscar; Koukofikis, Athanasios; Nicolau, Maria João; Costa, António; Meneses, Filipe; Ebner, Frank; Deinzer, Frank; Vaufreydaz, Dominique; Dao, Trung-Kien; Castelli, Eric
2017-03-10
This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors' estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described.
Effects of moisture controlled charcoal on indoor thermal and air environments
NASA Astrophysics Data System (ADS)
Matsumoto, Hiroshi; Yokogoshi, Midori; Nabeshima, Yuki
2017-10-01
It is crucial to remove and control indoor moisture in Japan, especially in hot and humid summers, in order to improve thermal comfort and save energy in buildings. Charcoal for moisture control made from the waste of wood material has attracted attention among many control strategies to control indoor moisture, and it is beginning to be used in houses. However, the basic characteristics of the charcoal to control moisture and remove chemical compounds in indoor air have not been investigated sufficiently. The objective of this study is to clarify the effect of moisture control charcoal on indoor thermal and air environments by a long-term field measurement using two housing scale models with/without charcoal in Toyohashi, Japan. The comparative experiments to investigate the effect of the charcoal on air temperature and humidity for two models with/without charcoal were conducted from 2015 to 2016. Also, the removal performance of volatile organic compound (VOCs) was investigated in the summer of 2015. Four bags of packed charcoal were set on the floor in the attic for one model during the experiment. As a result of the experiments, a significant effect of moisture control was observed in hot and humid season, and the efficient effect of moisture adsorption was obtained by the periodic humidification experiment using a humidifier. Furthermore, the charcoal showed a remarkable performance of VOC removal from indoor air by the injection experiment of formaldehyde.
40 CFR 35.702 - Basis for allotment.
Code of Federal Regulations, 2010 CFR
2010-07-01
... STATE AND LOCAL ASSISTANCE Environmental Program Grants for Tribes Indoor Radon Grants (section 306) § 35.702 Basis for allotment. (a) The Regional Administrator will allot Indoor Radon Grant funds based... Control Act. (b) No Tribe or Intertribal Consortium may receive an Indoor Radon Grant in excess of 10...
40 CFR 35.292 - Basis for allotment.
Code of Federal Regulations, 2010 CFR
2010-07-01
... STATE AND LOCAL ASSISTANCE Environmental Program Grants State Indoor Radon Grants (section 306) § 35.292 Basis for allotment. (a) The Regional Administrator will allot State Indoor Radon Grant funds based on... Control Act. (b) No State may receive a State Indoor Radon Grant in excess of 10 percent of the total...
SIMULATION TOOL KIT FOR INDOOR AIR QUALITY AND INHALATION EXPOSURE (IAQX) VERSION 1.0 USER'S GUIDE
The User's Guide describes a Microsoft Windows-based indoor air quality (IAQ) simulation software package designed Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure, or IAQX for short. This software complements and supplements existing IAQ simulation programs and...
40 CFR 35.292 - Basis for allotment.
Code of Federal Regulations, 2011 CFR
2011-07-01
... STATE AND LOCAL ASSISTANCE Environmental Program Grants State Indoor Radon Grants (section 306) § 35.292 Basis for allotment. (a) The Regional Administrator will allot State Indoor Radon Grant funds based on... Control Act. (b) No State may receive a State Indoor Radon Grant in excess of 10 percent of the total...
40 CFR 35.702 - Basis for allotment.
Code of Federal Regulations, 2011 CFR
2011-07-01
... STATE AND LOCAL ASSISTANCE Environmental Program Grants for Tribes Indoor Radon Grants (section 306) § 35.702 Basis for allotment. (a) The Regional Administrator will allot Indoor Radon Grant funds based... Control Act. (b) No Tribe or Intertribal Consortium may receive an Indoor Radon Grant in excess of 10...
Shelter and indoor air in the twenty-first century--radon, smoking, and lung cancer risks.
Fabrikant, J I
1990-01-01
Recognition that radon and its daughter products may accumulate to high levels in homes and in the workplace has led to concern about the potential lung cancer risk resulting from indoor domestic exposure. While such risks can be estimated with current dosimetric and epidemiological models for excess relative risks, it must be recognized that these models are based on data from occupational exposure and from underground miners' mortality experience. Several assumptions are required to apply risk estimates from an occupational setting to the indoor domestic environment. Analyses of the relevant data do not lead to a conclusive description of the interaction between radon daughters and cigarette smoking for the induction of lung cancer. The evidence compels the conclusion that indoor radon daughter exposure in homes represents a potential life-threatening public health hazard, particularly in males, and in cigarette smokers. Resolution of complex societal interactions will require public policy decisions involving the governmental, scientific, financial, and industrial sectors. These decisions impact the home, the workplace, and the marketplace, and they extend beyond the constraints of science. Risk identification, assessment, and management require scientific and engineering approaches to guide policy decisions to protect the public health. Mitigation and control procedures are only beginning to receive attention. Full acceptance for protection against what could prove to be a significant public health hazard in the twenty-first century will certainly involve policy decisions, not by scientists, but rather by men and women of government and law. PMID:2401265
NASA Astrophysics Data System (ADS)
Stocco, Corinne; MacNeill, Morgan; Wang, Daniel; Xu, Xiaohong; Guay, Mireille; Brook, Jeff; Wheeler, Amanda J.
As part of a multi-year personal exposure monitoring campaign, we collected personal, indoor, and outdoor levels of 188 volatile organic compounds (VOCs). In 2005, data were obtained for 48 non-smoking adults from Windsor, Ontario in order to assess their exposure to VOCs based on their daily routines and characteristics of their homes. During the 8-week winter and summer sampling sessions, five repeated 24-h measurements were obtained for each home. This paper focuses on the analysis of 18 VOCs: 11 have been declared toxic as defined under the Canadian Environmental Protection Act, [1999. Statutes of Canada. Act assented to September 14, 1999. Ottawa: Queen's Printer. Available at Canada Gazette (Part III) 22(3): (Chapter 33). http://canadagazette.gc.ca/partIII/1999/g3-02203.pdf], and seven are commonly found in household and personal care products. Results of mixed effects models indicate that personal exposure to these VOCs can be largely predicted by indoor concentrations, with models including indoor concentrations found to have an r2 value for the fixed effects ranging from 58.4% to 87.2% for the CEPA toxic VOCs and from 41.7% to 90.1% for the commonly found VOCs. Given that people spend the majority of their time inside their home, characteristics of the home such as air exchange rates, type of garage, and type of stove have a greater potential to impact personal exposures.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Klasen, Elizabeth M.; Wills, Beatriz; Naithani, Neha
Household air pollution from the burning of biomass fuels is recognized as the third greatest contributor to the global burden of disease. Incomplete combustion of biomass fuels releases a complex mixture of carbon monoxide (CO), particulate matter (PM) and other toxins into the household environment. Some investigators have used indoor CO concentrations as a reliable surrogate of indoor PM concentrations; however, the assumption that indoor CO concentration is a reasonable proxy of indoor PM concentration has been a subject of controversy. We sought to describe the relationship between indoor PM{sub 2.5} and CO concentrations in 128 households across three resource-poormore » settings in Peru, Nepal, and Kenya. We simultaneously collected minute-to-minute PM{sub 2.5} and CO concentrations within a meter of the open-fire stove for approximately 24 h using the EasyLog-USB-CO data logger (Lascar Electronics, Erie, PA) and the personal DataRAM-1000AN (Thermo Fisher Scientific Inc., Waltham, MA), respectively. We also collected information regarding household construction characteristics, and cooking practices of the primary cook. Average 24 h indoor PM{sub 2.5} and CO concentrations ranged between 615 and 1440 μg/m{sup 3}, and between 9.1 and 35.1 ppm, respectively. Minute-to-minute indoor PM{sub 2.5} concentrations were in a safe range (<25 μg/m{sup 3}) between 17% and 65% of the time, and exceeded 1000 μg/m{sup 3} between 8% and 21% of the time, whereas indoor CO concentrations were in a safe range (<7 ppm) between 46% and 79% of the time and exceeded 50 ppm between 4%, and 20% of the time. Overall correlations between indoor PM{sub 2.5} and CO concentrations were low to moderate (Spearman ρ between 0.59 and 0.83). There was also poor agreement and evidence of proportional bias between observed indoor PM{sub 2.5} concentrations vs. those estimated based on indoor CO concentrations, with greater discordance at lower concentrations. Our analysis does not support the notion that indoor CO concentration is a surrogate marker for indoor PM{sub 2.5} concentration across all settings. Both are important markers of household air pollution with different health and environmental implications and should therefore be independently measured. - Highlights: • We summarized indoor PM2.5 and CO concentrations across three resource-poor settings. • Overall correlations between indoor PM2.5 and CO were low to moderate. • Agreement between observed indoor PM2.5 vs. those estimated based on indoor CO was poor.« less
An IBeacon-Based Location System for Smart Home Control.
Liu, Qinghe; Yang, Xinshuang; Deng, Lizhen
2018-06-11
Indoor location and intelligent control system can bring convenience to people’s daily life. In this paper, an indoor control system is designed to achieve equipment remote control by using low-energy Bluetooth (BLE) beacon and Internet of Things (IoT) technology. The proposed system consists of five parts: web server, home gateway, smart terminal, smartphone app and BLE beacons. In the web server, fingerprint matching based on RSSI stochastic characteristic and posture recognition model based on geomagnetic sensing are used to establish a more efficient equipment control system, combined with Pedestrian Dead Reckoning (PDR) technology to improve the accuracy of location. A personalized menu of remote “one-click” control is finally offered to users in a smartphone app. This smart home control system has been implemented by hardware, and precision and stability tests have been conducted, which proved the practicability and good user experience of this solution.
Optical Indoor Positioning System Based on TFT Technology.
Gőzse, István
2015-12-24
A novel indoor positioning system is presented in the paper. Similarly to the camera-based solutions, it is based on visual detection, but it conceptually differs from the classical approaches. First, the objects are marked by LEDs, and second, a special sensing unit is applied, instead of a camera, to track the motion of the markers. This sensing unit realizes a modified pinhole camera model, where the light-sensing area is fixed and consists of a small number of sensing elements (photodiodes), and it is the hole that can be moved. The markers are tracked by controlling the motion of the hole, such that the light of the LEDs always hits the photodiodes. The proposed concept has several advantages: Apart from its low computational demands, it is insensitive to the disturbing ambient light. Moreover, as every component of the system can be realized by simple and inexpensive elements, the overall cost of the system can be kept low.
Wei, Wenjuan; Xiong, Jianyin; Zhang, Yinping
2013-01-01
Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs) and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0), the diffusion coefficient (D), and the partition coefficient (K), can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C. PMID:24312497
Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua
2015-01-01
Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics. PMID:25599427
3D indoor modeling using a hand-held embedded system with multiple laser range scanners
NASA Astrophysics Data System (ADS)
Hu, Shaoxing; Wang, Duhu; Xu, Shike
2016-10-01
Accurate three-dimensional perception is a key technology for many engineering applications, including mobile mapping, obstacle detection and virtual reality. In this article, we present a hand-held embedded system designed for constructing 3D representation of structured indoor environments. Different from traditional vehicle-borne mobile mapping methods, the system presented here is capable of efficiently acquiring 3D data while an operator carrying the device traverses through the site. It consists of a simultaneous localization and mapping(SLAM) module, a 3D attitude estimate module and a point cloud processing module. The SLAM is based on a scan matching approach using a modern LIDAR system, and the 3D attitude estimate is generated by a navigation filter using inertial sensors. The hardware comprises three 2D time-flight laser range finders and an inertial measurement unit(IMU). All the sensors are rigidly mounted on a body frame. The algorithms are developed on the frame of robot operating system(ROS). The 3D model is constructed using the point cloud library(PCL). Multiple datasets have shown robust performance of the presented system in indoor scenarios.
Myatt, Theodore A; Kaufman, Matthew H; Allen, Joseph G; MacIntosh, David L; Fabian, M Patricia; McDevitt, James J
2010-09-03
Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH) conditions. Further analysis has shown that absolute humidity (AH) may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US) using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity indoors.
2010-01-01
Background Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH) conditions. Further analysis has shown that absolute humidity (AH) may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. Methods A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US) using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. Results The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. Conclusion This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity indoors. PMID:20815876
Modeling Particle Exposure in US Trucking Terminals
Davis, ME; Smith, TJ; Laden, F; Hart, JE; Ryan, LM; Garshick, E
2007-01-01
Multi-tiered sampling approaches are common in environmental and occupational exposure assessment, where exposures for a given individual are often modeled based on simultaneous measurements taken at multiple indoor and outdoor sites. The monitoring data from such studies is hierarchical by design, imposing a complex covariance structure that must be accounted for in order to obtain unbiased estimates of exposure. Statistical methods such as structural equation modeling (SEM) represent a useful alternative to simple linear regression in these cases, providing simultaneous and unbiased predictions of each level of exposure based on a set of covariates specific to the exposure setting. We test the SEM approach using data from a large exposure assessment of diesel and combustion particles in the US trucking industry. The exposure assessment includes data from 36 different trucking terminals across the United States sampled between 2001 and 2005, measuring PM2.5 and its elemental carbon (EC), organic carbon (OC) components, by personal monitoring, and sampling at two indoor work locations and an outdoor “background” location. Using the SEM method, we predict: 1) personal exposures as a function of work related exposure and smoking status; 2) work related exposure as a function of terminal characteristics, indoor ventilation, job location, and background exposure conditions; and 3) background exposure conditions as a function of weather, nearby source pollution, and other regional differences across terminal sites. The primary advantage of SEMs in this setting is the ability to simultaneously predict exposures at each of the sampling locations, while accounting for the complex covariance structure among the measurements and descriptive variables. The statistically significant results and high R2 values observed from the trucking industry application supports the broader use of this approach in exposure assessment modeling. PMID:16856739
Kim, Sangmin; Kim, Jeonghyun; Jung, Jaehoon; Heo, Joon
2015-01-01
The cadastral system provides land ownership information by registering and representing land boundaries on a map. The current cadastral system in Korea, however, focuses mainly on the management of 2D land-surface boundaries. It is not yet possible to provide efficient or reliable land administration, as this 2D system cannot support or manage land information on 3D properties (including architectures and civil infrastructures) for both above-ground and underground facilities. A geometrical model of the 3D parcel, therefore, is required for registration of 3D properties. This paper, considering the role of the cadastral system, proposes a framework for a 3D underground cadastral system that can register various types of 3D underground properties using indoor mapping for as-built Building Information Modeling (BIM). The implementation consists of four phases: (1) geometric modeling of a real underground infrastructure using terrestrial laser scanning data; (2) implementation of as-built BIM based on geometric modeling results; (3) accuracy assessment for created as-built BIM using reference points acquired by total station; and (4) creation of three types of 3D underground cadastral map to represent underground properties. The experimental results, based on indoor mapping for as-built BIM, show that the proposed framework for a 3D underground cadastral system is able to register the rights, responsibilities, and restrictions corresponding to the 3D underground properties. In this way, clearly identifying the underground physical situation enables more reliable and effective decision-making in all aspects of the national land administration system. PMID:26690174
An Agent-Based Model for Navigation Simulation in a Heterogeneous Environment
ERIC Educational Resources Information Center
Shanklin, Teresa A.
2012-01-01
Complex navigation (e.g. indoor and outdoor environments) can be studied as a system-of-systems problem. The model is made up of disparate systems that can aid a user in navigating from one location to another, utilizing whatever sensor system or information is available. By using intelligent navigation sensors and techniques (e.g. RFID, Wifi,…
INDOOR AIR QUALITY DATA BASE FOR ORGANIC COMPOUNDS
The report gives results of the compilation of a data base for concentrations of organic compounds measured indoors. ased on a review of the literature from 1979 through 1990, the data base contains information on over 220 compounds ranging in molecular weight from 30 to 446. he ...
Reactive indoor air chemistry and health-A workshop summary.
Wells, J R; Schoemaecker, C; Carslaw, N; Waring, M S; Ham, J E; Nelissen, I; Wolkoff, P
2017-11-01
The chemical composition of indoor air changes due to the reactive nature of the indoor environment. Historically, only the stable parent compounds were investigated due to their ease of measurement by conventional methods. Today, however, scientists can better characterize oxidation products (gas and particulate-phase) formed by indoor chemistry. An understanding of occupant exposure can be developed through the investigation of indoor oxidants, the use of derivatization techniques, atmospheric pressure detection, the development of real-time technologies, and improved complex modeling techniques. Moreover, the connection between exposure and health effects is now receiving more attention from the research community. Nevertheless, a need still exists for improved understanding of the possible link between indoor air chemistry and observed acute or chronic health effects and long-term effects such as work-related asthma. Published by Elsevier GmbH.
Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization
NASA Astrophysics Data System (ADS)
Liu, Zexi
2018-01-01
Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.
Exposure to indoor tanning without burning and melanoma risk by sunburn history.
Vogel, Rachel Isaksson; Ahmed, Rehana L; Nelson, Heather H; Berwick, Marianne; Weinstock, Martin A; Lazovich, DeAnn
2014-07-01
Indoor tanning is carcinogenic to humans. Individuals report that they tan indoors before planning to be in the sun to prevent sunburns, but whether skin cancer is subsequently reduced is unknown. Using a population-based case-control study, we calculated the association between melanoma and indoor tanning after excluding exposed participants reporting indoor tanning-related burns, stratified by their number of lifetime sunburns (0, 1-2, 3-5, >5). Confounding was addressed using propensity score analysis methods. All statistical tests were two-sided. We observed increased risk of melanoma across all sunburn categories for participants who had tanned indoors without burning compared with those who never tanned indoors, including those who reported zero lifetime sunburns (odds ratio = 3.87; 95% confidence interval = 1.68 to 8.91; P = .002). These data provide evidence that indoor tanning is a risk factor for melanoma even among persons who reported never experiencing burns from indoor tanning or outdoor sun exposure. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Exposure to indoor tanning without burning and melanoma risk by sunburn history.
Vogel, Rachel Isaksson; Ahmed, Rehana L; Nelson, Heather H; Berwick, Marianne; Weinstock, Martin A; Lazovich, DeAnn
2014-06-01
Indoor tanning is carcinogenic to humans. Individuals report that they tan indoors before planning to be in the sun to prevent sunburns, but whether skin cancer is subsequently reduced is unknown. Using a population-based case-control study, we calculated the association between melanoma and indoor tanning after excluding exposed participants reporting indoor tanning-related burns, stratified by their number of lifetime sunburns (0, 1-2, 3-5, >5). Confounding was addressed using propensity score analysis methods. All statistical tests were two-sided. We observed increased risk of melanoma across all sunburn categories for participants who had tanned indoors without burning compared with those who never tanned indoors, including those who reported zero lifetime sunburns (odds ratio = 3.87; 95% confidence interval = 1.68 to 8.91; P = .002). These data provide evidence that indoor tanning is a risk factor for melanoma even among persons who reported never experiencing burns from indoor tanning or outdoor sun exposure. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Over the past two decades, more than 20 mass transfer models have been developed for the sources, sinks, and barriers for volatile and semivolatile organic compounds (VOCs and SVOCs) in the indoor environment. While these models have greatly improved our understanding of VOC and ...
High Blood Pressure and Long-Term Exposure to Indoor Noise and Air Pollution from Road Traffic
Künzli, Nino; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Vila, Joan; Bouso, Laura; Deltell, Alexandre; Marrugat, Jaume; Ramos, Rafel; Sunyer, Jordi; Elosua, Roberto; Basagaña, Xavier
2014-01-01
Background: Traffic noise has been associated with prevalence of hypertension, but reports are inconsistent for blood pressure (BP). To ascertain noise effects and to disentangle them from those suspected to be from traffic-related air pollution, it may be essential to estimate people’s noise exposure indoors in bedrooms. Objectives: We analyzed associations between long-term exposure to indoor traffic noise in bedrooms and prevalent hypertension and systolic (SBP) and diastolic (DBP) BP, considering long-term exposure to outdoor nitrogen dioxide (NO2). Methods: We evaluated 1,926 cohort participants at baseline (years 2003–2006; Girona, Spain). Outdoor annual average levels of nighttime traffic noise (Lnight) and NO2 were estimated at postal addresses with a detailed traffic noise model and a land-use regression model, respectively. Individual indoor traffic Lnight levels were derived from outdoor Lnight with application of insulations provided by reported noise-reducing factors. We assessed associations for hypertension and BP with multi-exposure logistic and linear regression models, respectively. Results: Median levels were 27.1 dB(A) (indoor Lnight), 56.7 dB(A) (outdoor Lnight), and 26.8 μg/m3 (NO2). Spearman correlations between outdoor and indoor Lnight with NO2 were 0.75 and 0.23, respectively. Indoor Lnight was associated both with hypertension (OR = 1.06; 95% CI: 0.99, 1.13) and SBP (β = 0.72; 95% CI: 0.29, 1.15) per 5 dB(A); and NO2 was associated with hypertension (OR = 1.16; 95% CI: 0.99, 1.36), SBP (β = 1.23; 95% CI: 0.21, 2.25), and DBP (β⊇= 0.56; 95% CI: –0.03, 1.14) per 10 μg/m3. In the outdoor noise model, Lnight was associated only with hypertension and NO2 with BP only. The indoor noise–SBP association was stronger and statistically significant with a threshold at 30 dB(A). Conclusion: Long-term exposure to indoor traffic noise was associated with prevalent hypertension and SBP, independently of NO2. Associations were less consistent for outdoor traffic Lnight and likely affected by collinearity. Citation: Foraster M, Künzli N, Aguilera I, Rivera M, Agis D, Vila J, Bouso L, Deltell A, Marrugat J, Ramos R, Sunyer J, Elosua R, Basagaña X. 2014. High blood pressure and long-term exposure to indoor noise and air pollution from road traffic. Environ Health Perspect 122:1193–1200; http://dx.doi.org/10.1289/ehp.1307156 PMID:25003348
Rethinking Indoor Localization Solutions Towards the Future of Mobile Location-Based Services
NASA Astrophysics Data System (ADS)
Guney, C.
2017-11-01
Satellite navigation systems with GNSS-enabled devices, such as smartphones, car navigation systems, have changed the way users travel in outdoor environment. GNSS is generally not well suited for indoor location and navigation because of two reasons: First, GNSS does not provide a high level of accuracy although indoor applications need higher accuracies. Secondly, poor coverage of satellite signals for indoor environments decreases its accuracy. So rather than using GNSS satellites within closed environments, existing indoor navigation solutions rely heavily on installed sensor networks. There is a high demand for accurate positioning in wireless networks in GNSS-denied environments. However, current wireless indoor positioning systems cannot satisfy the challenging needs of indoor location-aware applications. Nevertheless, access to a user's location indoors is increasingly important in the development of context-aware applications that increases business efficiency. In this study, how can the current wireless location sensing systems be tailored and integrated for specific applications, like smart cities/grids/buildings/cars and IoT applications, in GNSS-deprived areas.
Xu, Jia; Zhang, Nan; Han, Bin; You, Yan; Zhou, Jian; Zhang, Jiefeng; Niu, Can; Liu, Yating; He, Fei; Ding, Xiao; Bai, Zhipeng
2016-12-01
Using central site measurement data to predict personal exposure to particulate matter (PM) is challenging, because people spend most of their time indoors and ambient contribution to personal exposure is subject to infiltration conditions affected by many factors. Efforts in assessing and predicting exposure on the basis of associated indoor/outdoor and central site monitoring were limited in China. This study collected daily personal exposure, residential indoor/outdoor and community central site PM filter samples in an elderly community during the non-heating and heating periods in 2009 in Tianjin, China. Based on the chemical analysis results of particulate species, mass concentrations of the particulate compounds were estimated and used to reconstruct the PM mass for mass balance analysis. The infiltration factors (F inf ) of particulate compounds were estimated using both robust regression and mixed effect regression methods, and further estimated the exposure factor (F pex ) according to participants' time-activity patterns. Then an empirical exposure model was developed to predict personal exposure to PM and particulate compounds as the sum of ambient and non-ambient contributions. Results showed that PM mass observed during the heating period could be well represented through chemical mass reconstruction, because unidentified mass was minimal. Excluding the high observations (>300μg/m 3 ), this empirical exposure model performed well for PM and elemental carbon (EC) that had few indoor sources. These results support the use of F pex as an indicator for ambient contribution predictions, and the use of empirical non-ambient contribution to assess exposure to particulate compounds. Copyright © 2016 Elsevier B.V. All rights reserved.
Improving indoor air quality has been a priority at the US EPA for many years. Among the components of indoor air, molds present a growing concern for the public. A primary information source on indoor molds is the news media, which often confuses rather than clarifies the situa...
Indoor-Outdoor Air Pollution Relationship: A Literature Review.
ERIC Educational Resources Information Center
Benson, Ferris B.; And Others
While extensive measurements have been and are being made of outdoor pollution, relatively few data have been gathered on indoor pollution. The data that are available are compiled and analyzed in the report. Based on a review of the literature, it was possible to infer relationships between indoor and outdoor pollution and to identify factors…
Lantos-Hyde United States Government Malaria Strategy, 2009-2014
2010-04-25
Long lasting insecticide -treated nets (LLINs); • Indoor residual spraying (IRS) with insecticides ; • Intermittent preventive treatment of...measures: insecticide -treated mosquito nets (ITNs); indoor residual spraying (IRS) of insecticides ; artemisinin-based combination therapy (ACTs); and...is national policy. Indoor residual spraying : Between 2005 and 2009, PMI supported the introduction or
Mold inhibition on unseasoned southern pine
Carol A. Clausen; Vina W. Yang
2003-01-01
Concerns about indoor air quality due to mold growth have increased dramatically in the United States. In the absence of moisture management, fungicides need to be developed for indoor use to control mold establishment. An ideal fungicide for prevention of indoor mold growth on wood-based materials needs to specifically prevent spore germination and provide long-term...
Lin, Lian-Yu; Chuang, Hsiao-Chi; Liu, I-Jung; Chen, Hua-Wei; Chuang, Kai-Jen
2013-10-01
Indoor air pollution is associated with cardiovascular effects, however, little is known about the effects of improving indoor air quality on cardiovascular health. The aim of this study was to explore whether improving indoor air quality through air conditioning can improve cardiovascular health in human subjects. We recruited a panel of 300 healthy subjects from Taipei, aged 20 and over, to participate in six home visits each, to measure a variety of cardiovascular endpoints, including high sensitivity-C-reactive protein (hs-CRP), 8-hydroxy-2'-deoxyguanosine (8-OHdG), fibrinogen in plasma and heart rate variability (HRV). Indoor particles and total volatile organic compounds (VOCs) were measured simultaneously at the participant's home during each visit. Three exposure conditions were investigated in this study: participants were requested to keep their windows open during the first two visits, close their windows during the next two visits, and close the windows and turn on their air conditioners during the last two visits. We used linear mixed-effects models to associate the cardiovascular endpoints with individual indoor air pollutants. The results showed that increases in hs-CRP, 8-OHdG and fibrinogen, and decreases in HRV indices were associated with increased levels of indoor particles and total VOCs in single-pollutant and two-pollutant models. The effects of indoor particles and total VOCs on cardiovascular endpoints were greatest during visits with the windows open. During visits with the air conditioners turned on, no significant changes in cardiovascular endpoints were observed. In conclusion, indoor air pollution is associated with inflammation, oxidative stress, blood coagulation and autonomic dysfunction. Reductions in indoor air pollution and subsequent improvements in cardiovascular health can be achieved by closing windows and turning on air conditioners at home. Copyright © 2013 Elsevier B.V. All rights reserved.
Wifi-friendly building, enabling wifi signal indoor: an initial study
NASA Astrophysics Data System (ADS)
Suherman; Mubarakah, Naemah; Sagala, Romulo S.; Prayitno, Hendra
2018-03-01
The 802.11 network (wireless fidelity/WiFi) is the most common wireless infrastructure applied for internet access indoor. Widespread devices and installation simplicity make it better than similar technologies such as 802.16 and other 802.xx series. The access points are the most influential devices for indoor access. However, building indoor architectures contribute to the signal quality. Since WiFi installation in buildings becomes prevalent, the architecture should consider WiFi-friendliness into consideration. The more friendly the building to WiFi signal, the more efficient the 802.11 based wireless infrastructure. This paper present preliminary study how the building, specially the obstacle material, effects the WiFi signal propagation indoor. The study was performed by using ESP8266-based WiFi signal reader, to determine the impact indoor obstacles to WiFi signal propagation. The initial study shows that simple reflecting materials increase signal level about 1.14 dBm. WiFi-friendly building can be achieved by transforming building properties into signal interconnector. A simple photo frame with aluminium sheet insertion increase signal level on the second floor up to 6.56dBm.
Health effects of home energy efficiency interventions in England: a modelling study
Milner, James; Chalabi, Zaid; Das, Payel; Jones, Benjamin; Shrubsole, Clive; Davies, Mike; Wilkinson, Paul
2015-01-01
Objective To assess potential public health impacts of changes to indoor air quality and temperature due to energy efficiency retrofits in English dwellings to meet 2030 carbon reduction targets. Design Health impact modelling study. Setting England. Participants English household population. Intervention Three retrofit scenarios were modelled: (1) fabric and ventilation retrofits installed assuming building regulations are met; (2) as with scenario (1) but with additional ventilation for homes at risk of poor ventilation; (3) as with scenario (1) but with no additional ventilation to illustrate the potential risk of weak regulations and non-compliance. Main outcome Primary outcomes were changes in quality adjusted life years (QALYs) over 50 years from cardiorespiratory diseases, lung cancer, asthma and common mental disorders due to changes in indoor air pollutants, including secondhand tobacco smoke, PM2.5 from indoor and outdoor sources, radon, mould, and indoor winter temperatures. Results The modelling study estimates showed that scenario (1) resulted in positive effects on net mortality and morbidity of 2241 (95% credible intervals (CI) 2085 to 2397) QALYs per 10 000 persons over 50 years follow-up due to improved temperatures and reduced exposure to indoor pollutants, despite an increase in exposure to outdoor-generated particulate matter with a diameter of 2.5 μm or less (PM2.5). Scenario (2) resulted in a negative impact of −728 (95% CI −864 to −592) QALYs per 10 000 persons over 50 years due to an overall increase in indoor pollutant exposures. Scenario (3) resulted in −539 (95% CI −678 to -399) QALYs per 10 000 persons over 50 years follow-up due to an increase in indoor exposures despite the targeting of pollutants. Conclusions If properly implemented alongside ventilation, energy efficiency retrofits in housing can improve health by reducing exposure to cold and air pollutants. Maximising the health benefits requires careful understanding of the balance of changes in pollutant exposures, highlighting the importance of ventilation to mitigate the risk of poor indoor air quality. PMID:25916488
Indoor air pollution: Acute adverse health effects and host susceptibility
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zummo, S.M.; Karol, M.H.
1996-01-01
Increased awareness of the poor quality of indoor air compared with outdoor air has resulted in a significant amount of research on the adverse health effects and mechanisms of action of indoor air pollutants. Common indoor air agents are identified, along with resultant adverse health effects, mechanisms of action, and likely susceptible populations. Indoor air pollutants range from biological agents (such as dust mites) to chemical irritants (such as nitrogen dioxide, carbon monoxide, sulfur dioxide, formaldehyde, and isocyanates). These agents may exert their effects through allergic as well as nonallergic mechanisms. While the public does not generally perceive poor indoormore » air quality as a significant health risk, increasing reports of illness related to indoor air and an expanding base of knowledge on the health effects of indoor air pollution are likely to continue pushing the issue to the forefront.« less
Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing.
Li, Wen; Wei, Dongyan; Lai, Qifeng; Li, Xianghong; Yuan, Hong
2018-05-08
Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy.
Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing
Li, Wen; Wei, Dongyan; Lai, Qifeng; Li, Xianghong; Yuan, Hong
2018-01-01
Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy. PMID:29738454
An Indoor Location-Based Control System Using Bluetooth Beacons for IoT Systems.
Huh, Jun-Ho; Seo, Kyungryong
2017-12-19
The indoor location-based control system estimates the indoor position of a user to provide the service he/she requires. The major elements involved in the system are the localization server, service-provision client, user application positioning technology. The localization server controls access of terminal devices (e.g., Smart Phones and other wireless devices) to determine their locations within a specified space first and then the service-provision client initiates required services such as indoor navigation and monitoring/surveillance. The user application provides necessary data to let the server to localize the devices or allow the user to receive various services from the client. The major technological elements involved in this system are indoor space partition method, Bluetooth 4.0, RSSI (Received Signal Strength Indication) and trilateration. The system also employs the BLE communication technology when determining the position of the user in an indoor space. The position information obtained is then used to control a specific device(s). These technologies are fundamental in achieving a "Smart Living". An indoor location-based control system that provides services by estimating user's indoor locations has been implemented in this study (First scenario). The algorithm introduced in this study (Second scenario) is effective in extracting valid samples from the RSSI dataset but has it has some drawbacks as well. Although we used a range-average algorithm that measures the shortest distance, there are some limitations because the measurement results depend on the sample size and the sample efficiency depends on sampling speeds and environmental changes. However, the Bluetooth system can be implemented at a relatively low cost so that once the problem of precision is solved, it can be applied to various fields.
An Indoor Location-Based Control System Using Bluetooth Beacons for IoT Systems
Huh, Jun-Ho; Seo, Kyungryong
2017-01-01
The indoor location-based control system estimates the indoor position of a user to provide the service he/she requires. The major elements involved in the system are the localization server, service-provision client, user application positioning technology. The localization server controls access of terminal devices (e.g., Smart Phones and other wireless devices) to determine their locations within a specified space first and then the service-provision client initiates required services such as indoor navigation and monitoring/surveillance. The user application provides necessary data to let the server to localize the devices or allow the user to receive various services from the client. The major technological elements involved in this system are indoor space partition method, Bluetooth 4.0, RSSI (Received Signal Strength Indication) and trilateration. The system also employs the BLE communication technology when determining the position of the user in an indoor space. The position information obtained is then used to control a specific device(s). These technologies are fundamental in achieving a “Smart Living”. An indoor location-based control system that provides services by estimating user’s indoor locations has been implemented in this study (First scenario). The algorithm introduced in this study (Second scenario) is effective in extracting valid samples from the RSSI dataset but has it has some drawbacks as well. Although we used a range-average algorithm that measures the shortest distance, there are some limitations because the measurement results depend on the sample size and the sample efficiency depends on sampling speeds and environmental changes. However, the Bluetooth system can be implemented at a relatively low cost so that once the problem of precision is solved, it can be applied to various fields. PMID:29257044
The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work
Torres-Sospedra, Joaquín; Jiménez, Antonio R.; Knauth, Stefan; Moreira, Adriano; Beer, Yair; Fetzer, Toni; Ta, Viet-Cuong; Montoliu, Raul; Seco, Fernando; Mendoza-Silva, Germán M.; Belmonte, Oscar; Koukofikis, Athanasios; Nicolau, Maria João; Costa, António; Meneses, Filipe; Ebner, Frank; Deinzer, Frank; Vaufreydaz, Dominique; Dao, Trung-Kien; Castelli, Eric
2017-01-01
This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors’ estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described. PMID:28287447
Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning
Brković, Milenko; Simić, Mirjana
2014-01-01
Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443
Design of indoor temperature and humidity detection system based on single chip microcomputer
NASA Astrophysics Data System (ADS)
Fu, Xiuwei; Fu, Li; Ma, Tianhui
2018-03-01
The indoor temperature and humidity detection system based on STC15F2K60S2 is designed in this paper. The temperature and humidity sensor DHT22 to monitor the indoor temperature and humidity are used, and the temperature and humidity data to the user's handheld device are wirelessly transmitted, when the temperature reaches or exceeds the user set the temperature alarm value, and the system sound and light alarm, to remind the user.
Heading Estimation for Pedestrian Dead Reckoning Based on Robust Adaptive Kalman Filtering.
Wu, Dongjin; Xia, Linyuan; Geng, Jijun
2018-06-19
Pedestrian dead reckoning (PDR) using smart phone-embedded micro-electro-mechanical system (MEMS) sensors plays a key role in ubiquitous localization indoors and outdoors. However, as a relative localization method, it suffers from the problem of error accumulation which prevents it from long term independent running. Heading estimation error is one of the main location error sources, and therefore, in order to improve the location tracking performance of the PDR method in complex environments, an approach based on robust adaptive Kalman filtering (RAKF) for estimating accurate headings is proposed. In our approach, outputs from gyroscope, accelerometer, and magnetometer sensors are fused using the solution of Kalman filtering (KF) that the heading measurements derived from accelerations and magnetic field data are used to correct the states integrated from angular rates. In order to identify and control measurement outliers, a maximum likelihood-type estimator (M-estimator)-based model is used. Moreover, an adaptive factor is applied to resist the negative effects of state model disturbances. Extensive experiments under static and dynamic conditions were conducted in indoor environments. The experimental results demonstrate the proposed approach provides more accurate heading estimates and supports more robust and dynamic adaptive location tracking, compared with methods based on conventional KF.
Hernández, Noelia; Ocaña, Manuel; Alonso, Jose M; Kim, Euntai
2017-01-13
Although much research has taken place in WiFi indoor localization systems, their accuracy can still be improved. When designing this kind of system, fingerprint-based methods are a common choice. The problem with fingerprint-based methods comes with the need of site surveying the environment, which is effort consuming. In this work, we propose an approach, based on support vector regression, to estimate the received signal strength at non-site-surveyed positions of the environment. Experiments, performed in a real environment, show that the proposed method could be used to improve the resolution of fingerprint-based indoor WiFi localization systems without increasing the site survey effort.
Hernández, Noelia; Ocaña, Manuel; Alonso, Jose M.; Kim, Euntai
2017-01-01
Although much research has taken place in WiFi indoor localization systems, their accuracy can still be improved. When designing this kind of system, fingerprint-based methods are a common choice. The problem with fingerprint-based methods comes with the need of site surveying the environment, which is effort consuming. In this work, we propose an approach, based on support vector regression, to estimate the received signal strength at non-site-surveyed positions of the environment. Experiments, performed in a real environment, show that the proposed method could be used to improve the resolution of fingerprint-based indoor WiFi localization systems without increasing the site survey effort. PMID:28098773
Calculating Least Risk Paths in 3d Indoor Space
NASA Astrophysics Data System (ADS)
Vanclooster, A.; De Maeyer, Ph.; Fack, V.; Van de Weghe, N.
2013-08-01
Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm are proposed to be more aligned to the specific structure of indoor environments (e.g. no turn restrictions, restricted usage of rooms, vertical movement) and common wayfinding strategies indoors. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.
Short-term dynamics of indoor and outdoor endotoxin exposure: Case of Santiago, Chile, 2012.
Barraza, Francisco; Jorquera, Héctor; Heyer, Johanna; Palma, Wilfredo; Edwards, Ana María; Muñoz, Marcelo; Valdivia, Gonzalo; Montoya, Lupita D
2016-01-01
Indoor and outdoor endotoxin in PM2.5 was measured for the very first time in Santiago, Chile, in spring 2012. Average endotoxin concentrations were 0.099 and 0.094 [EU/m(3)] for indoor (N=44) and outdoor (N=41) samples, respectively; the indoor-outdoor correlation (log-transformed concentrations) was low: R=-0.06, 95% CI: (-0.35 to 0.24), likely owing to outdoor spatial variability. A linear regression model explained 68% of variability in outdoor endotoxins, using as predictors elemental carbon (a proxy of traffic emissions), chlorine (a tracer of marine air masses reaching the city) and relative humidity (a modulator of surface emissions of dust, vegetation and garbage debris). In this study, for the first time a potential source contribution function (PSCF) was applied to outdoor endotoxin measurements. Wind trajectory analysis identified upwind agricultural sources as contributors to the short-term, outdoor endotoxin variability. Our results confirm an association between combustion particles from traffic and outdoor endotoxin concentrations. For indoor endotoxins, a predictive model was developed but it only explained 44% of endotoxin variability; the significant predictors were tracers of indoor PM2.5 dust (Si, Ca), number of external windows and number of hours with internal doors open. Results suggest that short-term indoor endotoxin variability may be driven by household dust/garbage production and handling. This would explain the modest predictive performance of published models that use answers to household surveys as predictors. One feasible alternative is to increase the sampling period so that household features would arise as significant predictors of long-term airborne endotoxin levels. Copyright © 2016 Elsevier Ltd. All rights reserved.
Defining indoor heat thresholds for health in the UK.
Anderson, Mindy; Carmichael, Catriona; Murray, Virginia; Dengel, Andy; Swainson, Michael
2013-05-01
It has been recognised that as outdoor ambient temperatures increase past a particular threshold, so do mortality/morbidity rates. However, similar thresholds for indoor temperatures have not yet been identified. Due to a warming climate, the non-sustainability of air conditioning as a solution, and the desire for more energy-efficient airtight homes, thresholds for indoor temperature should be defined as a public health issue. The aim of this paper is to outline the need for indoor heat thresholds and to establish if they can be identified. Our objectives include: describing how indoor temperature is measured; highlighting threshold measurements and indices; describing adaptation to heat; summary of the risk of susceptible groups to heat; reviewing the current evidence on the link between sleep, heat and health; exploring current heat and health warning systems and thresholds; exploring the built environment and the risk of overheating; and identifying the gaps in current knowledge and research. A global literature search of key databases was conducted using a pre-defined set of keywords to retrieve peer-reviewed and grey literature. The paper will apply the findings to the context of the UK. A summary of 96 articles, reports, government documents and textbooks were analysed and a gap analysis was conducted. Evidence on the effects of indoor heat on health implies that buildings are modifiers of the effect of climate on health outcomes. Personal exposure and place-based heat studies showed the most significant correlations between indoor heat and health outcomes. However, the data are sparse and inconclusive in terms of identifying evidence-based definitions for thresholds. Further research needs to be conducted in order to provide an evidence base for threshold determination. Indoor and outdoor heat are related but are different in terms of language and measurement. Future collaboration between the health and building sectors is needed to develop a common language and an index for indoor heat and health thresholds in a changing climate.
This paper describes a method for dynamic modeling of the interactions of semivolatile organic compounds (SVOCs) with airborne and settled particulate matter in the indoor environment. This method is fully compatible with the other components within the framework. Despite the unc...
Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5
Health studies of fine particulate matter (PM2.5) often use outdoor concentrations as exposure surrogates, which fail to account for indoor attenuation of ambient PM2.5 and time indoors. To address these limitations, we developed an air pollution exposure model for individuals (E...
Malek, Salim; Melgani, Farid; Mekhalfi, Mohamed Lamine; Bazi, Yakoub
2017-11-16
This paper describes three coarse image description strategies, which are meant to promote a rough perception of surrounding objects for visually impaired individuals, with application to indoor spaces. The described algorithms operate on images (grabbed by the user, by means of a chest-mounted camera), and provide in output a list of objects that likely exist in his context across the indoor scene. In this regard, first, different colour, texture, and shape-based feature extractors are generated, followed by a feature learning step by means of AutoEncoder (AE) models. Second, the produced features are fused and fed into a multilabel classifier in order to list the potential objects. The conducted experiments point out that fusing a set of AE-learned features scores higher classification rates with respect to using the features individually. Furthermore, with respect to reference works, our method: (i) yields higher classification accuracies, and (ii) runs (at least four times) faster, which enables a potential full real-time application.
Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks
Richter, Philipp; Toledano-Ayala, Manuel
2015-01-01
Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate. PMID:26370996
Cance, Jessica Duncan; Talley, Anna E; Fromme, Kim
2016-02-01
Almost one-third of college students report recent cigarette use, primarily as "social smoking," and often in conjunction with alcohol use. While city-wide indoor smoking bans effectively reduce the number of social opportunities to smoke (eg, bars and music clubs), little is known about how these bans may impact the smoking behaviors of college students. Furthermore, nothing is known about how indoor smoking bans may impact students' drinking behaviors. The current study aims to determine the impact of a city-wide comprehensive indoor smoking ban on smoking and alcohol behaviors among a longitudinal sample of emerging adults. Data are from a 6-year longitudinal study (10 waves of data collection) that began the summer before college enrollment. Participants (N = 2244; 60% female) reported on their past 3-month smoking and drinking behaviors using Internet-based surveys at each wave. Piecewise linear growth modeling was used to determine how a city-wide comprehensive indoor smoking ban (implemented in the Fall of 2005 between Waves 4 and 5) impacted smoking frequency, cigarette quantity, drinking frequency, and number of binge drinking episodes. Smoking and alcohol use increased from the summer before college through the semester before implementation of the city-wide smoking ban. While smoking frequency (P < .001) and cigarette quantity (P < .05) declined after the ban, drinking frequency increased (P < .001) and the number of binge drinking episodes remained stable. Current findings suggest that comprehensive indoor smoking bans can influence the smoking behaviors of emerging adults, whereas trajectories of drinking are relatively unchanged. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Lejeune, Alexandre; Monahan, Frank J; Moloney, Aidan P; Earley, Bernadette; Black, Alistair D; Campion, Deirdre P; Englishby, Tanya; Reilly, Petrina; O'Doherty, John; Sweeney, Torres
2010-03-31
Despite an increasing preference of consumers for beef produced from more extensive pasture-based production systems and potential human health benefits from the consumption of such beef, data regarding the health status of animals raised on pasture are limited. The objective of this study was to characterise specific aspects of the bovine peripheral and the gastrointestinal muscosal immune systems of cattle raised on an outdoor pasture system in comparison to animals raised on a conventional intensive indoor concentrate-based system. A number of in vitro functional tests of immune cells suggested subtle differences between the animals on the outdoor versus indoor production systems. There was a decrease in the number of neutrophils and monocytes engaged in phagocytosis in outdoor cattle (P < 0.01 and P < 0.05, respectively) in comparison to those indoors. Following mitogen stimulation, a lower level of interferon-gamma was produced in leukocytes from the outdoor animals (P < 0.05). There was evidence of a gastrointestinal nematode infection in the outdoor animals with elevated levels of serum pepsinogen (P < 0.001), a higher number of eosinophils (P < 0.05) and a higher level of interleukin-4 and stem cell factor mRNA expression (P < 0.05) in the outdoor animals in comparison to the indoor animals. Lower levels of copper and iodine were measured in the outdoor animals in comparison to indoor animals (P < 0.001). Despite distinctly contrasting production systems, only subtle differences were identified in the peripheral immune parameters measured between cattle raised at pasture in comparison to animals raised on a conventional intensive indoor concentrate-based production system.
Indoor Semi-volatile Organic Compounds (i-SVOC) Version 1.0
i-SVOC Version 1.0 is a general-purpose software application for dynamic modeling of the emission, transport, sorption, and distribution of semi-volatile organic compounds (SVOCs) in indoor environments.
Indoor Air Quality and Energy Efficiency
EPA completed an extensive modeling study to assess the compatibilities and trade-offs between energy, indoor air quality, and thermal comfort objectives for HVAC systems and to formulate strategies for superior performance across all areas.
Changes to indoor air quality as a result of relocating families from slums to public housing
NASA Astrophysics Data System (ADS)
Burgos, Soledad; Ruiz, Pablo; Koifman, Rosalina
2013-05-01
One largely unstudied benefit of relocating families from slums to public housing is the potential improvement in indoor air quality (IAQ). We compared families that moved from slums to public housing with those that remained living in slums in Santiago, Chile in terms of fine particulate matter (PM2.5) as main indicator of change. A cross-sectional study of 98 relocated families and 71 still living in slums was carried out, obtaining indoor and outdoor samples by a Personal Environmental Monitor. Home characteristics, including indoor air pollution sources were collected through questionnaires. Multivariate regression models included the intervention (public housing or slum), indoor pollution sources, outdoor PM2.5 and family characteristics as predictors. Indoor PM2.5 concentrations were higher in slums (77.8 μg m-3 [SD = 35.7 μg m-3]) than in public housing (55.7 μg m-3 [SD = 34.6 μg m-3], p < 0.001). Differences between indoor and outdoor PM2.5 were significant only in the slum houses. The multivariate analysis showed that housing intervention significantly decreased indoor PM2.5 (10.4 μg m-3) after adjusting by the other predictors. Outdoor PM2.5 was the main predictor of indoor PM2.5. Other significant factors were water heating fuels and indoor smoking. Having infants 1-23 months was associated with a lowering of indoor PM2.5. Our results suggest that a public housing program that moves families from slums to public housing improves indoor air quality directly and also indirectly through air pollution sources.
Valero, Enrique; Adán, Antonio; Cerrada, Carlos
2012-01-01
In this paper we present a method that automatically yields Boundary Representation Models (B-rep) for indoors after processing dense point clouds collected by laser scanners from key locations through an existing facility. Our objective is particularly focused on providing single models which contain the shape, location and relationship of primitive structural elements of inhabited scenarios such as walls, ceilings and floors. We propose a discretization of the space in order to accurately segment the 3D data and generate complete B-rep models of indoors in which faces, edges and vertices are coherently connected. The approach has been tested in real scenarios with data coming from laser scanners yielding promising results. We have deeply evaluated the results by analyzing how reliably these elements can be detected and how accurately they are modeled. PMID:23443369
Liagkouridis, Ioannis; Cousins, Ian T; Cousins, Anna Palm
2014-09-01
This review explores the existing understanding and the available approaches to estimating the emissions and fate of semi-volatile organic compounds (SVOCs) and in particular focuses on the brominated flame retardants (BFRs). Volatilisation, an important emission mechanism for the more volatile compounds can be well described using current emission models. More research is needed, however, to better characterise alternative release mechanisms such as direct material-particle partitioning and material abrasion. These two particle-mediated emissions are likely to result in an increased chemical release from the source than can be accounted for by volatilisation, especially for low volatile compounds, and emission models need to be updated in order to account for these. Air-surface partitioning is an important fate process for SVOCs such as BFRs however it is still not well characterised indoors. In addition, the assumption of an instantaneous air-particle equilibrium adopted by current indoor fate models might not be valid for high-molecular weight, strongly sorbing compounds. A better description of indoor particle dynamics is required to assess the effect of particle-associated transport as this will control the fate of low volatile BFRs. We suggest further research steps that will improve modelling precision and increase our understanding of the factors that govern the indoor fate of a wide range of SVOCs. It is also considered that the appropriateness of the selected model for a given study relies on the individual characteristics of the study environment and scope of the study. Copyright © 2014 Elsevier B.V. All rights reserved.
Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stenner, Robert D.; Hadley, Donald L.; Armstrong, Peter R.
2001-03-01
Indoor air quality effects on human health are of increasing concern to public health agencies and building owners. The prevention and treatment of 'sick building' syndrome and the spread of air-borne diseases in hospitals, for example, are well known priorities. However, increasing attention is being directed to the vulnerability of our public buildings/places, public security and national defense facilities to terrorist attack or the accidental release of air-borne biological pathogens, harmful chemicals, or radioactive contaminants. The Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System (IA-NBC-HMAS) was developed to serve as a health impact analysis tool for usemore » in addressing these concerns. The overall goal was to develop a user-friendly fully functional prototype Health Modeling and Assessment system, which will operate under the PNNL FRAMES system for ease of use and to maximize its integration with other modeling and assessment capabilities accessible within the FRAMES system (e.g., ambient air fate and transport models, water borne fate and transport models, Physiologically Based Pharmacokinetic models, etc.). The prototype IA-NBC-HMAS is designed to serve as a functional Health Modeling and Assessment system that can be easily tailored to meet specific building analysis needs of a customer. The prototype system was developed and tested using an actual building (i.e., the Churchville Building located at the Aberdeen Proving Ground) and release scenario (i.e., the release and measurement of tracer materials within the building) to ensure realism and practicality in the design and development of the prototype system. A user-friendly "demo" accompanies this report to allow the reader the opportunity for a "hands on" review of the prototype system's capability.« less
NASA Astrophysics Data System (ADS)
Salonen, Heidi; Duchaine, Caroline; Mazaheri, Mandana; Clifford, Sam; Morawska, Lidia
2015-04-01
There is currently a lack of reference values for indoor air fungal concentrations to allow for the interpretation of measurement results in subtropical school settings. Analysis of the results of this work established that, in the majority of properly maintained subtropical school buildings, without any major affecting events such as floods or visible mould or moisture contamination, indoor culturable fungi levels were driven by outdoor concentration. The results also allowed us to benchmark the "baseline range" concentrations for total culturable fungi, Penicillium spp., Cladosporium spp. and Aspergillus spp. in such school settings. The measured concentration of total culturable fungi and three individual fungal genera were estimated using Bayesian hierarchical modelling. Pooling of these estimates provided a predictive distribution for concentrations at an unobserved school. The results indicated that "baseline" indoor concentration levels for indoor total fungi, Penicillium spp., Cladosporium spp. and Aspergillus spp. in such school settings were generally ≤1450, ≤680, ≤480 and ≤90 cfu/m3, respectively, and elevated levels would indicate mould damage in building structures. The indoor/outdoor ratio for most classrooms had 95% credible intervals containing 1, indicating that fungi concentrations are generally the same indoors and outdoors at each school. Bayesian fixed effects regression modelling showed that increasing both temperature and humidity resulted in higher levels of fungi concentration.
Winkler, Jon; Munk, Jeffrey; Woods, Jason
2018-04-01
Increasing insulation levels and improved windows are reducing sensible cooling loads in high-efficiency homes. This trend raises concerns that the resulting shift in the balance of sensible and latent cooling loads may result in higher indoor humidity, occupant discomfort, and stunted adoption of high-efficiency homes. This study utilizes established moisture-buffering and air-conditioner latent degradation models in conjunction with an approach to stochastically model internal gains. Building loads and indoor humidity levels are compared for simulations of typical new construction homes and high-efficiency homes in 10 US cities. The sensitivity of indoor humidity to changes in cooling set point, air-conditioner capacity,more » and blower control parameters are evaluated. The results show that high-efficiency homes in humid climates have cooling loads with a higher fraction of latent loads than the typical new construction home, resulting in higher indoor humidity. Reducing the cooling set point is the easiest method to reduce indoor humidity, but it is not energy efficient, and overcooling may lead to occupant discomfort. Eliminating the blower operation at the end of cooling cycles and reducing the cooling airflow rate also reduce indoor humidity and with a smaller impact on energy use and comfort.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Winkler, Jon; Munk, Jeffrey; Woods, Jason
Increasing insulation levels and improved windows are reducing sensible cooling loads in high-efficiency homes. This trend raises concerns that the resulting shift in the balance of sensible and latent cooling loads may result in higher indoor humidity, occupant discomfort, and stunted adoption of high-efficiency homes. This study utilizes established moisture-buffering and air-conditioner latent degradation models in conjunction with an approach to stochastically model internal gains. Building loads and indoor humidity levels are compared for simulations of typical new construction homes and high-efficiency homes in 10 US cities. The sensitivity of indoor humidity to changes in cooling set point, air-conditioner capacity,more » and blower control parameters are evaluated. The results show that high-efficiency homes in humid climates have cooling loads with a higher fraction of latent loads than the typical new construction home, resulting in higher indoor humidity. Reducing the cooling set point is the easiest method to reduce indoor humidity, but it is not energy efficient, and overcooling may lead to occupant discomfort. Eliminating the blower operation at the end of cooling cycles and reducing the cooling airflow rate also reduce indoor humidity and with a smaller impact on energy use and comfort.« less
LADM and IndoorGML for Support of Indoor Space Identification
NASA Astrophysics Data System (ADS)
Zlatanova, S.; Van Oosterom, P. J. M.; Lee, J.; Li, K.-J.; Lemmen, C. H. J.
2016-10-01
Guidance and security in large public buildings such as airports, museums and shopping malls requires much more information that traditional 2D methods offer. Therefore 3D semantically-reach models have been actively investigated with the aim to gather knowledge about availability and accessibility of spaces. Spaces can be unavailable to specific users because of plenty of reasons: the 3D geometry of spaces (too low, too narrow), the properties of the objects to be guided to a specific part of the building (walking, driving, flying), the status of the indoor environment (e.g. crowded, limited light, under reconstruction), property regulations (private areas), security considerations and so on. However, such information is not explicitly avaible in the existing 3D semantically-reach models. IFC and CityGML are restricted to architectural building components and provide little to no means to describe such properties. IndoorGML has been designed to establish a generic approach for space identification allowing a space subdivision and automatic creation of a network for route computation. But currently it also represents only spaces as they are defined by the architectural layout of the building. The Land Administration Domain Model is currently the only available model to specify spaces on the basis of ownership and rights for use. In this paper we compare the principles of IndoorGML and LADM, investigate the approaches to define spaces and suggest options to the linking of the two types of spaces. We argue that LADM space subdivision on basis of properties and rights of use can be used to define to semantically and geometrically available and accessible spaces and therefore can enrich the IndoorGML concept.
Sharma, Manju; O'Connell, Susan; Garelli, Brett; Sattayatewa, Chakkrid; Moschandreas, Demetrios; Pagilla, Krishna
2012-01-01
Indoor air quality (IAQ) and odors were determined using sampling/monitoring, measurement, and modeling methods in a large dewatering building at a very large water reclamation plant. The ultimate goal was to determine control strategies to reduce the sensory impacts on the workforce and achieve odor reduction within the building. Study approaches included: (1) investigation of air mixing by using CO(2) as an indicator, (2) measurement of airflow capacity of ventilation fans, (3) measurement of odors and odorants, (4) development of statistical and IAQ models, and (5) recommendation of control strategies. The results showed that air quality in the building complies with occupational safety and health guidelines; however, nuisance odors that can increase stress and productivity loss still persist. Excess roof fan capacity induced odor dispersion to the upper levels. Lack of a local air exhaust system of sufficient capacity and optimum design was found to be the contributor to occasional less than adequate indoor air quality and odors. Overall, air ventilation rate in the building has less effect on persistence of odors in the building. Odor/odorant emission rates from centrifuge drops were approximately 100 times higher than those from the open conveyors. Based on measurements and modeling, the key control strategies recommended include increasing local air exhaust system capacity and relocation of exhaust hoods closer to the centrifuge drops.
Wavelength-Resolved Photon Fluxes of Indoor Light Sources: Implications for HOx Production
NASA Astrophysics Data System (ADS)
Kowal, S.; Kahan, T.
2017-12-01
Only a handful of studies have considered photolytic reactions indoors because photon fluxes at short wavelengths are generally considered to be negligible. We have measured wavelength resolved photon fluxes from indoor light sources including incandescent, halogen, compact fluorescent (CFL), and light emitting diodes (LED). In addition, fluorescent tubes, used in many offices and industrial buildings, and sunlight through windows were measured. The measured photon fluxes were used to calculate photolysis rate constants for potential indoor hydroxyl and peroxy radical (OH and HO2, "HOx") precursors: acetaldehyde (CH3CHO), formaldehyde (HCHO), hydrogen peroxide (H2O2), nitrous acid (HONO) and ozone (O3). Rate constants in conjunction with typical indoor concentrations were used to predict HOx production rates under various lighting conditions. Our results illustrate that all light sources except LEDs emit light at high enough energy to photolyze HOx precursors. Under typical lighting conditions only fluorescent tubes and sunlight will initiate significant photochemical HOx formation, and HONO and HCHO will be the only molecules that will have a strong influence on HOx levels indoors. Data from our experiments can be used in indoor air models to better predict HOx levels indoors.
Problems In Indoor Mapping and Modelling
NASA Astrophysics Data System (ADS)
Zlatanova, S.; Sithole, G.; Nakagawa, M.; Zhu, Q.
2013-11-01
Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of this research is founded on advancements in photogrammetry, computer vision and image analysis, computer graphics, robotics, laser scanning and many others. While IMM used to be the privy of engineers, planners, consultants, contractors, and designers, this is no longer the case as commercial enterprises and individuals are also beginning to apply indoor models in their business process and applications. There are three main reasons for this. Firstly, the last two decades have seen greater use of spatial information by enterprises and the public. Secondly, IMM has been complimented by advancements in mobile computing and internet communications, making it easier than ever to access and interact with spatial information. Thirdly, indoor modelling has been advanced geometrically and semantically, opening doors for developing user-oriented, context-aware applications. This reshaping of the public's attitude and expectations with regards to spatial information has realised new applications and spurred demand for indoor models and the tools to use them. This paper examines the present state of IMM and considers the research areas that deserve attention in the future. In particular the paper considers problems in IMM that are relevant to commercial enterprises and the general public, groups this paper expects will emerge as the greatest users IMM. The subject of indoor modelling and mapping is discussed here in terms of Acquisitions and Sensors, Data Structures and Modelling, Visualisation, Applications, Legal Issues and Standards. Problems are discussed in terms of those that exist and those that are emerging. Existing problems are those that are currently being researched. Emerging problems are those problems or demands that are expected to arise because of social changes, technological advancements, or commercial interests. The motivation of this work is to define a set of research problems that are either being investigated or should be investigated. These will hopefully provide a framework for assessing progress and advances in indoor modelling. The framework will be developed in the form of a problem matrix, detailing existing and emerging problems, their solutions and present best practices. Once the framework is complete it will be published online so that the IMM community can discuss and modify it as necessary. When the framework has reached a steady state an empirical benchmark will be provided to test solutions to posed problems. A yearly evaluation of the problem matrix will follow, the results of which will be published.
Barnes, Brendon R
2014-04-25
Indoor air pollution caused by the indoor burning of solid biomass fuels has been associated with Acute Respiratory Infections such as pneumonia amongst children of less than five years of age. Behavioural change interventions have been identified as a potential strategy to reduce child indoor air pollution exposure, yet very little is known about the impact of behavioural change interventions to reduce indoor air pollution. Even less is known about how behaviour change theory has been incorporated into indoor air pollution behaviour change interventions. A review of published studies spanning 1983-2013 suggests that behavioural change strategies have the potential to reduce indoor air pollution exposure by 20%-98% in laboratory settings and 31%-94% in field settings. However, the evidence is: (1) based on studies that are methodologically weak; and (2) have little or no underlying theory. The paper concludes with a call for more rigorous studies to evaluate the role of behavioural change strategies (with or without improved technologies) to reduce indoor air pollution exposure in developing countries as well as interventions that draw more strongly on existing behavioural change theory and practice.
A first generation dynamic ingress, redistribution and transport model of soil track-in: DIRT.
Johnson, D L
2008-12-01
This work introduces a spatially resolved quantitative model, based on conservation of mass and first order transfer kinetics, for following the transport and redistribution of outdoor soil to, and within, the indoor environment by track-in on footwear. Implementations of the DIRT model examined the influence of room size, rug area and location, shoe size, and mass transfer coefficients for smooth and carpeted floor surfaces using the ratio of mass loading on carpeted to smooth floor surfaces as a performance metric. Results showed that in the limit for large numbers of random steps the dual aspects of deposition to and track-off from the carpets govern this ratio. Using recently obtained experimental measurements, historic transport and distribution parameters, cleaning efficiencies for the different floor surfaces, and indoor dust deposition rates to provide model boundary conditions, DIRT predicts realistic floor surface loadings. The spatio-temporal variability in model predictions agrees with field observations and suggests that floor surface dust loadings are constantly in flux; steady state distributions are hardly, if ever, achieved.
A hybrid stochastic approach for self-location of wireless sensors in indoor environments.
Lloret, Jaime; Tomas, Jesus; Garcia, Miguel; Canovas, Alejandro
2009-01-01
Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.
Zhang, L-Z; Zhang, X-R; Miao, Q-Z; Pei, L-X
2012-08-01
Fresh air ventilation is central to indoor environmental control. Total heat exchangers can be key equipment for energy conservation in ventilation. Membranes have been used for total heat exchangers for more than a decade. Much effort has been spent to achieve water vapor permeability of various membranes; however, relatively little attention has been paid to the selectivity of moisture compared with volatile organic compounds (VOCs) through such membranes. In this investigation, the most commonly used membranes, both hydrophilic and hydrophobic ones, are tested for their permeability for moisture and five VOCs (acetic acid, formaldehyde, acetaldehyde, toluene, and ethane). The selectivity of moisture vs. VOCs in these membranes is then evaluated. With a solution-diffusion model, the solubility and diffusivity of moisture and VOCs in these membranes are calculated. The resulting data could provide some reference for future material selection. Total heat exchangers are important equipment for fresh air ventilation with energy conservation. However, their implications for indoor air quality in terms of volatile organic compound permeation have not been known. The data in this article help us to clarify the impacts on indoor VOC levels of membrane-based heat exchangers. Guidelines for material selection can be obtained for future use total heat exchangers for building ventilation. © 2011 John Wiley & Sons A/S.
Practical Implementation of Semi-Automated As-Built Bim Creation for Complex Indoor Environments
NASA Astrophysics Data System (ADS)
Yoon, S.; Jung, J.; Heo, J.
2015-05-01
In recent days, for efficient management and operation of existing buildings, the importance of as-built BIM is emphasized in AEC/FM domain. However, fully automated as-built BIM creation is a tough issue since newly-constructed buildings are becoming more complex. To manage this problem, our research group has developed a semi-automated approach, focusing on productive 3D as-built BIM creation for complex indoor environments. In order to test its feasibility for a variety of complex indoor environments, we applied the developed approach to model the `Charlotte stairs' in Lotte World Mall, Korea. The approach includes 4 main phases: data acquisition, data pre-processing, geometric drawing, and as-built BIM creation. In the data acquisition phase, due to its complex structure, we moved the scanner location several times to obtain the entire point clouds of the test site. After which, data pre-processing phase entailing point-cloud registration, noise removal, and coordinate transformation was followed. The 3D geometric drawing was created using the RANSAC-based plane detection and boundary tracing methods. Finally, in order to create a semantically-rich BIM, the geometric drawing was imported into the commercial BIM software. The final as-built BIM confirmed that the feasibility of the proposed approach in the complex indoor environment.
A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments
Lloret, Jaime; Tomas, Jesus; Garcia, Miguel; Canovas, Alejandro
2009-01-01
Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided. PMID:22412334
Differences between Outdoor and Indoor Sound Levels for Open, Tilted, and Closed Windows
Locher, Barbara; Piquerez, André; Habermacher, Manuel; Ragettli, Martina; Cajochen, Christian; Vienneau, Danielle; Foraster, Maria; Müller, Uwe; Wunderli, Jean Marc
2018-01-01
Noise exposure prediction models for health effect studies normally estimate free field exposure levels outside. However, to assess the noise exposure inside dwellings, an estimate of indoor sound levels is necessary. To date, little field data is available about the difference between indoor and outdoor noise levels and factors affecting the damping of outside noise. This is a major cause of uncertainty in indoor noise exposure prediction and may lead to exposure misclassification in health assessments. This study aims to determine sound level differences between the indoors and the outdoors for different window positions and how this sound damping is related to building characteristics. For this purpose, measurements were carried out at home in a sample of 102 Swiss residents exposed to road traffic noise. Sound pressure level recordings were performed outdoors and indoors, in the living room and in the bedroom. Three scenarios—of open, tilted, and closed windows—were recorded for three minutes each. For each situation, data on additional parameters such as the orientation towards the source, floor, and room, as well as sound insulation characteristics were collected. On that basis, linear regression models were established. The median outdoor–indoor sound level differences were of 10 dB(A) for open, 16 dB(A) for tilted, and 28 dB(A) for closed windows. For open and tilted windows, the most relevant parameters affecting the outdoor–indoor differences were the position of the window, the type and volume of the room, and the age of the building. For closed windows, the relevant parameters were the sound level outside, the material of the window frame, the existence of window gaskets, and the number of windows. PMID:29346318
Differences between Outdoor and Indoor Sound Levels for Open, Tilted, and Closed Windows.
Locher, Barbara; Piquerez, André; Habermacher, Manuel; Ragettli, Martina; Röösli, Martin; Brink, Mark; Cajochen, Christian; Vienneau, Danielle; Foraster, Maria; Müller, Uwe; Wunderli, Jean Marc
2018-01-18
Noise exposure prediction models for health effect studies normally estimate free field exposure levels outside. However, to assess the noise exposure inside dwellings, an estimate of indoor sound levels is necessary. To date, little field data is available about the difference between indoor and outdoor noise levels and factors affecting the damping of outside noise. This is a major cause of uncertainty in indoor noise exposure prediction and may lead to exposure misclassification in health assessments. This study aims to determine sound level differences between the indoors and the outdoors for different window positions and how this sound damping is related to building characteristics. For this purpose, measurements were carried out at home in a sample of 102 Swiss residents exposed to road traffic noise. Sound pressure level recordings were performed outdoors and indoors, in the living room and in the bedroom. Three scenarios-of open, tilted, and closed windows-were recorded for three minutes each. For each situation, data on additional parameters such as the orientation towards the source, floor, and room, as well as sound insulation characteristics were collected. On that basis, linear regression models were established. The median outdoor-indoor sound level differences were of 10 dB(A) for open, 16 dB(A) for tilted, and 28 dB(A) for closed windows. For open and tilted windows, the most relevant parameters affecting the outdoor-indoor differences were the position of the window, the type and volume of the room, and the age of the building. For closed windows, the relevant parameters were the sound level outside, the material of the window frame, the existence of window gaskets, and the number of windows.
Mihailovic, D T; Udovičić, V; Krmar, M; Arsenić, I
2014-02-01
We have suggested a complexity measure based method for studying the dependence of measured (222)Rn concentration time series on indoor air temperature and humidity. This method is based on the Kolmogorov complexity (KL). We have introduced (i) the sequence of the KL, (ii) the Kolmogorov complexity highest value in the sequence (KLM) and (iii) the KL of the product of time series. The noticed loss of the KLM complexity of (222)Rn concentration time series can be attributed to the indoor air humidity that keeps the radon daughters in air. © 2013 Published by Elsevier Ltd.
Indoor air quality inspection and analysis system based on gas sensor array
NASA Astrophysics Data System (ADS)
Gao, Xiang; Wang, Mingjiang; Fan, Binwen
2017-08-01
A detection and analysis system capable of measuring the concentration of four major gases in indoor air is designed. It uses four gas sensors constitute a gas sensor array, to achieve four indoor gas concentration detection, while the detection of data for further processing to reduce the cross-sensitivity between the gas sensor to improve the accuracy of detection.
Predictors of Indoor Air Concentrations in Smoking and Non-Smoking Residences
Héroux, Marie-Eve; Clark, Nina; Van Ryswyk, Keith; Mallick, Ranjeeta; Gilbert, Nicolas L.; Harrison, Ian; Rispler, Kathleen; Wang, Daniel; Anastassopoulos, Angelos; Guay, Mireille; MacNeill, Morgan; Wheeler, Amanda J.
2010-01-01
Indoor concentrations of air pollutants (benzene, toluene, formaldehyde, acetaldehyde, acrolein, nitrogen dioxide, particulate matter, elemental carbon and ozone) were measured in residences in Regina, Saskatchewan, Canada. Data were collected in 106 homes in winter and 111 homes in summer of 2007, with 71 homes participating in both seasons. In addition, data for relative humidity, temperature, air exchange rates, housing characteristics and occupants’ activities during sampling were collected. Multiple linear regression analysis was used to construct season-specific models for the air pollutants. Where smoking was a major contributor to indoor concentrations, separate models were constructed for all homes and for those homes with no cigarette smoke exposure. The housing characteristics and occupants’ activities investigated in this study explained between 11% and 53% of the variability in indoor air pollutant concentrations, with ventilation, age of home and attached garage being important predictors for many pollutants. PMID:20948949
NASA Astrophysics Data System (ADS)
Hosseini, Hamid Reza; Yunos, Mohd Yazid Mohd; Ismail, Sumarni; Yaman, Maheran
2017-12-01
This paper analysis the effects of indoor air elements on the dissatisfaction of occupants in education of environments. Tries to find the equation model for increasing the comprehension about these affects and optimizes satisfaction of occupants about indoor environment. Subsequently, increase performance of students, lecturers and staffs. As the method, a satisfaction questionnaire (SQ) and measuring environment elements (MEE) was conducted, 143 respondents at five classrooms, four staff rooms and five lectures rooms were considered. Temperature, air velocity and humidity (TVH) were used as independent variables and dissatisfaction as dependent variable. The hypothesis was tested for significant relationship between variables, and analysis was applied. Results found that indoor air quality presents direct effects on dissatisfaction of occupants and indirect effects on performance and the highest effects fallowed by temperature. These results may help to optimize the quality of efficiency and effectiveness in education environments.
Strategies to Reduce Indoor Tanning
Holman, Dawn M.; Fox, Kathleen A.; Glenn, Jeffrey D.; Guy, Gery P.; Watson, Meg; Baker, Katie; Cokkinides, Vilma; Gottlieb, Mark; Lazovich, DeAnn; Perna, Frank M.; Sampson, Blake P.; Seidenberg, Andrew B.; Sinclair, Craig; Geller, Alan C.
2015-01-01
Exposure to ultraviolet radiation from indoor tanning device use is associated with an increased risk of skin cancer, including risk of malignant melanoma, and is an urgent public health problem. By reducing indoor tanning, future cases of skin cancer could be prevented, along with the associated morbidity, mortality, and healthcare costs. On August 20, 2012, the CDC hosted a meeting to discuss the current body of evidence on strategies to reduce indoor tanning as well as research gaps. Using the Action Model to Achieve Healthy People 2020 Overarching Goals as a framework, the current paper provides highlights on the topics that were discussed, including (1) the state of the evidence on strategies to reduce indoor tanning; (2) the tools necessary to effectively assess, monitor, and evaluate the short- and long-term impact of interventions designed to reduce indoor tanning; and (3) strategies to align efforts at the national, state, and local levels through transdisciplinary collaboration and coordination across multiple sectors. Although many challenges and barriers exist, a coordinated, multilevel, transdisciplinary approach has the potential to reduce indoor tanning and prevent future cases of skin cancer. PMID:23683986
Indoor External Radiation Risk in Densely Populated Regions of Southern Nigeria
NASA Astrophysics Data System (ADS)
Ife-Adediran, Oluwatobi O.; Uwadiae, Iyobosa B.
2018-02-01
It is known that certain types of building materials contain significant concentrations of natural radionuclides; consequently, exposure to indoor background radiation is from the combined radioactivity from the soil as well as building materials; indoor exposures therefore have higher radiation hazard potentials than outdoor exposures in this regard and hence, need to be monitored. In this paper, an evaluation of background ionizing radiation from different buildings in Lagos and Ibadan, Southwestern Nigeria was carried out to determine the exposure rate of the general public to indoor ionizing radiation. 630 in situ measurements from the different buildings were taken using a Geiger Muller counter (model GQ-320 Plus). The indoor dose rates (i.e., 50-120 nGy/h) were within the world average values while the Annual Effective Dose for most of the buildings were above the world average AED for indoor gamma exposure from building materials. The mean AED for Lagos and Ibadan due to indoor exposures were 0.37 and 0.39 mSv/y with Excess Lifetime Cancer Risk of 0.99E-3 and 1.05E-3, respectively.
Indoor External Radiation Risk in Densely Populated Regions of Southern Nigeria
NASA Astrophysics Data System (ADS)
Ife-Adediran, Oluwatobi O.; Uwadiae, Iyobosa B.
2018-05-01
It is known that certain types of building materials contain significant concentrations of natural radionuclides; consequently, exposure to indoor background radiation is from the combined radioactivity from the soil as well as building materials; indoor exposures therefore have higher radiation hazard potentials than outdoor exposures in this regard and hence, need to be monitored. In this paper, an evaluation of background ionizing radiation from different buildings in Lagos and Ibadan, Southwestern Nigeria was carried out to determine the exposure rate of the general public to indoor ionizing radiation. 630 in situ measurements from the different buildings were taken using a Geiger Muller counter (model GQ-320 Plus). The indoor dose rates (i.e., 50-120 nGy/h) were within the world average values while the Annual Effective Dose for most of the buildings were above the world average AED for indoor gamma exposure from building materials. The mean AED for Lagos and Ibadan due to indoor exposures were 0.37 and 0.39 mSv/y with Excess Lifetime Cancer Risk of 0.99E-3 and 1.05E-3, respectively.
NASA Astrophysics Data System (ADS)
Raymer, J. H.; Akland, G.; Johnson, T. R.; Long, T.; Michael, L.; Cauble, L.; McCombs, M.
Oxygenated additives in gasoline are designed to decrease the ozone-forming hydrocarbons and total air toxics, yet they can increase the emissions of aldehydes and thus increase human exposure to these toxic compounds. This paper describes a study conducted to characterize targeted aldehydes in microenvironments in Sacramento, CA, and Milwaukee, WI, and to improve our understanding of the impact of the urban environment on human exposure to air toxics. Data were obtained from microenvironmental concentration measurements, integrated, 24-h personal measurements, indoor and outdoor pollutant monitors at the participants' residences, from ambient pollutant monitors at fixed-site locations in each city, and from real-time diaries and questionnaires completed by the technicians and participants. As part of this study, a model to predict personal exposures based on individual time/activity data was developed for comparison to measured concentrations. Predicted concentrations were generally within 25% of the measured concentrations. The microenvironments that people encounter daily provide for widely varying exposures to aldehydes. The activities that occur in those microenvironments can modulate the aldehyde concentrations dramatically, especially for environments such as "indoor at home." By considering personal activity, location (microenvironment), duration in the microenvironment, and a knowledge of the general concentrations of aldehydes in the various microenvironments, a simple model can do a reasonably good job of predicting the time-averaged personal exposures to aldehydes, even in the absence of monitoring data. Although concentrations of aldehydes measured indoors at the participants' homes tracked well with personal exposure, there were instances where personal exposures and indoor concentrations differed significantly. Key to the ability to predict exposure based on time/activity data is the quality and completeness of the microenvironmental characterizations for the chemicals of interest. Consistent with many earlier studies, personal exposures are difficult to predict using data from regional outdoor monitors.
Cellular Automata-Based Application for Driver Assistance in Indoor Parking Areas.
Caballero-Gil, Cándido; Caballero-Gil, Pino; Molina-Gil, Jezabel
2016-11-15
This work proposes an adaptive recommendation mechanism for smart parking that takes advantage of the popularity of smartphones and the rise of the Internet of Things. The proposal includes a centralized system to forecast available indoor parking spaces, and a low-cost mobile application to obtain data of actual and predicted parking occupancy. The described scheme uses data from both sources bidirectionally so that the centralized forecast system is fed with data obtained with the distributed system based on smartphones, and vice versa. The mobile application uses different wireless technologies to provide the forecast system with actual parking data and receive from the system useful recommendations about where to park. Thus, the proposal can be used by any driver to easily find available parking spaces in indoor facilities. The client software developed for smartphones is a lightweight Android application that supplies precise indoor positioning systems based on Quick Response codes or Near Field Communication tags, and semi-precise indoor positioning systems based on Bluetooth Low Energy beacons. The performance of the proposed approach has been evaluated by conducting computer simulations and real experimentation with a preliminary implementation. The results have shown the strengths of the proposal in the reduction of the time and energy costs to find available parking spaces.
Cellular Automata-Based Application for Driver Assistance in Indoor Parking Areas †
Caballero-Gil, Cándido; Caballero-Gil, Pino; Molina-Gil, Jezabel
2016-01-01
This work proposes an adaptive recommendation mechanism for smart parking that takes advantage of the popularity of smartphones and the rise of the Internet of Things. The proposal includes a centralized system to forecast available indoor parking spaces, and a low-cost mobile application to obtain data of actual and predicted parking occupancy. The described scheme uses data from both sources bidirectionally so that the centralized forecast system is fed with data obtained with the distributed system based on smartphones, and vice versa. The mobile application uses different wireless technologies to provide the forecast system with actual parking data and receive from the system useful recommendations about where to park. Thus, the proposal can be used by any driver to easily find available parking spaces in indoor facilities. The client software developed for smartphones is a lightweight Android application that supplies precise indoor positioning systems based on Quick Response codes or Near Field Communication tags, and semi-precise indoor positioning systems based on Bluetooth Low Energy beacons. The performance of the proposed approach has been evaluated by conducting computer simulations and real experimentation with a preliminary implementation. The results have shown the strengths of the proposal in the reduction of the time and energy costs to find available parking spaces. PMID:27854282
Youth indoor tanning and skin cancer prevention: lessons from tobacco control.
Seidenberg, Andrew B; Mahalingam-Dhingra, Aditya; Weinstock, Martin A; Sinclair, Craig; Geller, Alan C
2015-02-01
Youth use of ultraviolet-emitting indoor tanning beds represents a present and emerging public health crisis. Nearly 30% of white female high school students report tanning indoors, and a quarter of high school tanners have used a tanning bed more than 20 times in the past year. Despite the significant health risks of tanning beds, including potentially deadly melanoma and eye problems, limited actions have been taken in the U.S. to protect youth. Tobacco control policies and campaigns, which have sharply reduced youth smoking, may provide a useful framework to control indoor tanning among young people. This article describes several evidence-based tobacco control strategies with potential applicability to indoor tanning within the context of the U.S. Further, current tobacco control policies and current indoor tanning policies in the U.S. are compared, and recommendations on how to curtail youth indoor tanning are discussed. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
NFC Internal: An Indoor Navigation System
Ozdenizci, Busra; Coskun, Vedat; Ok, Kerem
2015-01-01
Indoor navigation systems have recently become a popular research field due to the lack of GPS signals indoors. Several indoors navigation systems have already been proposed in order to eliminate deficiencies; however each of them has several technical and usability limitations. In this study, we propose NFC Internal, a Near Field Communication (NFC)-based indoor navigation system, which enables users to navigate through a building or a complex by enabling a simple location update, simply by touching NFC tags those are spread around and orient users to the destination. In this paper, we initially present the system requirements, give the design details and study the viability of NFC Internal with a prototype application and a case study. Moreover, we evaluate the performance of the system and compare it with existing indoor navigation systems. It is seen that NFC Internal has considerable advantages and significant contributions to existing indoor navigation systems in terms of security and privacy, cost, performance, robustness, complexity, user preference and commercial availability. PMID:25825976
A PARTICIPANT-BASED APPROACH TO INDOOR/OUTDOOR AIR MONITORING IN COMMUNITY HEALTH STUDIES
Community health studies of traffic-related air pollution have been hampered by the cost and participant burden associated with collecting household-level exposure data. The current study utilized a novel participant-based approach to collect indoor and outdoor air monitoring da...
*A participant-based approach to indoor/outdoor air monitoring in Community Health Studies
Community health studies of traffic-related air pollution have been hampered by the cost and participant burden associated with collecting household-level exposure data. The current study utilized a participant-based approach to collect indoor and outdoor air monitoring data from...
Long-term integrating samplers for indoor air and sub slab soil gas at VI sites
Vapor intrusion (VI) site assessments are plagued by substantial spatial and temporal variability that makes exposure and risk assessment difficult. Most risk-based decision making for volatile organic compound (VOC) exposure in the indoor environment is based on health benchmark...
Indoor Tanning Among High School Students in the United States, 2009 and 2011
Guy, Gery P.; Berkowitz, Zahava; Tai, Eric; Holman, Dawn M.; Jones, Sherry Everett; Richardson, Lisa C.
2015-01-01
IMPORTANCE Indoor tanning is associated with an increased risk of skin cancer, including melanoma, and is particularly dangerous for younger and more frequent indoor tanners. OBJECTIVE To examine the prevalence of indoor tanning and frequent indoor tanning (≥10 times during the 12 months before each survey) and their association with health-related behaviors. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional study examined data from the 2009 and 2011 national Youth Risk Behavior Surveys, which used nationally representative samples of US high school students representing approximately 15.5 million students each survey year. The study included 25 861 students who answered the indoor tanning question. MAIN OUTCOMES AND MEASURES The prevalence of indoor tanning and frequent indoor tanning were examined as well as their association with demographic characteristics and health-related behaviors using multivariable logistic regression modeling. RESULTS The prevalence of indoor tanning was greater among female, older, and non-Hispanic white students. Indoor tanning was highest among female students aged 18 years or older, with 31.5% engaging in indoor tanning in 2011, and among non-Hispanic white female students, with 29.3% engaging in indoor tanning in 2011. Among female students, the adjusted prevalence of indoor tanning decreased from 26.4% in 2009 to 20.7% in 2011. Among female and male students, indoor tanning was associated with other risk-taking behaviors, such as binge drinking (P < .001 and P = .006, respectively), unhealthy weight control practices (P < .001, for both), and having sexual intercourse (P < .001, for both). Additionally, indoor tanning among female students was associated with using illegal drugs (P < .001) and having sexual intercourse with 4 or more persons (P = .03); use among male students was associated with taking steroids without a physician’s prescription (P < .001), smoking cigarettes daily (P = .03), and attempting suicide (P = .006). More than half of respondents engaging in indoor tanning reported frequent use of the devices. CONCLUSIONS AND RELEVANCE Indoor tanning is common among high school students. Public health efforts are needed to change social norms regarding tanned skin and to increase awareness, knowledge, and behaviors related to indoor tanning. The clustering of risky behaviors suggests a need for coordinated, multifaceted approaches, including primary care physician counseling, to address such behaviors among adolescents. PMID:24577222
Low-frequency outdoor-indoor noise level difference for wind turbine assessment.
Thorsson, Pontus; Persson Waye, Kerstin; Smith, Michael; Ögren, Mikael; Pedersen, Eja; Forssén, Jens
2018-03-01
To increase the understanding of wind turbine noise on sleep, human physiological reactions need to be studied in a controlled laboratory setting. The paper presents an outdoor-indoor noise level difference as a function of frequency, applicable to creating wind turbine indoor sounds with the outdoor sounds as input. For this, a combination of measurement data and modeling results has been used. The suggested data are provided in a table.
Fast fingerprint database maintenance for indoor positioning based on UGV SLAM.
Tang, Jian; Chen, Yuwei; Chen, Liang; Liu, Jingbin; Hyyppä, Juha; Kukko, Antero; Kaartinen, Harri; Hyyppä, Hannu; Chen, Ruizhi
2015-03-04
Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI) fingerprints of Signals of OPportunity (SOP) is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV) platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz) and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning.
Concentrations of indoor pollutants database: User's manual
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1992-05-01
This manual describes the computer-based database on indoor air pollutants. This comprehensive database alloys helps utility personnel perform rapid searches on literature related to indoor air pollutants. Besides general information, it provides guidance for finding specific information on concentrations of indoor air pollutants. The manual includes information on installing and using the database as well as a tutorial to assist the user in becoming familiar with the procedures involved in doing bibliographic and summary section searches. The manual demonstrates how to search for information by going through a series of questions that provide search parameters such as pollutants type, year,more » building type, keywords (from a specific list), country, geographic region, author's last name, and title. As more and more parameters are specified, the list of references found in the data search becomes smaller and more specific to the user's needs. Appendixes list types of information that can be input into the database when making a request. The CIP database allows individual utilities to obtain information on indoor air quality based on building types and other factors in their own service territory. This information is useful for utilities with concerns about indoor air quality and the control of indoor air pollutants. The CIP database itself is distributed by the Electric Power Software Center and runs on IBM PC-compatible computers.« less
Concentrations of indoor pollutants database: User`s manual
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1992-05-01
This manual describes the computer-based database on indoor air pollutants. This comprehensive database alloys helps utility personnel perform rapid searches on literature related to indoor air pollutants. Besides general information, it provides guidance for finding specific information on concentrations of indoor air pollutants. The manual includes information on installing and using the database as well as a tutorial to assist the user in becoming familiar with the procedures involved in doing bibliographic and summary section searches. The manual demonstrates how to search for information by going through a series of questions that provide search parameters such as pollutants type, year,more » building type, keywords (from a specific list), country, geographic region, author`s last name, and title. As more and more parameters are specified, the list of references found in the data search becomes smaller and more specific to the user`s needs. Appendixes list types of information that can be input into the database when making a request. The CIP database allows individual utilities to obtain information on indoor air quality based on building types and other factors in their own service territory. This information is useful for utilities with concerns about indoor air quality and the control of indoor air pollutants. The CIP database itself is distributed by the Electric Power Software Center and runs on IBM PC-compatible computers.« less
Kadiyala, Akhil; Kaur, Devinder; Kumar, Ashok
2013-02-01
The present study developed a novel approach to modeling indoor air quality (IAQ) of a public transportation bus by the development of hybrid genetic-algorithm-based neural networks (also known as evolutionary neural networks) with input variables optimized from using the regression trees, referred as the GART approach. This study validated the applicability of the GART modeling approach in solving complex nonlinear systems by accurately predicting the monitored contaminants of carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), sulfur dioxide (SO2), 0.3-0.4 microm sized particle numbers, 0.4-0.5 microm sized particle numbers, particulate matter (PM) concentrations less than 1.0 microm (PM10), and PM concentrations less than 2.5 microm (PM2.5) inside a public transportation bus operating on 20% grade biodiesel in Toledo, OH. First, the important variables affecting each monitored in-bus contaminant were determined using regression trees. Second, the analysis of variance was used as a complimentary sensitivity analysis to the regression tree results to determine a subset of statistically significant variables affecting each monitored in-bus contaminant. Finally, the identified subsets of statistically significant variables were used as inputs to develop three artificial neural network (ANN) models. The models developed were regression tree-based back-propagation network (BPN-RT), regression tree-based radial basis function network (RBFN-RT), and GART models. Performance measures were used to validate the predictive capacity of the developed IAQ models. The results from this approach were compared with the results obtained from using a theoretical approach and a generalized practicable approach to modeling IAQ that included the consideration of additional independent variables when developing the aforementioned ANN models. The hybrid GART models were able to capture majority of the variance in the monitored in-bus contaminants. The genetic-algorithm-based neural network IAQ models outperformed the traditional ANN methods of the back-propagation and the radial basis function networks. The novelty of this research is the development of a novel approach to modeling vehicular indoor air quality by integration of the advanced methods of genetic algorithms, regression trees, and the analysis of variance for the monitored in-vehicle gaseous and particulate matter contaminants, and comparing the results obtained from using the developed approach with conventional artificial intelligence techniques of back propagation networks and radial basis function networks. This study validated the newly developed approach using holdout and threefold cross-validation methods. These results are of great interest to scientists, researchers, and the public in understanding the various aspects of modeling an indoor microenvironment. This methodology can easily be extended to other fields of study also.
Bohlin, Pernilla; Audy, Ondřej; Škrdlíková, Lenka; Kukučka, Petr; Vojta, Šimon; Přibylová, Petra; Prokeš, Roman; Čupr, Pavel; Klánová, Jana
2014-11-01
Indoor air pollution has been recognized as an important risk factor for human health, especially in areas where people tend to spend most of their time indoors. Many semi-volatile organic compounds (SVOCs) have primarily indoor sources and are present in orders of magnitude higher concentrations indoors than outdoors. Despite this, awareness of SVOCs in indoor air and assessment of the link between indoor concentrations and human health have lagged behind those of outdoor air. This is partially related to challenges associated with indoor sampling of SVOCs. Passive air samplers (PASs), which are widely accepted in established outdoor air monitoring networks, have been used to fill the knowledge gaps on indoor SVOCs distribution. However, their applicability for indoor environments and the assessment of human health risks lack sufficient experimental data. To address this issue, we performed an indoor calibration study of polyurethane foam (PUF) PAS deployed in a double-dome chamber, covering both legacy and new SVOC classes. PUF-PAS and a continuous low-volume active air sampler (AAS) were co-deployed for a calibration period of twelve weeks. Based on the results from this evaluation, PUF-PAS in a double-bowl chamber is recommended for indoor sampling and health risk assessment of gas phase SVOCs, including novel brominated flame retardants (nBFR) providing sufficient exposure time is applied. Data for particle associated SVOCs suffered from significant uncertainties caused by low level of detection and low precision in this study. A more open chamber design for indoor studies may allow for higher sampling rates (RS) and better performance for the particle associated SVOCs.
Jeong, Seol Young; Jo, Hyeong Gon; Kang, Soon Ju
2014-03-21
A tracking service like asset management is essential in a dynamic hospital environment consisting of numerous mobile assets (e.g., wheelchairs or infusion pumps) that are continuously relocated throughout a hospital. The tracking service is accomplished based on the key technologies of an indoor location-based service (LBS), such as locating and monitoring multiple mobile targets inside a building in real time. An indoor LBS such as a tracking service entails numerous resource lookups being requested concurrently and frequently from several locations, as well as a network infrastructure requiring support for high scalability in indoor environments. A traditional centralized architecture needs to maintain a geographic map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor mobile asset management (MAM) platform, and proposes an architecture for multiple trackees (such as mobile assets) and trackers based on the proposed distributed platform in real time. In order to verify the suggested platform, scalability performance according to increases in the number of concurrent lookups was evaluated in a real test bed. Tracking latency and traffic load ratio in the proposed tracking architecture was also evaluated.
Bleakley, Amy; Jordan, Amy; Ellithorpe, Morgan E; Lazovich, DeAnn; Grossman, Sara; Glanz, Karen
2018-03-15
Indoor tanning is a risk factor for melanoma among young white women. Health communications can be an effective way of reaching this population and promoting behavior change. The purpose of this study was (i) to investigate the associations between intention to quit indoor tanning and attitudes, normative pressure, and efficacy about quitting, and (ii) to identify beliefs about quitting indoor tanning that can be used to design effective health communication messages to reduce skin cancer risk. A national online survey was conducted with 279 non-Hispanic white women ages 18-25 in the USA who are indoor tanners. The survey, based on the reasoned action approach, assessed intention, attitudes, norms, and efficacy and their corresponding underlying beliefs related to quitting indoor tanning, along with other known covariates. Data were collected in November/December 2015. Intention to quit indoor tanning was significantly associated with attitudes, specifically with the beliefs that it would "reduce damage to skin" (increased intention) and "make me less happy" (decreased intention). While self-efficacy was not related to intention to quit indoor tanning, injunctive normative beliefs were with key referent groups including mothers, friends, and romantic partners. Messages aimed at discouraging indoor tanning among young, non-Hispanic, white women should highlight the salient belief that quitting indoor tanning will reduce skin damage, counter the belief that it will make them less happy, and highlight key people who would approve of them quitting indoor tanning.
Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin
2014-07-02
Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.
Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin
2014-01-01
Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital. PMID:24991942
NASA Astrophysics Data System (ADS)
Gu, Wenjun; Zhang, Weizhi; Wang, Jin; Amini Kashani, M. R.; Kavehrad, Mohsen
2015-01-01
Over the past decade, location based services (LBS) have found their wide applications in indoor environments, such as large shopping malls, hospitals, warehouses, airports, etc. Current technologies provide wide choices of available solutions, which include Radio-frequency identification (RFID), Ultra wideband (UWB), wireless local area network (WLAN) and Bluetooth. With the rapid development of light-emitting-diodes (LED) technology, visible light communications (VLC) also bring a practical approach to LBS. As visible light has a better immunity against multipath effect than radio waves, higher positioning accuracy is achieved. LEDs are utilized both for illumination and positioning purpose to realize relatively lower infrastructure cost. In this paper, an indoor positioning system using VLC is proposed, with LEDs as transmitters and photo diodes as receivers. The algorithm for estimation is based on received-signalstrength (RSS) information collected from photo diodes and trilateration technique. By appropriately making use of the characteristics of receiver movements and the property of trilateration, estimation on three-dimensional (3-D) coordinates is attained. Filtering technique is applied to enable tracking capability of the algorithm, and a higher accuracy is reached compare to raw estimates. Gaussian mixture Sigma-point particle filter (GM-SPPF) is proposed for this 3-D system, which introduces the notion of Gaussian Mixture Model (GMM). The number of particles in the filter is reduced by approximating the probability distribution with Gaussian components.
Characterization of fine particulate matter in Ohio: Indoor, outdoor, and personal exposures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Crist, Kevin C.; Liu, Bian; Kim, Myoungwoo
2008-01-15
Ambient, indoor, and personal PM{sub 2.5} concentrations were assessed based on an exhaustive study of PM{sub 2.5} performed in Ohio from 1999 to 2000. Locations in Columbus, one in an urban corridor and the other in a suburban area were involved. A third rural location in Athens, Ohio, was also established. At all three locations, elementary schools were utilized to determine outdoor, indoor, and personal PM{sub 2.5} concentrations for fourth and fifth grade students using filter-based measurements. Three groups of 30 students each were used for personal sampling at each school. Continuous ambient PM{sub 2.5} mass concentrations were also measuredmore » with tapered element oscillating microbalances (TEOMs). At all three sites, personal and indoor PM{sub 2.5} concentrations exceeded outdoor levels. This trend is consistent on all week days and most evident in the spring as compared to fall and winter. The ambient PM{sub 2.5} concentrations were similar among the three sites, suggesting the existence of a common regional source influence. At all the three sites, larger variations were found in personal and indoor PM{sub 2.5} than ambient levels. The strongest correlations were found between indoor and personal concentrations, indicating that personal PM{sub 2.5} exposures were significantly affected by indoor PM{sub 2.5} than by ambient PM{sub 2.5}. This was further confirmed by the indoor to outdoor (I/O) ratios of PM{sub 2.5} concentrations, which were greater when school was in session than non-school days when the students were absent.« less
Jakobsen, Markus D.; Jay, Kenneth; Persson, Roger; Andersen, Lars L.
2015-01-01
Monitoring of indoor climate is an essential part of occupational health and safety. While questionnaires are commonly used for surveillance, not all workers may perceive an identical indoor climate similarly. The aim of this study was to evaluate perceived indoor climate among workers with chronic pain compared with pain-free colleagues and to determine the influence of central sensitization on this perception. Eighty-two male slaughterhouse workers, 49 with upper-limb chronic pain and 33 pain-free controls, replied to a questionnaire with 13 items of indoor climate complaints. Pressure pain threshold (PPT) was measured in muscles of the arm, shoulder, and lower leg. Cross-sectional associations were determined using general linear models controlled for age, smoking, and job position. The number of indoor climate complaints was twice as high among workers with chronic pain compared with pain-free controls (1.8 [95% CI: 1.3–2.3] versus 0.9 [0.4–1.5], resp.). PPT of the nonpainful leg muscle was negatively associated with the number of complaints. Workers with chronic pain reported more indoor climate complaints than pain-free controls despite similar actual indoor climate. Previous studies that did not account for musculoskeletal pain in questionnaire assessment of indoor climate may be biased. Central sensitization likely explains the present findings. PMID:26425368
Building Assessment Survey and Evaluation Data (BASE)
The Building Assessment Survey and Evaluation (BASE) study was a five year study to characterize determinants of indoor air quality and occupant perceptions in representative public and commercial office buildings across the U.S. This data source is the raw data from this study about the indoor air quality.
Factors affecting recreation participation by Vermont residents
Thomas A. More; Herbert E. Echelberger; Edward J. Koenemann; Edward J. Koenemann
1990-01-01
Long-term recreation planning requires an understanding of recreation participation patterns. This study examined Vermonters' participation in 27 leisure activities from three domains (outdoor, resource based, and indoor) to see how such participation differed in each domain. Indoor activities were the most popular, followed by resource-based activities and...
ASSESSMENT OF VENTILATION SYSTEMS AS RELATED TO THE BASE STUDY
The U.S. EPA's Office of Radiation and Indoor Air studied 100 public and private office buildings across the U.S. from 1994 1998. The purpose of the study, entitled the Building Assessment Survey and Evaluation (BASE) Study, was to: (a) provide a distribution of indoor air quali...
Predicting indoor pollutant concentrations, and applications to air quality management
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lorenzetti, David M.
Because most people spend more than 90% of their time indoors, predicting exposure to airborne pollutants requires models that incorporate the effect of buildings. Buildings affect the exposure of their occupants in a number of ways, both by design (for example, filters in ventilation systems remove particles) and incidentally (for example, sorption on walls can reduce peak concentrations, but prolong exposure to semivolatile organic compounds). Furthermore, building materials and occupant activities can generate pollutants. Indoor air quality depends not only on outdoor air quality, but also on the design, maintenance, and use of the building. For example, ''sick building'' symptomsmore » such as respiratory problems and headaches have been related to the presence of air-conditioning systems, to carpeting, to low ventilation rates, and to high occupant density (1). The physical processes of interest apply even in simple structures such as homes. Indoor air quality models simulate the processes, such as ventilation and filtration, that control pollutant concentrations in a building. Section 2 describes the modeling approach, and the important transport processes in buildings. Because advection usually dominates among the transport processes, Sections 3 and 4 describe methods for predicting airflows. The concluding section summarizes the application of these models.« less
NASA Astrophysics Data System (ADS)
Rai, Aakash C.; Lin, Chao-Hsin; Chen, Qingyan
2015-02-01
Ozone-terpene reactions are important sources of indoor ultrafine particles (UFPs), a potential health hazard for human beings. Humans themselves act as possible sites for ozone-initiated particle generation through reactions with squalene (a terpene) that is present in their skin, hair, and clothing. This investigation developed a numerical model to probe particle generation from ozone reactions with clothing worn by humans. The model was based on particle generation measured in an environmental chamber as well as physical formulations of particle nucleation, condensational growth, and deposition. In five out of the six test cases, the model was able to predict particle size distributions reasonably well. The failure in the remaining case demonstrated the fundamental limitations of nucleation models. The model that was developed was used to predict particle generation under various building and airliner cabin conditions. These predictions indicate that ozone reactions with human-worn clothing could be an important source of UFPs in densely occupied classrooms and airliner cabins. Those reactions could account for about 40% of the total UFPs measured on a Boeing 737-700 flight. The model predictions at this stage are indicative and should be improved further.
Marion, OUIDIR; Lise, GIORGIS-ALLEMAND; Sarah, LYON-CAEN; Xavier, MORELLI; Claire, CRACOWSKI; Sabrina, PONTET; Isabelle, PIN; Johanna, LEPEULE; Valérie, SIROUX; Rémy, SLAMA
2016-01-01
Studies of air pollution effects during pregnancy generally only consider exposure in the outdoor air at the home address. We aimed to compare exposure models differing in their ability to account for the spatial resolution of pollutants, space-time activity and indoor air pollution levels. We recruited 40 pregnant women in the Grenoble urban area, France, who carried a Global Positioning System (GPS) during up to 3 weeks; in a subgroup, indoor measurements of fine particles (PM2.5) were conducted at home (n=9) and personal exposure to nitrogen dioxide (NO2) was assessed using passive air samplers (n=10). Outdoor concentrations of NO2, and PM2.5 were estimated from a dispersion model with a fine spatial resolution. Women spent on average 16 h per day at home. Considering only outdoor levels, for estimates at the home address, the correlation between the estimate using the nearest background air monitoring station and the estimate from the dispersion model was high (r=0.93) for PM2.5 and moderate (r=0.67) for NO2. The model incorporating clean GPS data was less correlated with the estimate relying on raw GPS data (r=0.77) than the model ignoring space-time activity (r=0.93). PM2.5 outdoor levels were not to moderately correlated with estimates from the model incorporating indoor measurements and space-time activity (r=−0.10 to 0.47), while NO2 personal levels were not correlated with outdoor levels (r=−0.42 to 0.03). In this urban area, accounting for space-time activity little influenced exposure estimates; in a subgroup of subjects (n=9), incorporating indoor pollution levels seemed to strongly modify them. PMID:26300245
Exploring the effect of diffuse reflection on indoor localization systems based on RSSI-VLC.
Mohammed, Nazmi A; Elkarim, Mohammed Abd
2015-08-10
This work explores and evaluates the effect of diffuse light reflection on the accuracy of indoor localization systems based on visible light communication (VLC) in a high reflectivity environment using a received signal strength indication (RSSI) technique. The effect of the essential receiver (Rx) and transmitter (Tx) parameters on the localization error with different transmitted LED power and wall reflectivity factors is investigated at the worst Rx coordinates for a directed/overall link. Since this work assumes harsh operating conditions (i.e., a multipath model, high reflectivity surfaces, worst Rx position), an error of ≥ 1.46 m is found. To achieve a localization error in the range of 30 cm under these conditions with moderate LED power (i.e., P = 0.45 W), low reflectivity walls (i.e., ρ = 0.1) should be used, which would enable a localization error of approximately 7 mm at the room's center.
Indoor air quality analysis based on Hadoop
NASA Astrophysics Data System (ADS)
Tuo, Wang; Yunhua, Sun; Song, Tian; Liang, Yu; Weihong, Cui
2014-03-01
The air of the office environment is our research object. The data of temperature, humidity, concentrations of carbon dioxide, carbon monoxide and ammonia are collected peer one to eight seconds by the sensor monitoring system. And all the data are stored in the Hbase database of Hadoop platform. With the help of HBase feature of column-oriented store and versioned (automatically add the time column), the time-series data sets are bulit based on the primary key Row-key and timestamp. The parallel computing programming model MapReduce is used to process millions of data collected by sensors. By analysing the changing trend of parameters' value at different time of the same day and at the same time of various dates, the impact of human factor and other factors on the room microenvironment is achieved according to the liquidity of the office staff. Moreover, the effective way to improve indoor air quality is proposed in the end of this paper.
Understanding interactions in the adsorption of gaseous organic compounds to indoor materials.
Ongwandee, Maneerat; Chatsuvan, Thabtim; Suksawas Na Ayudhya, Wichitsawat; Morris, John
2017-02-01
We studied adsorption of organic compounds to a wide range of indoor materials, including plastics, gypsum board, carpet, and many others, under various relative humidity conditions by applying a conceptual model of the free energy of interfacial interactions of both van der Waals and Lewis acid-base (e-donor/acceptor) types. Data used for the analyses were partitioning coefficients of adsorbates between surface and gas phase obtained from three sources: our sorption experiments and two other published studies. Target organic compounds included apolars, monopolars, and bipolars. We established correlations of partitioning coefficients of adsorbates for a considered surface with the corresponding hexadecane/air partitioning coefficients of the adsorbates which are used as representative of a van der Waals descriptor instead of vapor pressure. The logarithmic adsorption coefficients of the apolars and weak bases, e.g., aliphatics and aromatics, to indoor materials linearly correlates well with the logarithmic hexadecane/air partitioning coefficients regardless of the surface polarity. The surface polarity in terms of e-donor/acceptor interactions becomes important for adsorption of the strong bases and bipolars, e.g., amines, phenols, and alcohols, to unpainted gypsum board. Under dry or humid conditions, the adsorption to flat plastic materials still linearly correlates well with the van der Waals interactions of the adsorbates, but no correlations were observed for the adsorption to fleecy or plush materials, e.g., carpet. Adsorption of highly bipolar compounds, e.g., phenol and isopropanol, is strongly affected by humidity, attributed to Lewis acid-base interactions with modified surfaces.
Elío, J; Crowley, Q; Scanlon, R; Hodgson, J; Zgaga, L
2018-05-01
Radon is a naturally occurring gas, classified as a Class 1 human carcinogen, being the second most significant cause of lung cancer after tobacco smoking. A robust spatial definition of radon distribution in the built environment is therefore essential for understanding the relationship between radon exposure and its adverse health effects on the general population. Using Ireland as a case study, we present a methodology to estimate an average indoor radon concentration and calculate the expected radon-related lung cancer incidence. We use this approach to define Radon Priority Areas at the administrative level of Electoral Divisions (EDs). Geostatistical methods were applied to a data set of almost 32,000 indoor radon measurements, sampled in Ireland between 1992 and 2013. Average indoor radon concentrations by ED range from 21 to 338 Bq m -3 , corresponding to an effective dose ranging from 0.8 to 13.3 mSv y -1 respectively. Radon-related lung cancer incidence by ED was calculated using a dose-effect model giving between 15 and 239 cases per million people per year, depending on the ED. Based on these calculations, together with the population density, we estimate that of the approximately 2,300 lung cancer cases currently diagnosed in Ireland annually, about 280 may be directly linked to radon exposure. This figure does not account for the synergistic effect of radon exposure with other factors (e.g. tobacco smoking), so likely represents a minimum estimate. Our approach spatially defines areas with the expected highest incidence of radon-related lung cancer, even though indoor radon concentrations for these areas may be moderate or low. We therefore recommend that both indoor radon concentration and population density by small area are considered when establishing national radon action plans. Copyright © 2018 Elsevier Ltd. All rights reserved.
Analysis of isocyanates in indoor dust.
Bekki, Kanae; Uchiyama, Shigehisa; Kunugita, Naoki
2018-05-04
Isocyanates are harmful semi-volatile organic compounds that are emitted from various consumer products like polyurethane foam-based mattresses. Although it is a concern that isocyanates might accumulate in indoor dust, causing infants and toddlers, in particular, to be exposed to them, little information is available on the levels of isocyanates in the indoor environment. In this study, we investigated the suitability of an analytical method for determining the presence and level of isocyanates in the indoor dust. The method we developed displayed acceptable linearity, accuracy, and precision in the analysis of eleven different isocyanates. By using this analytical method, we could detect five isocyanates (ICA, MIC, EIC, PIC, and PHI) and quantify three isocyanates (MIC, EIC, and PHI) in indoor dust collected in different houses. This study is the first to focus on the pollution of indoor dust by isocyanates, and the tested method is suitable for the estimation of the level of isocyanate exposure. Graphical abstract ᅟ.
Carol A. Clausen; Vina W. Yang
2004-01-01
Concerns about indoor air quality due to mold growth have increased dramatically in the United States. In the absence of proper moisture management, fungicides need to be developed for indoor use to control mold establishment. An ideal fungicide for prevention of indoor mold growth on wood-based materials needs to specifically prevent spore germination and provide long...
Indoor air pollutants and health in the United Arab Emirates.
Yeatts, Karin B; El-Sadig, Mohamed; Leith, David; Kalsbeek, William; Al-Maskari, Fatma; Couper, David; Funk, William E; Zoubeidi, Taoufik; Chan, Ronna L; Trent, Chris B; Davidson, Christopher A; Boundy, Maryanne G; Kassab, Maamoon M; Hasan, Mohamed Y; Rusyn, Ivan; Gibson, Jacqueline MacDonald; Olshan, Andrew F
2012-05-01
Comprehensive global data on the health effects of indoor air pollutants are lacking. There are few large population-based multi-air pollutant health assessments. Further, little is known about indoor air health risks in the Middle East, especially in countries undergoing rapid economic development. To provide multifactorial indoor air exposure and health data, we conducted a population-based study of indoor air pollution and health in the United Arab Emirates (UAE). We conducted a cross-sectional study in a population-based sample of 628 households in the UAE. Indoor air pollutants [sulfur dioxide (SO2), nitrogen dioxide (NO2), hydrogen sulfide (H2S), formaldehyde (HCHO), carbon monoxide (CO), and particulate matter] were measured using passive samplers over a 7-day period. Health information was collected from 1,590 household members via in-person interviews. Participants in households with quantified SO2, NO2, and H2S (i.e., with measured concentrations above the limit of quantification) were twice as likely to report doctor-diagnosed asthma. Participants in homes with quantified SO2 were more likely to report wheezing symptoms {ever wheezing, prevalence odds ratio [POR] 1.79 [95% confidence interval (CI) 1.05, 3.05]; speech-limiting wheeze, POR 3.53 (95% CI: 1.06, 11.74)}. NO2 and H2S were similarly associated with wheezing symptoms. Quantified HCHO was associated with neurologic symptoms (difficulty concentrating POR 1.47; 95% CI: 1.02, 2.13). Burning incense daily was associated with increased headaches (POR 1.87; 95% CI: 1.09, 3.21), difficulty concentrating (POR 3.08; 95% CI: 1.70, 5.58), and forgetfulness (POR 2.68: 95% CI: 1.47, 4.89). This study provides new information regarding potential health risks from pollutants commonly found in indoor environments in the UAE and other countries. Multipollutant exposure and health assessments in cohort studies are needed to better characterize health effects of indoor air pollutants.
Indoor Air Pollutants and Health in the United Arab Emirates
El-Sadig, Mohamed; Leith, David; Kalsbeek, William; Al-Maskari, Fatma; Couper, David; Funk, William E.; Zoubeidi, Taoufik; Chan, Ronna L.; Trent, Chris B.; Davidson, Christopher A.; Boundy, Maryanne G.; Kassab, Maamoon M.; Hasan, Mohamed Y.; Rusyn, Ivan; Gibson, Jacqueline MacDonald; Olshan, Andrew F.
2012-01-01
Background: Comprehensive global data on the health effects of indoor air pollutants are lacking. There are few large population-based multi–air pollutant health assessments. Further, little is known about indoor air health risks in the Middle East, especially in countries undergoing rapid economic development. Objectives: To provide multifactorial indoor air exposure and health data, we conducted a population-based study of indoor air pollution and health in the United Arab Emirates (UAE). Methods: We conducted a cross-sectional study in a population-based sample of 628 households in the UAE. Indoor air pollutants [sulfur dioxide (SO2), nitrogen dioxide (NO2), hydrogen sulfide (H2S), formaldehyde (HCHO), carbon monoxide (CO), and particulate matter] were measured using passive samplers over a 7-day period. Health information was collected from 1,590 household members via in-person interviews. Results: Participants in households with quantified SO2, NO2, and H2S (i.e., with measured concentrations above the limit of quantification) were twice as likely to report doctor-diagnosed asthma. Participants in homes with quantified SO2 were more likely to report wheezing symptoms {ever wheezing, prevalence odds ratio [POR] 1.79 [95% confidence interval (CI) 1.05, 3.05]; speech-limiting wheeze, POR 3.53 (95% CI: 1.06, 11.74)}. NO2 and H2S were similarly associated with wheezing symptoms. Quantified HCHO was associated with neurologic symptoms (difficulty concentrating POR 1.47; 95% CI: 1.02, 2.13). Burning incense daily was associated with increased headaches (POR 1.87; 95% CI: 1.09, 3.21), difficulty concentrating (POR 3.08; 95% CI: 1.70, 5.58), and forgetfulness (POR 2.68: 95% CI: 1.47, 4.89). Conclusions: This study provides new information regarding potential health risks from pollutants commonly found in indoor environments in the UAE and other countries. Multipollutant exposure and health assessments in cohort studies are needed to better characterize health effects of indoor air pollutants. PMID:22357138
Evaluation of an Indoor Sonic Boom Subjective Test Facility at NASA Langley Research Center
NASA Technical Reports Server (NTRS)
Loubeau, Alexandra; Rathsam, Jonathan; Klos, Jacob
2011-01-01
A sonic boom simulator at NASA Langley Research Center has been constructed for research on human response to low-amplitude sonic booms heard indoors. Research in this facility will ultimately lead to development of a psychoacoustic model for single indoor booms. The first subjective test was designed to explore indoor human response to variations in sonic boom rise time and amplitude. Another goal was to identify loudness level variability across listener locations within the facility. Finally, the test also served to evaluate the facility as a laboratory research tool for studying indoor human response to sonic booms. Subjects listened to test sounds and were asked to rate their annoyance relative to a reference boom. Measurements of test signals were conducted for objective analysis and correlation with subjective responses. Results confirm the functionality of the facility and effectiveness of the test methods and indicate that loudness level does not fully describe indoor annoyance to the selected sonic boom signals.
NASA Technical Reports Server (NTRS)
Rathsam, Jonathan; Loubeau, Alexandra; Klos, Jacob
2013-01-01
The National Aeronautics and Space Administration's High Speed Project is developing a predictive capability for annoyance caused by shaped sonic booms transmitted indoors. The predictive capability is intended for use by aircraft designers as well as by aircraft noise regulators who are considering lifting the current prohibition on overland civil supersonic flight. The goal of the current study is to use an indoor simulator to validate two models developed using headphone tests for annoyance caused by sonic booms with and without rattle augmentation. The predictors in the proposed models include Moore and Glasberg's Stationary Loudness Level, the time derivative of Moore and Glasberg's time-varying short-term Loudness Level, and the difference between two weighted sound exposure levels, CSEL-ASEL. The indoor simulator provides a more realistic listening environment than headphones due to lowfrequency sound reproduction down to 6 Hz, which also causes perceptible tactile vibration. The results of this study show that a model consisting of {PL + (CSEL-ASEL)} is a reliable predictor of annoyance caused by shaped sonic booms alone, rattle sounds alone, and shaped sonic booms and rattle sounds together.
Neural network based optimal control of HVAC&R systems
NASA Astrophysics Data System (ADS)
Ning, Min
Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the supervisory controller, a set of five adaptive PI (proportional-integral) controllers are designed for each of the five local control loops of the HVAC&R system. The five controllers are used to track optimal set points and zone air temperature set points. Parameters of these PI controllers are tuned online to reduce tracking errors. The updating rules are derived from Lyapunov stability analysis. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.
Study on water evaporation rate from indoor swimming pools
NASA Astrophysics Data System (ADS)
Rzeźnik, Ilona
2017-11-01
The air relative humidity in closed spaces of indoor swimming pools influences significantly on users thermal comfort and the stability of the building structure, so its preservation on suitable level is very important. For this purpose, buildings are equipped with HVAC systems which provide adequate level of humidity. The selection of devices and their technical parameters is made using the mathematical models of water evaporation rate in the unoccupied and occupied indoor swimming pool. In the literature, there are many papers describing this phenomena but the results differ from each other. The aim of the study was the experimental verification of published models of evaporation rate in the pool. The tests carried out on a laboratory scale, using model of indoor swimming pool, measuring 99cm/68cm/22cm. The model was equipped with water spray installation with six nozzles to simulate conditions during the use of the swimming pool. The measurements were made for conditions of sports pools (water temperature 24°C) and recreational swimming pool (water temperature 34°C). According to the recommendations the air temperature was about 2°C higher than water temperature, and the relative humidity ranged from 40% to 55%. Models Shah and Biasin & Krumm were characterized by the best fit to the results of measurements on a laboratory scale.
Hwang, Bosun; Han, Jonghee; Choi, Jong Min; Park, Kwang Suk
2008-11-01
The purpose of this study was to develop an unobtrusive energy expenditure (EE) measurement system using an infrared (IR) sensor-based activity monitoring system to measure indoor activities and to estimate individual quantitative EE. IR-sensor activation counts were measured with a Bluetooth-based monitoring system and the standard EE was calculated using an established regression equation. Ten male subjects participated in the experiment and three different EE measurement systems (gas analyzer, accelerometer, IR sensor) were used simultaneously in order to determine the regression equation and evaluate the performance. As a standard measurement, oxygen consumption was simultaneously measured by a portable metabolic system (Metamax 3X, Cortex, Germany). A single room experiment was performed to develop a regression model of the standard EE measurement from the proposed IR sensor-based measurement system. In addition, correlation and regression analyses were done to compare the performance of the IR system with that of the Actigraph system. We determined that our proposed IR-based EE measurement system shows a similar correlation to the Actigraph system with the standard measurement system.
Indoor radon regulation using tabulated values of temporal radon variation.
Tsapalov, Andrey; Kovler, Konstantin
2018-03-01
Mass measurements of indoor radon concentrations have been conducted for about 30 years. In most of the countries, a national reference/action/limit level is adopted, limiting the annual average indoor radon (AAIR) concentration. However, until now, there is no single and generally accepted international protocol for determining the AAIR with a known confidence interval, based on measurements of different durations. Obviously, as the duration of measurements increases, the uncertainty of the AAIR estimation decreases. The lack of the information about the confidence interval of the determined AAIR level does not allow correct comparison with the radon reference level. This greatly complicates development of an effective indoor radon measurement protocol and strategy. The paper proposes a general principle of indoor radon regulation, based on the simple criteria widely used in metrology, and introduces a new parameter - coefficient of temporal radon variation K V (t) that depends on the measurement duration and determines the uncertainty of the AAIR. An algorithm for determining K V (t) based on the results of annual continuous radon monitoring in experimental rooms is proposed. Included are indoor radon activity concentrations and equilibrium equivalent concentration (EEC) of radon progeny. The monitoring was conducted in 10 selected experimental rooms located in 7 buildings, mainly in the Moscow region (Russia), from 2006 to 2013. The experimental and tabulated values of K V (t) and also the values of the coefficient of temporal EEC variation depending on the mode and duration of the measurements were obtained. The recommendations to improve the efficiency and reliability of indoor radon regulation are given. The importance of taking into account the geological factors is discussed. The representativity of the results of the study is estimated and the approach for their verification is proposed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Unexpectedly high indoor hydroxyl radical concentrations associated with nitrous acid
Gómez Alvarez, Elena; Amedro, Damien; Afif, Charbel; Gligorovski, Sasho; Schoemaecker, Coralie; Fittschen, Christa; Doussin, Jean-Francois; Wortham, Henri
2013-01-01
The hydroxyl (OH) radical is the most important oxidant in the atmosphere since it controls its self-oxidizing capacity. The main sources of OH radicals are the photolysis of ozone and the photolysis of nitrous acid (HONO). Due to the attenuation of solar radiation in the indoor environment, the possibility of OH formation through photolytic pathways indoors has been ignored up to now. In the indoor air, the ozonolysis of alkenes has been suggested as an alternative route of OH formation. Models and indirect measurements performed up to now according to this hypothesis suggest concentrations of OH radicals on the order of 104–105 molecules per cubic centimeter. Here, we present direct measurements of significant amounts of OH radicals of up to 1.8⋅106 molecules per cubic centimeter during an experimental campaign carried out in a school classroom in Marseille. This concentration is on the same order of magnitude of outdoor OH levels in the urban scenario. We also show that photolysis of HONO is an important source of OH radicals indoors under certain conditions (i.e., direct solar irradiation inside the room). Additionally, the OH concentrations were found to follow a linear dependence with the product J(HONO)⋅[HONO]. This was also supported by using a simple quasiphotostationary state model on the OH radical budget. These findings force a change in our understanding of indoor air quality because the reactivity linked to OH would involve formation of secondary species through chemical reactions that are potentially more hazardous than the primary pollutants in the indoor air. PMID:23898188
Refining Time-Activity Classification of Human Subjects Using the Global Positioning System
Hu, Maogui; Li, Wei; Li, Lianfa; Houston, Douglas; Wu, Jun
2016-01-01
Background Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Methods Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Results Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. Conclusions The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well with just GPS, road and tax parcel data. However, caution is warranted when generalizing the model developed from a small number of subjects to other populations. PMID:26919723
Long-term radon concentrations estimated from 210Po embedded in glass
Lively, R.S.; Steck, D.J.
1993-01-01
Measured surface-alpha activity on glass exposed in radon chambers and houses has a linear correlation to the integrated radon exposure. Experimental results in chambers and houses have been obtained on glass exposed to radon concentrations between 100 Bq m-3 and 9 MBq m-3 for periods of a few days to several years. Theoretical calculations support the experimental results through a model that predicts the fractions of airborne activity that deposit and become embedded or adsorbed. The combination of measured activity and calculated embedded fraction for a given deposition environment can be applied to most indoor areas and produces a better estimate for lifetime radon exposure than estimates based on short-term indoor radon measurements.
Indoor Photogrammetry Aided with Uwb Navigation
NASA Astrophysics Data System (ADS)
Masiero, A.; Fissore, F.; Guarnieri, A.; Vettore, A.
2018-05-01
The subject of photogrammetric surveying with mobile devices, in particular smartphones, is becoming of significant interest in the research community. Nowadays, the process of providing 3D point clouds with photogrammetric procedures is well known. However, external information is still typically needed in order to move from the point cloud obtained from images to a 3D metric reconstruction. This paper investigates the integration of information provided by an UWB positioning system with visual based reconstruction to produce a metric reconstruction. Furthermore, the orientation (with respect to North-East directions) of the obtained model is assessed thanks to the use of inertial sensors included in the considered UWB devices. Results of this integration are shown on two case studies in indoor environments.
Degradation of indoor limonene by outdoor ozone: A cascade of secondary organic aerosols.
Rösch, Carolin; Wissenbach, Dirk K; Franck, Ulrich; Wendisch, Manfred; Schlink, Uwe
2017-07-01
In indoor air, terpene-ozone reactions can form secondary organic aerosols (SOA) in a transient process. 'Real world' measurements conducted in a furnished room without air conditioning were modelled involving the indoor background of airborne particulate matter, outdoor ozone infiltrated by natural ventilation, repeated transient limonene evaporations, and different subsequent ventilation regimes. For the given setup, we disentangled the development of nucleated, coagulated, and condensed SOA fractions in the indoor air and calculated the time dependence of the aerosol mass fraction (AMF) by means of a process model. The AMF varied significantly between 0.3 and 5.0 and was influenced by the ozone limonene ratio and the background particles which existed prior to SOA formation. Both influencing factors determine whether nucleation or adsorption processes are preferred; condensation is strongly intensified by particulate background. The results provide evidence that SOA levels in natural indoor environments can surpass those known from chamber measurements. An indicator for the SOA forming potential of limonene was found to be limona ketone. Multiplying its concentration (in μg/m 3 ) by 450(±100) provides an estimate of the concentration of the reacted limonene. This can be used to detect a high particle formation potential due to limonene pollution, e.g. in epidemiological studies considering adverse health effects of indoor air pollutants. Copyright © 2017 Elsevier Ltd. All rights reserved.
Van Loy, Michael D; Nazaroff, William W; Daisey, Joan M
1998-10-01
Recently developed models and data describing the interactions of gas-phase semi-volatile organic compounds with indoor surfaces are employed to examine the effects of sorption on nicotine's suitability as an environmental tobacco smoke (ETS) marker. Using parameters from our studies of nicotine sorption on carpet, painted wallboard, and stainless steel and previously published data on ETS particle deposition, the dynamic behavior of nicotine was modeled in two different indoor environments: a house and a stainless steel chamber. The results show that apparently contradictory observations of nicotine's behavior in indoor air can be understood by considering the effects of sorption under different experimental conditions. In indoor environments in which smoking has occurred regularly for an extended period, the sorbed mass of nicotine is very large relative to the mass emitted by a single cigarette. The importance of nicotine adsorption relative to ventilation as a gas-phase removal mechanism is reduced. Where smoking occurs less regularly or the indoor surfaces are cleaned prior to smoking (as in a laboratory chamber), nicotine deposition is more significant. Nicotine concentrations closely track the levels of other ETS constituents in environments with habitual smoking if the data are averaged over a period significantly longer than the period between cigarette combustion episodes. However, nicotine is not a suitable tracer for predicting ETS exposures at fine time scales or in settings where smoking occurs infrequently and irregularly.
Optical Indoor Positioning System Based on TFT Technology
Gőzse, István
2015-01-01
A novel indoor positioning system is presented in the paper. Similarly to the camera-based solutions, it is based on visual detection, but it conceptually differs from the classical approaches. First, the objects are marked by LEDs, and second, a special sensing unit is applied, instead of a camera, to track the motion of the markers. This sensing unit realizes a modified pinhole camera model, where the light-sensing area is fixed and consists of a small number of sensing elements (photodiodes), and it is the hole that can be moved. The markers are tracked by controlling the motion of the hole, such that the light of the LEDs always hits the photodiodes. The proposed concept has several advantages: Apart from its low computational demands, it is insensitive to the disturbing ambient light. Moreover, as every component of the system can be realized by simple and inexpensive elements, the overall cost of the system can be kept low. PMID:26712753
Zhou, Mu; Zhang, Qiao; Xu, Kunjie; Tian, Zengshan; Wang, Yanmeng; He, Wei
2015-01-01
Due to the wide deployment of wireless local area networks (WLAN), received signal strength (RSS)-based indoor WLAN localization has attracted considerable attention in both academia and industry. In this paper, we propose a novel page rank-based indoor mapping and localization (PRIMAL) by using the gene-sequenced unlabeled WLAN RSS for simultaneous localization and mapping (SLAM). Specifically, first of all, based on the observation of the motion patterns of the people in the target environment, we use the Allen logic to construct the mobility graph to characterize the connectivity among different areas of interest. Second, the concept of gene sequencing is utilized to assemble the sporadically-collected RSS sequences into a signal graph based on the transition relations among different RSS sequences. Third, we apply the graph drawing approach to exhibit both the mobility graph and signal graph in a more readable manner. Finally, the page rank (PR) algorithm is proposed to construct the mapping from the signal graph into the mobility graph. The experimental results show that the proposed approach achieves satisfactory localization accuracy and meanwhile avoids the intensive time and labor cost involved in the conventional location fingerprinting-based indoor WLAN localization. PMID:26404274
Cai, Hao; Long, Weiding; Li, Xianting; Kong, Lingjuan; Xiong, Shuang
2010-06-15
In case hazardous contaminants are suddenly released indoors, the prompt and proper emergency responses are critical to protect occupants. This paper aims to provide a framework for determining the optimal combination of ventilation and evacuation strategies by considering the uncertainty of source locations. The certainty of source locations is classified as complete certainty, incomplete certainty, and complete uncertainty to cover all the possible situations. According to this classification, three types of decision analysis models are presented. A new concept, efficiency factor of contaminant source (EFCS), is incorporated in these models to evaluate the payoffs of the ventilation and evacuation strategies. A procedure of decision-making based on these models is proposed and demonstrated by numerical studies of one hundred scenarios with ten ventilation modes, two evacuation modes, and five source locations. The results show that the models can be useful to direct the decision analysis of both the ventilation and evacuation strategies. In addition, the certainty of the source locations has an important effect on the outcomes of the decision-making. Copyright 2010 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, Jason; Winkler, Jon
Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less
Woods, Jason; Winkler, Jon
2018-01-31
Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less
Barnes, Brendon R.
2014-01-01
Indoor air pollution caused by the indoor burning of solid biomass fuels has been associated with Acute Respiratory Infections such as pneumonia amongst children of less than five years of age. Behavioural change interventions have been identified as a potential strategy to reduce child indoor air pollution exposure, yet very little is known about the impact of behavioural change interventions to reduce indoor air pollution. Even less is known about how behaviour change theory has been incorporated into indoor air pollution behaviour change interventions. A review of published studies spanning 1983–2013 suggests that behavioural change strategies have the potential to reduce indoor air pollution exposure by 20%–98% in laboratory settings and 31%–94% in field settings. However, the evidence is: (1) based on studies that are methodologically weak; and (2) have little or no underlying theory. The paper concludes with a call for more rigorous studies to evaluate the role of behavioural change strategies (with or without improved technologies) to reduce indoor air pollution exposure in developing countries as well as interventions that draw more strongly on existing behavioural change theory and practice. PMID:24776723
Logistic regression model for detecting radon prone areas in Ireland.
Elío, J; Crowley, Q; Scanlon, R; Hodgson, J; Long, S
2017-12-01
A new high spatial resolution radon risk map of Ireland has been developed, based on a combination of indoor radon measurements (n=31,910) and relevant geological information (i.e. Bedrock Geology, Quaternary Geology, soil permeability and aquifer type). Logistic regression was used to predict the probability of having an indoor radon concentration above the national reference level of 200Bqm -3 in Ireland. The four geological datasets evaluated were found to be statistically significant, and, based on combinations of these four variables, the predicted probabilities ranged from 0.57% to 75.5%. Results show that the Republic of Ireland may be divided in three main radon risk categories: High (HR), Medium (MR) and Low (LR). The probability of having an indoor radon concentration above 200Bqm -3 in each area was found to be 19%, 8% and 3%; respectively. In the Republic of Ireland, the population affected by radon concentrations above 200Bqm -3 is estimated at ca. 460k (about 10% of the total population). Of these, 57% (265k), 35% (160k) and 8% (35k) are in High, Medium and Low Risk Areas, respectively. Our results provide a high spatial resolution utility which permit customised radon-awareness information to be targeted at specific geographic areas. Copyright © 2017 Elsevier B.V. All rights reserved.
Tan, Yanliang; Ishikawa, Tetsuo; Janik, Miroslaw; Tokonami, Shinji; Hosoda, Masahiro; Sorimachi, Atsuyuki; Kearfott, Kimberlee
2015-12-01
The accident at the Fukushima Daiichi Nuclear Power Plant (FDNPP) in Japan resulted in significant releases of fission products. While substantial data exist concerning outdoor air radioactivity following the accident, the resulting indoor radioactivity remains pure speculation without a proper method for estimating the ratio of the indoor to outdoor airborne radioactivity, termed the airborne sheltering factor (ASF). Lacking a meaningful value of the ASF, it is difficult to assess the inhalation doses to residents and evacuees even when outdoor radionuclide concentrations are available. A simple model was developed and the key parameters needed to estimate the ASF were obtained through data fitting of selected indoor and outdoor airborne radioactivity measurement data obtained following the accident at a single location. Using the new model with values of the air exchange rate, interior air volume, and the inner surface area of the dwellings, the ASF can be estimated for a variety of dwelling types. Assessment of the inhalation dose to individuals readily follows from the value of the ASF, the person's indoor occupancy factor, and the measured outdoor radioactivity concentration. Copyright © 2015 Elsevier B.V. All rights reserved.
Determining the ventilation and aerosol deposition rates from routine indoor-air measurements.
Halios, Christos H; Helmis, Costas G; Deligianni, Katerina; Vratolis, Sterios; Eleftheriadis, Konstantinos
2014-01-01
Measurement of air exchange rate provides critical information in energy and indoor-air quality studies. Continuous measurement of ventilation rates is a rather costly exercise and requires specific instrumentation. In this work, an alternative methodology is proposed and tested, where the air exchange rate is calculated by utilizing indoor and outdoor routine measurements of a common pollutant such as SO2, whereas the uncertainties induced in the calculations are analytically determined. The application of this methodology is demonstrated, for three residential microenvironments in Athens, Greece, and the results are also compared against ventilation rates calculated from differential pressure measurements. The calculated time resolved ventilation rates were applied to the mass balance equation to estimate the particle loss rate which was found to agree with literature values at an average of 0.50 h(-1). The proposed method was further evaluated by applying a mass balance numerical model for the calculation of the indoor aerosol number concentrations, using the previously calculated ventilation rate, the outdoor measured number concentrations and the particle loss rates as input values. The model results for the indoors' concentrations were found to be compared well with the experimentally measured values.
NASA Astrophysics Data System (ADS)
Chan, S.; Sohn, G.
2012-06-01
The past few years have seen wide spread adoption of outdoor positioning services, mainly GPS, being incorporated into everyday devices such as smartphones and tablets. While outdoor positioning has been well received by the public, its indoor counterpart has been mostly limited to private use due to its higher costs and complexity for setting up the proper environment. The objective of this research is to provide an affordable mean for indoor localization using wireless local area network (WLAN) Wi-Fi technology. We combined two different Wi-Fi approaches to locate a user. The first method involves the use of matching the pre-recorded received signal strength (RSS) from nearby access points (AP), to the data transmitted from the user on the fly. This is commonly known as "fingerprint matching". The second approach is a distance-based trilateration approach using three known AP coordinates detected on the user's device to derive the position. The combination of the two steps enhances the accuracy of the user position in an indoor environment allowing location-based services (LBS) such as mobile augmented reality (MAR) to be deployed more effectively in the indoor environment. The mapping of the RSS map can also prove useful to IT planning personnel for covering locations with no Wi-Fi coverage (ie. dead spots). The experiments presented in this research helps provide a foundation for the integration of indoor with outdoor positioning to create a seamless transition experience for users.
Syazwan, Aizat Ismail; Hafizan, Juahir; Baharudin, Mohd Rafee; Azman, Ahmad Zaid Fattah; Izwyn, Zulkapri; Zulfadhli, Ismail; Syahidatussyakirah, Katis
2013-01-01
Objectives: The purpose of this study was to analyze the relationship of airborne chemicals and the physical work environment risk element on the indoor air symptoms of nonindustrial workers. Design: A cross-sectional study consisting of 200 office workers. A random selection of 200 buildings was analyzed for exposure and indoor air symptoms based on a pilot study in the Klang Valley, Malaysia. Methods: A set of modified published questionnaires by the Department of Occupational Safety and Health (DOSH), Malaysia and a previous study (MM040NA questionnaire) pertaining to indoor air symptoms was used in the evaluation process of the indoor air symptoms. Statistical analyses involving logistic regression and linear regression were used to determine the relationship between exposure and indoor air symptoms for use in the development of an indoor risk matrix. Results: The results indicate that some indoor air pollutants (carbon monoxide, formaldehyde, total volatile organic compound, and dust) are related to indoor air symptoms of men and women. Temperature and relative humidity showed a positive association with complaints related to the perceived indoor environmental condition (drafts and inconsistency of temperature). Men predominantly reported general symptoms when stratification of gender involved exposure to formaldehyde. Women reported high levels of complaints related to mucosal and general symptoms from exposure to the dust level indoors. Conclusion: Exposure to pollutants (total volatile organic compounds, carbon monoxide, and formaldehyde) and physical stressors (air temperature and relative humidity) influence reported symptoms of office workers. These parameters should be focused upon and graded as one of the important elements in the grading procedure when qualitatively evaluating the indoor environment. PMID:23526736
Indoor tanning bed use and risk of food addiction based on the modified Yale Food Addiction Scale
Li, Wen-Qing; McGeary, John E.; Cho, Eunyoung; Flint, Alan; Wu, Shaowei; Ascherio, Alberto; Rimm, Eric; Field, Alison; Qureshi, Abrar A.
2017-01-01
Abstract The popularity of indoor tanning may be partly attributed to the addictive characteristics of tanning for some individuals. We aimed to determine the association between frequent indoor tanning, which we view as a surrogate for tanning addiction, and food addiction. A total of 67,910 women were included from the Nurses’ Health Study II. In 2005, we collected information on indoor tanning during high school/college and age 25-35 years, and calculated the average use of indoor tanning during these periods. Food addiction was defined as ≥3 clinically significant symptoms plus clinically significant impairment or distress, assessed in 2009 using a modified version of the Yale Food Addiction Scale. Totally 23.3% (15,822) of the participants reported indoor tanning at high school/college or age 25-35 years. A total of 5,557 (8.2%) women met the criteria for food addiction. We observed a dose–response relationship between frequency of indoor tanning and the likelihood of food addiction (Ptrend < 0.0001), independent of depression, BMI, and other confounders. Compared with never indoor tanners, the odds ratio (95% confidence interval) of food addiction was 1.07 (0.99-1.17) for average indoor tanning 1-2 times/year, 1.25 (1.09-1.43) for 3-5 times/year, 1.34 (1.14-1.56) for 6-11 times/year, 1.61 (1.35-1.91) for 12-23 times/year, and 2.98 (1.95-4.57) for 24 or more times/year. Frequent indoor tanning before or at early adulthood is associated with prevalence of food addiction at middle age. Our data support the addictive property of frequent indoor tanning, which may guide intervention strategies to curb indoor tanning and prevent skin cancer. PMID:28808183
Indoor tanning bed use and risk of food addiction based on the modified Yale Food Addiction Scale.
Li, Wen-Qing; E McGeary, John; Cho, Eunyoung; Flint, Alan; Wu, Shaowei; Ascherio, Alberto; Rimm, Eric; Field, Alison; A Qureshi, Abrar
2016-10-17
The popularity of indoor tanning may be partly attributed to the addictive characteristics of tanning for some individuals. We aimed to determine the association between frequent indoor tanning, which we view as a surrogate for tanning addiction, and food addiction. A total of 67,910 women were included from the Nurses' Health Study II. In 2005, we collected information on indoor tanning during high school/college and age 25-35 years, and calculated the average use of indoor tanning during these periods. Food addiction was defined as ≥3 clinically significant symptoms plus clinically significant impairment or distress, assessed in 2009 using a modified version of the Yale Food Addiction Scale. Totally 23.3% (15,822) of the participants reported indoor tanning at high school/college or age 25-35 years. A total of 5,557 (8.2%) women met the criteria for food addiction. We observed a dose-response relationship between frequency of indoor tanning and the likelihood of food addiction (P trend <0.0001), independent of depression, BMI, and other confounders. Compared with never indoor tanners, the odds ratio (95% confidence interval) of food addiction was 1.07 (0.99-1.17) for average indoor tanning 1-2 times/year, 1.25 (1.09-1.43) for 3-5 times/year, 1.34 (1.14-1.56) for 6-11 times/year, 1.61 (1.35-1.91) for 12-23 times/year, and 2.98 (1.95-4.57) for 24 or more times/year. Frequent indoor tanning before or at early adulthood is associated with prevalence of food addiction at middle age. Our data support the addictive property of frequent indoor tanning, which may guide intervention strategies to curb indoor tanning and prevent skin cancer.
Syazwan, Aizat Ismail; Hafizan, Juahir; Baharudin, Mohd Rafee; Azman, Ahmad Zaid Fattah; Izwyn, Zulkapri; Zulfadhli, Ismail; Syahidatussyakirah, Katis
2013-01-01
The purpose of this study was to analyze the relationship of airborne chemicals and the physical work environment risk element on the indoor air symptoms of nonindustrial workers. A cross-sectional study consisting of 200 office workers. A random selection of 200 buildings was analyzed for exposure and indoor air symptoms based on a pilot study in the Klang Valley, Malaysia. A set of modified published questionnaires by the Department of Occupational Safety and Health (DOSH), Malaysia and a previous study (MM040NA questionnaire) pertaining to indoor air symptoms was used in the evaluation process of the indoor air symptoms. Statistical analyses involving logistic regression and linear regression were used to determine the relationship between exposure and indoor air symptoms for use in the development of an indoor risk matrix. The results indicate that some indoor air pollutants (carbon monoxide, formaldehyde, total volatile organic compound, and dust) are related to indoor air symptoms of men and women. Temperature and relative humidity showed a positive association with complaints related to the perceived indoor environmental condition (drafts and inconsistency of temperature). Men predominantly reported general symptoms when stratification of gender involved exposure to formaldehyde. Women reported high levels of complaints related to mucosal and general symptoms from exposure to the dust level indoors. Exposure to pollutants (total volatile organic compounds, carbon monoxide, and formaldehyde) and physical stressors (air temperature and relative humidity) influence reported symptoms of office workers. These parameters should be focused upon and graded as one of the important elements in the grading procedure when qualitatively evaluating the indoor environment.
Zuo, JinXing; Ji, Wei; Ben, YuJie; Hassan, Muhammad Azher; Fan, WenHong; Bates, Liam; Dong, ZhaoMin
2018-05-19
Due to time- and expense- consuming of conventional indoor PM 2.5 (particulate matter with aerodynamic diameter of less than 2.5 μm) sampling, the sample size in previous studies was generally small, which leaded to high heterogeneity in indoor PM 2.5 exposure assessment. Based on 4403 indoor air monitors in Beijing, this study evaluated indoor PM 2.5 exposure from 15th March 2016 to 14th March 2017. Indoor PM 2.5 concentration in Beijing was estimated to be 38.6 ± 18.4 μg/m 3 . Specifically, the concentration in non-heating season was 34.9 ± 15.8 μg/m 3 , which was 24% lower than that in heating season (46.1 ± 21.2 μg/m 3 ). A significant correlation between indoor and ambient PM 2.5 (p < 0.05) was evident with an infiltration factor of 0.21, and the ambient PM 2.5 contributed approximately 52% and 42% to indoor PM 2.5 for non-heating and heating seasons, respectively. Meanwhile, the mean indoor/outdoor (I/O) ratio was estimated to be 0.73 ± 0.54. Finally, the adjusted PM 2.5 exposure level integrating the indoor and outdoor impact was calculated to be 46.8 ± 27.4 μg/m 3 , which was approximately 42% lower than estimation only relied on ambient PM 2.5 concentration. This study is the first attempt to employ big data from commercial air monitors to evaluate indoor PM 2.5 exposure and risk in Beijing, which may be instrumental to indoor PM 2.5 pollution control. Copyright © 2018 Elsevier Ltd. All rights reserved.
Indoor tanning and risk of early-onset basal cell carcinoma
Ferrucci, Leah M.; Cartmel, Brenda; Molinaro, Annette M.; Leffell, David J.; Bale, Allen E.; Mayne, Susan T.
2011-01-01
Background Despite a rise in incidence of basal cell carcinoma (BCC) among young people and the ubiquity of indoor tanning in this population, few epidemiologic studies have investigated this exposure-disease relationship. Objective Evaluate the association between indoor tanning and early-onset BCC. Methods BCC cases (n=376) and controls with minor benign skin conditions (n=390) under age 40 were identified through Yale Dermatopathology. Participants provided information on ever indoor tanning, age of initiation, frequency, duration, burns while tanning, and type of tanning device during an in-person interview. We calculated odds ratios (OR) and 95% confidence intervals (CI) using multivariate logistic regression with never indoor tanners as the referent group. Results Ever indoor tanning was associated with a 69% increased risk of early-onset BCC (95% CI=1.15-2.48). This association was stronger among women (OR=2.14, 95% CI=1.31-3.47), for multiple BCCs (OR=2.16, 95% CI=1.26-3.70), and for BCCs on the trunk and extremities (OR=2.81, 95% CI=1.57-5.02). Risk increased dose-dependently with years used regular indoor tanning devices (p-trend=0.003), number of overall burns (p-trend=<0.001) and burns to biopsy site (p-trend=<0.001) from indoor tanning. Approximately one-quarter (27%) of early-onset BCCs (or 43% among women) could be prevented if individuals never tanned indoors. Limitations Potential recall bias of indoor tanning by cases and generalizability of the control population suggest replication in other studies is warranted. Conclusions Indoor tanning was a strong risk factor for early-onset BCC, particularly among women. Indoor tanning should continue to be targeted by both policy-based and behavioral interventions, as the impact on BCC-associated morbidity may be substantial. PMID:22153793
Setton, Eleanor M; Keller, C Peter; Cloutier-Fisher, Denise; Hystad, Perry W
2008-01-01
Background Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. Conclusion The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy. PMID:18638398
Space Subdivision in Indoor Mobile Laser Scanning Point Clouds Based on Scanline Analysis.
Zheng, Yi; Peter, Michael; Zhong, Ruofei; Oude Elberink, Sander; Zhou, Quan
2018-06-05
Indoor space subdivision is an important aspect of scene analysis that provides essential information for many applications, such as indoor navigation and evacuation route planning. Until now, most proposed scene understanding algorithms have been based on whole point clouds, which has led to complicated operations, high computational loads and low processing speed. This paper presents novel methods to efficiently extract the location of openings (e.g., doors and windows) and to subdivide space by analyzing scanlines. An opening detection method is demonstrated that analyses the local geometric regularity in scanlines to refine the extracted opening. Moreover, a space subdivision method based on the extracted openings and the scanning system trajectory is described. Finally, the opening detection and space subdivision results are saved as point cloud labels which will be used for further investigations. The method has been tested on a real dataset collected by ZEB-REVO. The experimental results validate the completeness and correctness of the proposed method for different indoor environment and scanning paths.
Influenza transmission during extreme indoor conditions in a low-resource tropical setting
NASA Astrophysics Data System (ADS)
Tamerius, James; Ojeda, Sergio; Uejio, Christopher K.; Shaman, Jeffrey; Lopez, Brenda; Sanchez, Nery; Gordon, Aubree
2017-04-01
Influenza transmission occurs throughout the planet across wide-ranging environmental conditions. However, our understanding of the environmental factors mediating transmission is evaluated using outdoor environmental measurements, which may not be representative of the indoor conditions where influenza is transmitted. In this study, we examined the relationship between indoor environment and influenza transmission in a low-resource tropical population. We used a case-based ascertainment design to enroll 34 households with a suspected influenza case and then monitored households for influenza, while recording indoor temperature and humidity data in each household. We show that the indoor environment is not commensurate with outdoor conditions and that the relationship between indoor and outdoor conditions varies significantly across homes. We also show evidence of influenza transmission in extreme indoor environments. Specifically, our data suggests that indoor environments averaged 29 °C, 18 g/kg specific humidity, and 68 % relative humidity across 15 transmission events observed. These indoor settings also exhibited significant temporal variability with temperatures as high as 39 °C and specific and relative humidity increasing to 22 g/kg and 85 %, respectively, during some transmission events. However, we were unable to detect differences in the transmission efficiency by indoor temperature or humidity conditions. Overall, these results indicate that laboratory studies investigating influenza transmission and virus survival should increase the range of environmental conditions that they assess and that observational studies investigating the relationship between environment and influenza activity should use caution using outdoor environmental measurements since they can be imprecise estimates of the conditions that mediate transmission indoors.
Influenza transmission during extreme indoor conditions in a low-resource tropical setting.
Tamerius, James; Ojeda, Sergio; Uejio, Christopher K; Shaman, Jeffrey; Lopez, Brenda; Sanchez, Nery; Gordon, Aubree
2017-04-01
Influenza transmission occurs throughout the planet across wide-ranging environmental conditions. However, our understanding of the environmental factors mediating transmission is evaluated using outdoor environmental measurements, which may not be representative of the indoor conditions where influenza is transmitted. In this study, we examined the relationship between indoor environment and influenza transmission in a low-resource tropical population. We used a case-based ascertainment design to enroll 34 households with a suspected influenza case and then monitored households for influenza, while recording indoor temperature and humidity data in each household. We show that the indoor environment is not commensurate with outdoor conditions and that the relationship between indoor and outdoor conditions varies significantly across homes. We also show evidence of influenza transmission in extreme indoor environments. Specifically, our data suggests that indoor environments averaged 29 °C, 18 g/kg specific humidity, and 68 % relative humidity across 15 transmission events observed. These indoor settings also exhibited significant temporal variability with temperatures as high as 39 °C and specific and relative humidity increasing to 22 g/kg and 85 %, respectively, during some transmission events. However, we were unable to detect differences in the transmission efficiency by indoor temperature or humidity conditions. Overall, these results indicate that laboratory studies investigating influenza transmission and virus survival should increase the range of environmental conditions that they assess and that observational studies investigating the relationship between environment and influenza activity should use caution using outdoor environmental measurements since they can be imprecise estimates of the conditions that mediate transmission indoors.
The Mechanistic Indicators of Childhood Asthma (MICA) study in Detroit, Michigan introduced a participant-based approach to reduce the resource burden associated with collection of indoor and outdoor residential air sampling data. A subset of participants designated as MICA-Air c...
Development of indoor environmental index: Air quality index and thermal comfort index
NASA Astrophysics Data System (ADS)
Saad, S. M.; Shakaff, A. Y. M.; Saad, A. R. M.; Yusof, A. M.; Andrew, A. M.; Zakaria, A.; Adom, A. H.
2017-03-01
In this paper, index for indoor air quality (also known as IAQI) and thermal comfort index (TCI) have been developed. The IAQI was actually modified from previous outdoor air quality index (AQI) designed by the United States Environmental Protection Agency (US EPA). In order to measure the index, a real-time monitoring system to monitor indoor air quality level was developed. The proposed system consists of three parts: sensor module cloud, base station and service-oriented client. The sensor module cloud (SMC) contains collections of sensor modules that measures the air quality data and transmit the captured data to base station through wireless. Each sensor modules includes an integrated sensor array that can measure indoor air parameters like Carbon Dioxide, Carbon Monoxide, Ozone, Nitrogen Dioxide, Oxygen, Volatile Organic Compound and Particulate Matter. Temperature and humidity were also being measured in order to determine comfort condition in indoor environment. The result from several experiments show that the system is able to measure the air quality presented in IAQI and TCI in many indoor environment settings like air-conditioner, chemical present and cigarette smoke that may impact the air quality. It also shows that the air quality are changing dramatically, thus real-time monitoring system is essential.
DOSE-DEPENDENT ALLERGIC ASTHMA RESPONSES TO PENICILLIUM CHRYSOGENUM
ABSTRACT
Indoor mold has been associated with development of allergic asthma. Penicillium chrysogenum, a common indoor mold, is known to have several allergens and its viable conidia can induce allergic responses in a mouse model of allergic penicilliosis. The hypothesis o...
Early-Onset Basal Cell Carcinoma and Indoor Tanning: A Population-Based Study
Zens, M. Scot; Li, Zhigang; Stukel, Therese A.; Perry, Ann E.; Gilbert-Diamond, Diane; Sayarath, Vicki; Stephenson, Rita S.; Barton, Dorothea; Nelson, Heather H.; Spencer, Steven K.
2014-01-01
OBJECTIVE: Indoor tanning with UV radiation–emitting lamps is common among adolescents and young adults. Rising incidence rates of basal cell carcinoma (BCC) have been reported for the United States and elsewhere, particularly among those diagnosed at younger ages. Recent epidemiologic studies have raised concerns that indoor tanning may be contributing to early occurrence of BCC, and younger people may be especially vulnerable to cancer risk associated with this exposure. Therefore, we sought to address these issues in a population-based case–control study from New Hampshire. METHODS: Data on indoor tanning were obtained on 657 cases of BCC and 452 controls ≤50 years of age. RESULTS: Early-onset BCC was related to indoor tanning, with an adjusted odds ratio (OR) of 1.6 (95% confidence interval, 1.3–2.1). The strongest association was observed for first exposure as an adolescent or young adult, with a 10% increase in the OR with each age younger at first exposure (OR per year of age ≤23 = 1.1; 95% confidence interval, 1.0–1.2). Associations were present for each type of device examined (ie, sunlamps, tanning beds, and tanning booths). CONCLUSIONS: Our findings suggest early exposure to indoor tanning increases the risk of early development of BCC. They also underscore the importance of counseling adolescents and young adults about the risks of indoor tanning and for discouraging parents from consenting minors to this practice. PMID:24958589
Early-onset basal cell carcinoma and indoor tanning: a population-based study.
Karagas, Margaret R; Zens, M Scot; Li, Zhigang; Stukel, Therese A; Perry, Ann E; Gilbert-Diamond, Diane; Sayarath, Vicki; Stephenson, Rita S; Barton, Dorothea; Nelson, Heather H; Spencer, Steven K
2014-07-01
Indoor tanning with UV radiation-emitting lamps is common among adolescents and young adults. Rising incidence rates of basal cell carcinoma (BCC) have been reported for the United States and elsewhere, particularly among those diagnosed at younger ages. Recent epidemiologic studies have raised concerns that indoor tanning may be contributing to early occurrence of BCC, and younger people may be especially vulnerable to cancer risk associated with this exposure. Therefore, we sought to address these issues in a population-based case-control study from New Hampshire. Data on indoor tanning were obtained on 657 cases of BCC and 452 controls ≤50 years of age. Early-onset BCC was related to indoor tanning, with an adjusted odds ratio (OR) of 1.6 (95% confidence interval, 1.3-2.1). The strongest association was observed for first exposure as an adolescent or young adult, with a 10% increase in the OR with each age younger at first exposure (OR per year of age ≤23 = 1.1; 95% confidence interval, 1.0-1.2). Associations were present for each type of device examined (ie, sunlamps, tanning beds, and tanning booths). Our findings suggest early exposure to indoor tanning increases the risk of early development of BCC. They also underscore the importance of counseling adolescents and young adults about the risks of indoor tanning and for discouraging parents from consenting minors to this practice. Copyright © 2014 by the American Academy of Pediatrics.
Fast Fingerprint Database Maintenance for Indoor Positioning Based on UGV SLAM
Tang, Jian; Chen, Yuwei; Chen, Liang; Liu, Jingbin; Hyyppä, Juha; Kukko, Antero; Kaartinen, Harri; Hyyppä, Hannu; Chen, Ruizhi
2015-01-01
Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI) fingerprints of Signals of OPportunity (SOP) is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV) platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz) and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning. PMID:25746096
Estimation of indoor and outdoor ratios of selected volatile organic compounds in Canada
NASA Astrophysics Data System (ADS)
Xu, Jing; Szyszkowicz, Mieczyslaw; Jovic, Branka; Cakmak, Sabit; Austin, Claire C.; Zhu, Jiping
2016-09-01
Indoor air and outdoor air concentration (I/O) ratio can be used to identify the origins of volatile organic compounds (VOCs). I/O ratios of 25 VOCs in Canada were estimated based on the data collected in various areas in Canada between September 2009 and December 2011. The indoor VOC data were extracted from the Canadian Health Measures Survey (CHMS). Outdoor VOC data were obtained from Canada's National Air Pollution Surveillance (NAPS) Network. The sampling locations covered nine areas in six provinces in Canada. Indoor air concentrations were found higher than outdoor air for all studied VOCs, except for carbon tetrachloride. Two different approaches were employed to estimate the I/O ratios; both approaches produced similar I/O values. The I/O ratios obtained from this study were similar to two other Canadian studies where indoor air and outdoor air of individual dwellings were measured. However, the I/O ratios found in Canada were higher than those in European cities and in two large USA cities, possibly due to the fact that the outdoor air concentrations recorded in the Canadian studies were lower. Possible source origins identified for the studied VOCs based on their I/O ratios were similar to those reported by others. In general, chlorinated hydrocarbons, short-chain (C5, C6) n-alkanes and benzene had significant outdoor sources, while long-chain (C10sbnd C12) n-alkanes, terpenes, naphthalene and styrene had significant indoor sources. The remaining VOCs had mixed indoor and outdoor sources.
Laser-Based Slam with Efficient Occupancy Likelihood Map Learning for Dynamic Indoor Scenes
NASA Astrophysics Data System (ADS)
Li, Li; Yao, Jian; Xie, Renping; Tu, Jinge; Feng, Chen
2016-06-01
Location-Based Services (LBS) have attracted growing attention in recent years, especially in indoor environments. The fundamental technique of LBS is the map building for unknown environments, this technique also named as simultaneous localization and mapping (SLAM) in robotic society. In this paper, we propose a novel approach for SLAMin dynamic indoor scenes based on a 2D laser scanner mounted on a mobile Unmanned Ground Vehicle (UGV) with the help of the grid-based occupancy likelihood map. Instead of applying scan matching in two adjacent scans, we propose to match current scan with the occupancy likelihood map learned from all previous scans in multiple scales to avoid the accumulation of matching errors. Due to that the acquisition of the points in a scan is sequential but not simultaneous, there unavoidably exists the scan distortion at different extents. To compensate the scan distortion caused by the motion of the UGV, we propose to integrate a velocity of a laser range finder (LRF) into the scan matching optimization framework. Besides, to reduce the effect of dynamic objects such as walking pedestrians often existed in indoor scenes as much as possible, we propose a new occupancy likelihood map learning strategy by increasing or decreasing the probability of each occupancy grid after each scan matching. Experimental results in several challenged indoor scenes demonstrate that our proposed approach is capable of providing high-precision SLAM results.
Predictors of summertime heat index levels in New York City apartments
Quinn, Ashlinn; Kinney, Patrick; Shaman, Jeffrey
2018-01-01
Background During heat waves, fatal overexposure to heat most often occurs at home. It is not known how factors such as building size, floor level, and different types of air conditioning (AC) contribute to excess indoor heat. Methods We monitored indoor temperature and humidity in 36 apartments in New York City during summers 2014 and 2015, and used these values to calculate the indoor heat index (HI). We investigated the role of AC type and building-level factors on indoor HI using multilevel regression models. Results 34 of 36 homes had AC. Central and ductless AC types were associated with the coolest indoor conditions; homes with window and portable AC were significantly warmer. Apartments on the top floor of a building were significantly hotter during heat advisory periods than other apartments regardless of the presence of AC. High indoor HI levels persisted in some homes for approximately one day following the end of the two heat advisory periods. Conclusions We provide concrete evidence of higher heat levels in top floor apartments and in homes with certain types of AC. High heat levels that persist indoors after outdoor heat has subsided may present an underappreciated public health risk. PMID:28107558
A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals
Castañón–Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo
2015-01-01
The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information. PMID:26633417
A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals.
Castañón-Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo
2015-12-02
The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi-Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.
Forecasting human exposure to atmospheric pollutants in Portugal - A modelling approach
NASA Astrophysics Data System (ADS)
Borrego, C.; Sá, E.; Monteiro, A.; Ferreira, J.; Miranda, A. I.
2009-12-01
Air pollution has become one main environmental concern because of its known impact on human health. Aiming to inform the population about the air they are breathing, several air quality modelling systems have been developed and tested allowing the assessment and forecast of air pollution ambient levels in many countries. However, every day, an individual is exposed to different concentrations of atmospheric pollutants as he/she moves from and to different outdoor and indoor places (the so-called microenvironments). Therefore, a more efficient way to prevent the population from the health risks caused by air pollution should be based on exposure rather than air concentrations estimations. The objective of the present study is to develop a methodology to forecast the human exposure of the Portuguese population based on the air quality forecasting system available and validated for Portugal since 2005. Besides that, a long-term evaluation of human exposure estimates aims to be obtained using one-year of this forecasting system application. Additionally, a hypothetical 50% emission reduction scenario has been designed and studied as a contribution to study emission reduction strategies impact on human exposure. To estimate the population exposure the forecasting results of the air quality modelling system MM5-CHIMERE have been combined with the population spatial distribution over Portugal and their time-activity patterns, i.e. the fraction of the day time spent in specific indoor and outdoor places. The population characterization concerning age, work, type of occupation and related time spent was obtained from national census and available enquiries performed by the National Institute of Statistics. A daily exposure estimation module has been developed gathering all these data and considering empirical indoor/outdoor relations from literature to calculate the indoor concentrations in each one of the microenvironments considered, namely home, office/school, and other indoors (leisure activities like shopping areas, gym, theatre/cinema and restaurants). The results show how this developed modelling system can be useful to anticipate air pollution episodes and to estimate their effects on human health on a long-term basis. The two metropolitan areas of Porto and Lisbon are identified as the most critical ones in terms of air pollution effects on human health over Portugal in a long-term as well as in a short-term perspective. The coexistence of high concentration values and high population density is the key factor for these stressed areas. Regarding the 50% emission reduction scenario, the model results are significantly different for both pollutants: there is a small overall reduction in the individual exposure values of PM 10 (<10 μg m -3 h), but for O 3, in contrast, there is an extended area where exposure values increase with emission reduction. This detailed knowledge is a prerequisite for the development of effective policies to reduce the foreseen adverse impact of air pollution on human health and to act on time.
Indoor Map Aided Wi-Fi Integrated Lbs on Smartphone Platforms
NASA Astrophysics Data System (ADS)
Yu, C.; El-Sheimy, N.
2017-09-01
In this research, an indoor map aided INS/Wi-Fi integrated location based services (LBS) applications is proposed and implemented on smartphone platforms. Indoor map information together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value from Wi-Fi are collected to obtain an accurate, continuous, and low-cost position solution. The main challenge of this research is to make effective use of various measurements that complement each other without increasing the computational burden of the system. The integrated system in this paper includes three modules: INS, Wi-Fi (if signal available) and indoor maps. A cascade structure Particle/Kalman filter framework is applied to combine the different modules. Firstly, INS position and Wi-Fi fingerprint position integrated through Kalman filter for estimating positioning information. Then, indoor map information is applied to correct the error of INS/Wi-Fi estimated position through particle filter. Indoor tests show that the proposed method can effectively reduce the accumulation positioning errors of stand-alone INS systems, and provide stable, continuous and reliable indoor location service.
Indoor-Outdoor Detection Using a Smart Phone Sensor.
Wang, Weiping; Chang, Qiang; Li, Qun; Shi, Zesen; Chen, Wei
2016-09-22
In the era of mobile internet, Location Based Services (LBS) have developed dramatically. Seamless Indoor and Outdoor Navigation and Localization (SNAL) has attracted a lot of attention. No single positioning technology was capable of meeting the various positioning requirements in different environments. Selecting different positioning techniques for different environments is an alternative method. Detecting the users' current environment is crucial for this technique. In this paper, we proposed to detect the indoor/outdoor environment automatically without high energy consumption. The basic idea was simple: we applied a machine learning algorithm to classify the neighboring Global System for Mobile (GSM) communication cellular base station's signal strength in different environments, and identified the users' current context by signal pattern recognition. We tested the algorithm in four different environments. The results showed that the proposed algorithm was capable of identifying open outdoors, semi-outdoors, light indoors and deep indoors environments with 100% accuracy using the signal strength of four nearby GSM stations. The required hardware and signal are widely available in our daily lives, implying its high compatibility and availability.
Is the perception of clean, humid air indeed affected by cooling the respiratory tract?
NASA Astrophysics Data System (ADS)
Burek, Rudolf; Polednik, Bernard; Guz, Łukasz
2017-07-01
The study aims at determining exposure-response relationships after short exposure to clean air and long exposure to air polluted by people. The impact of water vapor content in the indoor air on its acceptability (ACC) was assessed by the occupants after a short exposure to clean air and an hour-long exposure to increasingly polluted air. The study presents a critical analysis pertaining to the stimulation of olfactory sensations by the air enthalpy suggested in previous models and proposes a new model based on the Weber-Fechner law. Our assumption was that water vapor is the stimulus of olfactory sensations. The model was calibrated and verified in field conditions, in a mechanically ventilated and air conditioned auditorium. Measurements of the air temperature, relative humidity, velocity and CO2 content were carried out; the acceptability of air quality was assessed by 162 untrained students. The subjective assessments and the measurements of the environmental qualities allowed for determining the Weber coefficients and the threshold concentrations of water vapor, as well as for establishing the limitations of the model at short and long exposure to polluted indoor air. The results are in agreement with previous studies. The standard error equals 0.07 for immediate assessments and 0.17 for assessments after adaptation. Based on the model one can predict the ACC assessments of trained and untrained participants.
An Indoor Monitoring System for Ambient Assisted Living Based on Internet of Things Architecture
Marques, Gonçalo; Pitarma, Rui
2016-01-01
The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the aging of the world population. The AAL technologies are designed to meet the needs of the aging population in order to maintain their independence as long as possible. As people typically spend more than 90% of their time in indoor environments, indoor air quality (iAQ) is perceived as an imperative variable to be controlled for the inhabitants’ wellbeing and comfort. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. The continuous technological advancements make it possible to build smart objects with great capabilities for sensing and connecting several possible advancements in ambient assisted living systems architectures. Indoor environments are characterized by several pollutant sources. Most of the monitoring frameworks instantly accessible are exceptionally costly and only permit the gathering of arbitrary examples. iAQ is an indoor air quality system based on an Internet of Things paradigm that incorporates in its construction Arduino, ESP8266, and XBee technologies for processing and data transmission and micro sensors for data acquisition. It also allows access to data collected through web access and through a mobile application in real time, and this data can be accessed by doctors in order to support medical diagnostics. Five smaller scale sensors of natural parameters (air temperature, moistness, carbon monoxide, carbon dioxide, and glow) were utilized. Different sensors can be included to check for particular contamination. The results reveal that the system can give a viable indoor air quality appraisal in order to anticipate technical interventions for improving indoor air quality. Indeed indoor air quality might be distinctively contrasted with what is normal for a quality living environment. PMID:27869682
An Indoor Monitoring System for Ambient Assisted Living Based on Internet of Things Architecture.
Marques, Gonçalo; Pitarma, Rui
2016-11-17
The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the aging of the world population. The AAL technologies are designed to meet the needs of the aging population in order to maintain their independence as long as possible. As people typically spend more than 90% of their time in indoor environments, indoor air quality (iAQ) is perceived as an imperative variable to be controlled for the inhabitants' wellbeing and comfort. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. The continuous technological advancements make it possible to build smart objects with great capabilities for sensing and connecting several possible advancements in ambient assisted living systems architectures. Indoor environments are characterized by several pollutant sources. Most of the monitoring frameworks instantly accessible are exceptionally costly and only permit the gathering of arbitrary examples. iAQ is an indoor air quality system based on an Internet of Things paradigm that incorporates in its construction Arduino, ESP8266, and XBee technologies for processing and data transmission and micro sensors for data acquisition. It also allows access to data collected through web access and through a mobile application in real time, and this data can be accessed by doctors in order to support medical diagnostics. Five smaller scale sensors of natural parameters (air temperature, moistness, carbon monoxide, carbon dioxide, and glow) were utilized. Different sensors can be included to check for particular contamination. The results reveal that the system can give a viable indoor air quality appraisal in order to anticipate technical interventions for improving indoor air quality. Indeed indoor air quality might be distinctively contrasted with what is normal for a quality living environment.