Specific Indoor Environment Research Articles

Robust LOS/NLOS Identification for UWB Signals Using Improved Fuzzy Decision Tree Under Volatile Indoor Conditions

Ultra-wideband (UWB) is a very promising indoor wireless positioning technology. However, in the harsh and volatile indoor environment, the propagation of UWB signals is vulnerable to non-line-of-sight (NLOS) conditions, and the contaminated range measurements will degrade the accuracy for UWB localization. Therefore, it is necessary to identify LOS/NLOS. Recent studies mainly focus on the identification of UWB signal propagation conditions by using channel impulse response (CIR) or extracted channel statistical features. However, these studies usually only focus on specific indoor environment or stable indoor conditions. In fact, the indoor environment is harsh and changeable. In order to deal with the dynamic and uncertain information of the indoor environments, this paper proposes a robust method to identify LOS/NLOS using fuzzy decision tree (FDT) based on Bayesian optimization. The proposed method first extracts the classification features from the CIRs, and then fuzzifies the features. Finally, it combines Bayesian optimization to construct the FDT, so as to identify the propagation conditions of UWB signals. The experimental results show that the identification accuracy of the proposed method is higher than 90 % in both static and dynamic experiments, and the overall performance is excellent. Compared with other methods, it has certain advantages and robustness.

SICK BUILDING SYNDROME: HOW IS IT AFFECTED BY AIRBORNE POLLEN, INDOOR AND OUTDOOR POLLUTANTS?

<h3>Introduction</h3> The Sick Building Syndrome (SBS) is defined as symptoms experienced by occupants of specific indoor environments. Other factors may influence this syndrome such as indoor and outdoor pollutants. The aim of the study was to determine the association of the clinical manifestations of the SBS with pollen, indoor and outdoor pollutants in the home environment. <h3>Methods</h3> It was an observational, transversal and descriptive study that was performed from November 2021 to April 2022. It included subjects >18 years old who completed an online survey regarding SBS (general symptoms, nasal, eye, oropharyngeal and skin symptoms) presented at home, housing information and personal history. Pollen Sense SensorÒ was used for airborne pollen data and the local pollution monitoring system for pollutant information. Ethics committee approval: AL21-00015. SPSS version 24 was used for statistical analysis. <h3>Results</h3> A total of 402 surveys were included; 91% of subjects reported having at least 1 symptom, fatigue (74.6%) was the most frequent. Humidity at home was associated to nasal, eye and cutaneous symptoms (p<0.001). Presence of cats was associated to nasal and eye symptoms (p=0.028). Smoking (p=0.045), allergy history (p<0.001) and living in an apartment (p=0.006) were related to nasal symptoms. Headache was associated with exposure to high levels of <i>Fraxinus</i> pollen (p=0.019). Nitrogen oxides (NOx) presented a p=0.05 with eye and nasal symptoms. PM10 were related to cutaneous symptoms and itchy scalp at levels of 67.5 µg/m3. <h3>Conclusion</h3> SBS was associated with airborne pollen, indoor and outdoor pollutants. Humidity represents a risk factor for the development of SBS symptoms.

Polychlorinated Biphenyls (PCBs) in the Environment: Occupational and Exposure Events, Effects on Human Health and Fertility.

In the last decade or so, polychlorinated biphenyls (PCBs) garnered renewed attention in the scientific community due to new evidence pointing at their continued presence in the environment and workplaces and the potential human risks related to their presence. PCBs move from the environment to humans through different routes; the dominant pathway is the ingestion of contaminated foods (fish, seafood and dairy products), followed by inhalation (both indoor and outdoor air), and, to a lesser extent, dust ingestion and dermal contact. Numerous studies reported the environmental and occupational exposure to these pollutants, deriving from building materials (flame-retardants, plasticizers, paints, caulking compounds, sealants, fluorescent light ballasts, etc.) and electrical equipment. The highest PCBs contaminations were detected in e-waste recycling sites, suggesting the need for the implementation of remediation strategies of such polluted areas to safeguard the health of workers and local populations. Furthermore, a significant correlation between PCB exposure and increased blood PCB concentrations was observed in people working in PCB-contaminated workplaces. Several epidemiological studies suggest that environmental and occupational exposure to high concentrations of PCBs is associated with different health outcomes, such as neuropsychological and neurobehavioral deficits, dementia, immune system dysfunctions, cardiovascular diseases and cancer. In addition, recent studies indicate that PCBs bioaccumulation can reduce fertility, with harmful effects on the reproductive system that can be passed to offspring. In the near future, further studies are needed to assess the real effects of PCBs exposure at low concentrations for prolonged exposure in workplaces and specific indoor environments.

Application of A Priori Map in Dynamic Background Removal for Indoor Human Perception Using a Thermopile Array

Human perception is of great research and application value. Thermopile infrared array sensor (TPAS) is an available solution without privacy invasion. In specific indoor environment like apartment and office, there are inevitable interfering thermal sources except human. Extracting human from the dynamically changing background i.e. background removal is a critical process. Based on the hardware platform built by a thermopile infrared array sensor MLX90640 with an output of 24×32 pixels, this paper proposes an adaptive Gaussian background removal algorithm applying a priori map (AGBR-PM) for indoor single human perception. For each static thermal source, an a priori map is established containing its location and thermal radiation feature in the way of support degree matrix. We build a Gaussian background model consisting of mean and standard deviation matrix. Each frame of thermal image is segmented into foreground and background based on 2σ rule. A state and cross detection algorithm is proposed to compensate the error caused by interfering static thermal sources, and an erosion-connected component analysis and foreground complement algorithm is adopted to reduce the random noise as well. A regional update strategy is designed to adapt to the emergence of random thermal sources in background. The experimental results have shown that AGBR-PM has an excellent adaptability to dynamically changing environment, and can remove the background correctly.

Another Look at Privacy-Preserving Automated Contact Tracing

In the current COVID-19 pandemic, manual contact tracing has been proven to be very helpful to reach close contacts of infected users and slow down spread of the virus. To improve its scalability, a number of automated contact tracing (ACT) solutions have been proposed, and some of them have been deployed. Despite the dedicated efforts, security and privacy issues of these solutions are still open and under intensive debate. In this article, we examine the ACT concept from a broader perspective, by focusing on not only security and privacy issues but also functional issues such as interface, usability, and coverage. We first elaborate on these issues and particularly point out the inevitable privacy leakages in existing Bluetooth Low Energy based ACT solutions, including centralized and decentralized ones. In addition, we examine the existing venue-based ACT solutions and identify their privacy and security concerns. Then, we propose a generic venue-based ACT solution and a concrete instantiation based on Bluetooth Low Energy technology. Our solution monitors users’ contacting history only in virus-spreading-prone venues and offers higher-level protection for both security and privacy than its predecessors. Finally, we evaluate our solution from security, privacy, and efficiency perspectives, and also highlight how to reduce false positives in some specific indoor environments.

Optimal moisture buffering thickness of the hygroscopic material layer: Modeling and derivation

The indoor humidity level can be passively improved by the hygroscopic material without energy consumption. Some studies demonstrate that the moisture buffering capacity (MBC) of the hygroscopic material layer is affected by the material's thickness. There exists an optimal thickness that maximizes the material's moisture buffering capacity when some hygroscopic material is exposed in a specific indoor environment. Some methods have been proposed to determine this optimal moisture buffering thickness (Lopt). However, such methods are primarily based on experimental measurements or numerical simulation. Therefore, optimal moisture buffering thicknesses are approximate values. In this paper, an analytical method was proposed to solve the theoretical Lopt based on the moisture transfer function. Correspondingly, the ideal and practical optimal thickness, which present an ideal situation and a practical situation of the indoor humidity variation, respectively, were theoretically derived and validated using numerical simulations. Moreover, the optimal moisture buffering thicknesses of some conventional building wall hygroscopic materials were derived and calculated simply and efficiently via the proposed analytical method. The proposed analytical method is based on the theoretical derivation and has many advantages in terms of computational efficiency and accuracy compared with experimental measurements and numerical simulations.

International Real Estate Review

Our paper aims to examine the healthy building adoption patterns by first asking two critical questions that are relevant to the market conditions: What are healthy buildings? What is their financial value for tenants and owners? We then synthesize the existing academic and industry literature. We find some early evidence of a real estate price premium for specific indoor environment quality (IEQ) and design features. In terms of health-focused building certification systems (BCSs), no empirical and quantitative research has been done on the financial performance of healthy buildings, except for theoretical models. We then proceed to conduct interviews with executives of 15 real estate corporations across the globe to understand the perspectives of real estate owner operators and their strategies for this emerging market. The interviews results confirm that the scarcity of empirical evidence that links healthy building attributes to financial returns inhibits the adoption of healthy buildings in mainstream designs. Moreover, differences in the adoption patterns of healthy buildings are due to the building ownership structure at the firm level, tenants, end-users and building conditions. The strategies of firms in pursuing a healthy building range from risk mitigation to proactive pursuit of new growth opportunities. Private equity funds and real estate investment trust (REIT) firms tend to focus on risk mitigation, while direct real estate investment firms are more likely to carry out the latter to position themselves as a leader within the real estate industry.

An adaptive predicted percentage dissatisfied model based on the air-conditioner turning-on behaviors in the residential buildings of China

To ease the Predicted Percentage of Dissatisfied (PPD) measurement and calculation and consider the adaptive behaviors of residents, the present research proposed an adaptive thermal discomfort evaluation model: Air-conditioner based Adaptive Predicted Percentage of Dissatisfied (aaPPD). First, the indoor temperature, outdoor temperature, and humidity data of the residential buildings in five cities within three climate regions in China were collected. Second, through the air-conditioner-turning-on (ATO) judgment algorithm, the data from when the air conditioner was turned on could be extracted from the original data, and then transformed via the Monte Carlo sampling method to obtain a dataset of the ATO percentage of residents within specific indoor and outdoor environments. Finally, a nonlinear model was built according to this dataset. The final R2 of this model was 0.833. This model utilized data from resident ATO behaviors as the basis for determining the thermal discomfort and avoiding the psychological impact on the subjects when filling out the thermal sensation vote questionnaire. Moreover, when compared with the PPD model, the aaPPD model simplified the variables to obtain the calculation parameters more conveniently and ease the thermal discomfort testing and predictions, which could allow for better adaptation to the early architectural design stage working characteristics.

Market Adoption of Healthy Buildings in the Office Sector: A Global Study from the Owner’s Perspective

The emergence of human health and well-being concerns provide market differentiation opportunities for real estate companies globally. Our paper examines the market adoption of healthy office buildings by looking into how a healthy office building is defined and measured in the marketplace. What is its financial value for tenants and owners? What are real estate owner's perspectives and strategies for this emerging market? We synthesized the existing body of academic and industry literature, and conducted interviews with executives from 15 real estate corporations that own office buildings across the globe. The results from literature review indicate that there is some early evidence of a real estate price premium for specific indoor environment quality (IEQ) features. At the level of health-focused building certification systems (BCS), there is no empirical and quantitative research on healthy building’s financial performance, except theoretical return on investment (ROI) models. The results from owners’ interviews confirm that the scarcity of empirical evidence linking healthy building attributes to financial returns presents the mainstream adoption barrier for building owners. Owners are adopting diverse healthy building attributes that are driven by end-user’s health and wellbeing demand regardless if they are adopting health-focused BCSs. Their strategies for pursuing the healthy building market range from risk mitigation to proactive pursuit of new growth opportunities. Private equity funds and real estate investment trusts (REITs) firms tend to focus on the former, while direct real estate investment firms are more likely adopt proactive strategies to lead the adoption curve.

Deep Learning Object Detector Using a Combination of Convolutional Neural Network (CNN) Architecture (MiniVGGNet) and Classic Object Detection Algorithm

The object detection system is a computer technology related to image processing and computer vision that detects instances of semantic objects of a certain class in digital images and videos. The system consists of two main processes, which are classification and detection. Once an object instance has been classified and detected, it is possible to obtain further information, including recognizes the specific instance, track the object over an image sequence and extract further information about the object and the scene. This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. For object detection, sliding windows and image pyramids were used to localize and detect objects at different locations, and non-maxima suppression (NMS) was used to obtain the final bounding box to localize the object location. Based on the experiment result, the percentage of classification accuracy of the network is 80% to 90% and the time for the system to detect the object is less than 15sec/frame. Experimental results show that there are reasonable and efficient to combine classic object detection method with a deep learning classification approach. The performance of this method can work in some specific use cases and effectively solving the problem of the inaccurate classification and detection of typical features.

Investigation on air quality of specific indoor environments\u2014spa salons located in Gdynia, Poland

Due to excessive application of essential oils and scented products in spa salons during aromatherapy and massage sessions, the elevated concentration of total volatile organic compounds (TVOCs), particularly terpenes, which are known as secondary organic aerosol (SOA) precursors, is expected there. This study was aimed at determination of VOCs with a particular regard to terpenes in air samples collected in selected spa salons located in Northern Poland. Active air sampling was conducted before and after treatments. Samples were analyzed with the use of thermal desorption gas chromatography coupled with flame-ionization detector (TD-GC-FID) and mass spectrometer (TD-GC-MS). Obtained results allowed to characterize chemical composition of indoor air of spa salons and also to relate the dependence between applied essential oil and indoor air chemical composition. It has been proved that (i) spa salons are characterized by TVOC concentrations exceeding recommended values of 300–400 μg m−3 in most of examined cases, reaching up to several thousand of micrograms per cubic meter, (ii) TVOC concentration is strictly related to salon characteristics and carried out treatments, (iii) terpenes constitute a significant part of TVOCs present in spa indoor air, from 22 up to 86%, (iv) most commonly investigated terpenes in the literature (d-limonene, α-pinene, camphene, and linalool) were also determined at the highest concentration levels in this study and (v) VOC chemical composition is strictly dependent on the type of applied essential oils. On the basis of obtained results, it may be stated that extensive application of essential oils rich in terpenes can significantly alter indoor air chemistry of spa salons, thereby influencing health and well-being of employees working there.Graphical abstract

Candida auris, an Agent of Hospital-Associated Outbreaks: Which Challenging Issues Do We Need to Have in Mind?

The emergence of Candida auris is considered as one of the most serious problems associated with nosocomial transmission and with infection control practices in hospital environment. This multidrug resistant species is rapidly spreading worldwide, with several described outbreaks. Until now, this species has been isolated from different hospital surfaces, where it can survive for long periods. There are multiple unanswered questions regarding C. auris, such as prevalence in population, environmental contamination, effectiveness of infection prevention and control, and impact on patient mortality. In order to understand how it spreads and discover possible reservoirs, it is essential to know the ecology, natural environment, and distribution of this species. It is also important to explore possible reasons to this recent emergence, namely the environmental presence of azoles or the possible effect of climate change on this sudden emergence. This review aims to discuss some of the most challenging issues that we need to have in mind in the management of C. auris and to raise the awareness to its presence in specific indoor environments as hospital settings.

Bringing It Indoors: A Review of Narrowband Radio Propagation Modeling for Enclosed Spaces

Small cells are now widely deployed indoors to address hot-spot areas where capacity uplift is needed. This deployment leads to the increase of wireless networks as a challenge to service demands of personal communication systems, which has inspired the scientific community to work towards understanding and predicting in-building radio wave propagation performance. Despite this, only a few reviews have attempted to overview channel modeling for specific indoor environments and even fewer outline remarks that include a methodology for designing and planning indoor radio systems. Consequently, a comprehensive survey of indoor narrowband channel models is presented, spanning more than 30 years of continuous research to overview and contrast significant developments including their disadvantages, and proposing a new taxonomy to analyze them. Finally, remarks on indoor radio propagation modeling with a vision for future research opportunities are presented.

Aspergillus collected in specific indoor settings: their molecular identification and susceptibility pattern

ABSTRACT Exposure to Aspergillus conidia is an increased risk factor for the development of respiratory symptoms. The emergence of azole resistance in Aspergillus fumigatus is a major concern for the scientific community. The aim of this study was to perform the molecular identification of Aspergillus species collected from different occupational and non-occupational indoor settings and to study the azole susceptibility profile of the collected Fumigati isolates. The selected Aspergillus isolates were identified as belonging to the sections Fumigati, Nigri Versicolores, Terrei, Clavati and Nidulantes. All the Aspergillus fumigatus were screened for azole resistance using an agar media supplemented with itraconazole, voriconazole and posaconazole. None of the tested isolates showed resistance to those azoles. Knowledge of Aspergillus epidemiology in specific indoor environments allows a better risk characterization regarding Aspergillus burden. This study allowed the analysis of the molecular epidemiology and the determination of the susceptibility pattern of Aspergillus section Fumigati found in the studied indoor settings.

Does the presence of certain bacterial family in the microbiome indicate specific indoor environment characteristics? A factorial design approach for identifying bio-fingerprints

The study applies the current knowledge on microbiome in built environments towards identifying microbes, specifically bacteria as bio-fingerprints which can reflect indoor space and occupant characteristics. Data were collected from the literature on the bacterial family and the indoor environment. The factorial design approach was applied to quantify and compare the influence of selected indoor environmental parameters, sampling region (air or surface), sampling locations (residence or non-residence), gender and age and their interactions on the types and concentration of detected bacterial families. Factorial design analysis identified and confirmed Corynebacteriaceae and Lactobacillaceae as the gender signature for males and females, respectively. The significant bacterial families across all scenarios are: Corynebacteriaceae, Propionibacteriaceae, Bacillaceae, Staphylococcaceae, Lactobacillaceae, Methylobacteriaceae, Moraxellaceae, Micrococcaceae, Enterobacteriaceae, Rhodobacteraceae, Streptococcaceae and Pseudomonadaceae. Higher concentrations of Propionibacteriaceae indicate that the specific location is an adult-occupied space. Staphylococcaceae presence is the bio-fingerprint of contaminated air of hospitals bio-fingerprint and Moraxellaceae on hospital surfaces are distinct characteristics. Streptococcaceae is a bio-fingerprint of contaminated air of schools and other children-occupied spaces. Enterobacteriaceae is a bio-fingerprint of contaminated air of non-residence locations. Bacillaceae does not indicate any indoor characteristics.

Evaluation Model of Specific Indoor Environment Overall Comfort Based on Effective-Function Method

The indoor overall environmental comfort of part limited spaces is studied in this paper. The operative temperature, illumination, and noise intensity are used as objective parameters in order to evaluate the thermal, luminous, and acoustic environment. The thermal, luminous, and acoustic environment are investigated by using the subjective questionnaire in this experiment, and the function relation of the single physical parameter is established. Then, using the effective-function comprehensive evaluation carries on non-dimensional, weighting, and penalty substitution synthesis for the evaluation index of thermal, luminous, and acoustic environment, and establishes the evaluation model of the indoor overall environment. According to the experimental results and evaluation analysis, it is considered that the noise intensity and operative temperature have great influence on the indoor environment overall comfort and the illumination has less effect. Referring to the ISO7730 standard and combining it with the situation of our country, the indoor overall environment is divided into the zone of comfort. The predicted overall comfort vote (POCV), which is greater than or equal to −0.5 is the high comfort zone I. The area of −0.5 &gt; POCV ≥ −1.0 is designated as low comfort zone II. It provides a certain basis for the evaluation of indoor overall environmental comfort.

Evaluation of Two WiFi Positioning Systems Based on Autonomous Crowdsourcing of Handheld Devices for Indoor Navigation

Current WiFi positioning systems (WPSs) require databases – such as locations of WiFi access points and propagation parameters, or a radio map – to assist with positioning. Typically, procedures for building such databases are time-consuming and labour-intensive. In this paper, two autonomous crowdsourcing systems are proposed to build the databases on handheld devices by using our designed algorithms and an inertial navigation solution from a Trusted Portable Navigator (T-PN). The proposed systems, running on smartphones, build and update the database autonomously and adaptively to account for the dynamic environment. To evaluate the performance of automatically generated databases, two improved WiFi positioning schemes (fingerprinting and trilateration) corresponding to these two database building systems, are also discussed. The main contribution of the paper is the proposal of two crowdsourcing-based WPSs that eliminate the various limitations of current crowdsourcing-based systems which (a) require a floor plan or GPS, (b) are suitable only for specific indoor environments, and (c) implement a simple MEMS-based sensors’ solution. In addition, these two WPSs are evaluated and compared through field tests. Results in different test scenarios show that average positioning errors of both proposed systems are all less than 5.75 m.

Calculation and Simulation of Electromagnetic Wave Propagation Path Loss Based on Matlab

Abstract In order to reliable data transmission of wireless sensor network (WSN) in indoor environment, the indoor field intensity distribution and transmission characteristics of electromagnetic wave were researched. First of all, the 3D model in specific indoor environment was built by the finite difference time domain method (FDTD).Then, layout of room, different furniture, position of field source and field source frequency had an influence on indoor field intensity distribution that were studied, and the field intensity distribution was simulated by MATALAB. According to simulation of three dimensional field intensity distribution, and it had directly shown that various factors had an influence on the indoor field intensity distribution, thus indoor wireless sensor network nodes can be reasonable deployed by it, the packet loss rate of WSN transmission was reduced from information source, and it provided theoretical basis for further improving WSN information transmission reliability.

Coverage Aspects of Indoor VLC Networks

Achieving both illumination and data reception with probability almost one inside a specific indoor environment is not an effortless task in visible light communication (VLC) networks. Several factors such as error probability, transmitted power, dimming factor, or node failure affect coverage probability to a large extent. To assure reliable signal reception, a dense transmitting network is required on the ceiling. In this paper, we investigate how the key factors contribute to a network deployment with a reliable degree of coverage at a specific horizontal plane. Considering that VLC is set to be one of the most challenging technologies for domestic applications in 5G networks, the analysis on coverage issues discussed herein is of particular interest in practical scenarios.

노인주거 대안으로서의 친환경 공동주택 디자인 가이드라인 제시

This study aims to suggest `an eco-friendly residential housing design guideline as an elderly housing alternative` by mixing the concept of a `sensor citizen community` housing environment with the concept of an `eco-friendly` housing environment, based on the directivity of an elderly housing alternative for surviving in a super-aged society and the directivity of a sustainable housing environment of providing against global warming. Basically, this study considered the directivity of `an eco-friendly residential building as an elderly housing alternative` by analyzing housing environment elements and elements to be considered in an elderly housing environment and setting the directivity of an elderly housing environment, which reflects the change in the design paradigm. In relation to the concept of universal design, for considering the perspective of elderly users, existing elements were compared and major planning elements were applied to the scope of complex planning, communal space and housing unit space. In relation to the concept of eco-friendly design, also, a guideline was re-organized and planning elements were applied to each category by comparing domestic and foreign green building certification system. Based on domestic and foreign authorized guidelines of universal design and green building certification system, this study was focused on suggesting an eco-friendly residential housing design guideline as an elderly housing alternative to make users perceive the need for a specific indoor environment design guideline and system.