我国风机盘管技术现状分析

介绍了近年来我国在风机盘管技术领域的最新成果，在结构形式、强化传热、提高室内空气品质、降低噪音和提高自动控制水平等方面的技术进展情况，分析了目前风机盘管中存在的问题，并对今后的发展方向进行了展望。     

Indoor Air Quality: Exploring Policy Options to Reduce Human Exposures

Deciding between the different policy approaches available for reducing human exposures to indoor pollutants is an exceptionally complex task. These options can range from waiting until more definitive information is available to enacting regulatory standards, with many variations in between. This paper presents some of the factors policy-makers must consider in establishing indoor air quality policies, and the role researchers should play in ensuring that indoor air policies are based on the best available scientific information.     

Comparison of Displacement and Mixing Diffusers

In order to cumpare the peformance of different supply diffuers of ventilation air, the airflow passern, temperature stratifiation and contaminant dispersion in a furnitured office ventilated by three kinds of air diffuer were numerically investigated. The air diffuers studied in this paper are a quarter-cylinder displacement diffuer on the floor and mixing diffuers (linear and vortex diffuers) on the ceiling. The heat sources in the of-fice are considered to be 50% convective and 50% radiative. The k-? two-equatwn model of turbulence is employed to predict the turbulent diffusion. The results show that the displacement diffuser provides a rather uniform flow field with low velocify in most areas, and the vertical temperature difference from floor to ceiling is as high as 6 K. With the linear diffuser, the air velociry is high, and the temperature is uniform both horizontally and vertically. The air velocity generated by the vortex diffuser is moderate. The distributions of the temperature and the contaminant are rather uniform.     

Air Filtration and Radon Decay Product Mitigation

Air cleaning as a means of mitigating the risks arising from exposure to indoor radon progeny has been evaluated in a single-family house in the north eastem US. using an automated, semi-continuous activity-weighted size distribution measurement system. The measurements included radon concentration, condensation nuclei count, and activity-weighted size distribution of radon decay products. Measurements were made in the house with and without an operating air filtration system and with various particle sources common to normal indoor activities operating. Aerosols were generated by running water in a shower, candle burning, cigarette smoking, vacuuming, opening doors, and cooking. Using a room model, the changes in attachment rates, average attachment diameters, and deposition rates of the unattached fraction with and without the air cleaning system were calculated. In the presence of active aerosol sources, the air filtration unit typically reduced the concentration of particles within the hour following the end of particle generation. After candle burning, cigarette smoking, and vacuuming in the bedroom, the reductions of PAEC by air filtration are about 60% with the air filtration system operating in the bedroom. During cooking in the kitchen, the reductions of PAEC in the bedroom with the air filtration system were about 40%. However, for all cases the dose reductions were smaller than the particle and PAEC reductions. For those particles that were generated within the bedroom, there was a 20% to 50% reduction in dose. In the case of cooking where the door was open and particles infiltrated from the rest of the house, the dose reduction was only 5% on average and appears to be insignificant. Thus, the dose reductions were h e r than the reductions in activity concentration, but there were no cases where the estimated dose actually increased.     

Geological controls to the indoor radon distribution in southern Belgium

Soils and rocks are the predominant source of indoor radon (Rn) in southern Belgium. We have studied the correlations between geological features and indoor Rn concentrations using an indoor Rn data set of approx. 1700 short-term measurements. The sediments in the study region are divided into 11 geological series or 43 stages and 16 rock types. The results show a striking relation between indoor Rn concentration and the geological factors.     

The Danish Twin Apartment Study – Part II: Mathematical modeling of the relative strength of sources of indoor air pollution

Abstract This study deals with the modeling of air pollution in apartments from laboratory measurements of source strengths, using formaldehyde and Total Volatile Organic Compounds (TVOCs) as model pollutants. The sources in two test apartments were grouped into two: building-related sources and occupant-related sources. The measured source strengths and ventilation rates were used for the prediction of concentrations expected in the apartments. These predictions were compared to measurements in the apartment over 12 months. The conclusions were that the model predictions based on emission rates measured in the laboratory can be used to predict the long-term concentration of the two model pollutants in the apartments. Considering the measured differences in ventilation between the apartments, an occupant emission rate of between 0.2 and 0.3 mg/h/kg body weight could be estimated. Based on previous suggested limits of acceptable exposures of humans to VOCs, an acceptable average emission rate of VOCs from building materials in general was estimated to be about 30 (μ/m²/h. The modeling showed that during the first 200 days, building materials dominated the emissions. After this, sources relating to the occupants dominated. On average about half of the VOC pollution originated from the building materials.     

I3WSN: Industrial Intelligent Wireless Sensor Networks for indoor environments

Sensor Web Enablement (SWE) technologies have been successfully applied to a great variety of outdoor scenarios but, in practical terms, little effort has been applied for indoor environments, and even less in the field of industrial applications. This article presents an intelligent SWE application for an indoor and industrial scenario, with the aim of improving and increasing the levels of human safety. The base low-level architecture is built on top of wireless sensor networks (WSN) connected to a Sensor Observation Service (SOS). Higher layers in the architecture include services that make real time decisions based on the collected data. Both simulation and experimental results are presented. The paper shows the viability of our approach in terms of performance, scalability, modularity and safety.     

室内概率阈值反向最近邻查询

室内空间变得越发的庞大和复杂,随之产生了越来越多的室内空间查询需求.目前已有文献提出了针对室内空间环境的范围查询和最近邻查询,而作为常见的空间查询类型的反向最近邻查询,尚未有相关的研究.为此,提出了室内概率阈值反向最近邻查询和基于定位设备的设备可达图模型.在图模型基础上,提出了室内概率阈值反向最近邻查询处理算法,该算法由基于图模型的批量剪枝、基于室内距离的剪枝、基于概率的剪枝和概率计算4部分构成,通过剪枝策略修剪掉不可能出现在结果集中的对象,从而缩小了查询空间,提高了效率.     

An indoor localization system in a multiblock workspace

As service robots and other ubiquitous technology have evolved, an increasing need for the autonomous navigation of mobile objects has arisen. In a large number of localization schemes, the absolute-position estimation method, which relies on navigation beacons or landmarks, has been widely used as it has the advantages of being economical and accurate. However, only a few of these schemes have expanded their application to complicated workspaces, or those that have many rooms or blocks. As the navigation of mobile objects in complicated workspaces is vital for ubiquitous technology, multiblock navigation is necessary. This article presents methodologies and techniques for the multiblock navigation of the indoor localization system with active beacon sensors. This new indoor localization system design includes ultrasonic attenuation compensation, dilution-of-precision analysis, and a fault detection and isolation algorithm using redundant measurements. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Passive infrared sensor dataset and deep learning models for device-free indoor localization and tracking

Location estimation or localization is one of the key components in IoT applications such as remote health monitoring and smart homes. Amongst device-free localization technologies, passive infrared (PIR) sensors are one of the promising options due to their low cost, low energy consumption, and good accuracy. However, most of the existing systems are complexly designed and difficult to deploy in real life, in addition, there is no public dataset available for researchers to benchmark their proposed localization and tracking methods. In this paper, we propose a system and a dataset collected from our PIR system consisting of commercial-of-the-shelf (COTS) sensors without any modification. Our dataset includes profile data of 36 classes that have over 1,000 samples of different walking directions and test data consisting of multiple scenarios with a sequence length of over 2,000 timesteps. To evaluate our system and dataset, we implement various deep learning methods such as CNN, RNN, and CNN–RNN. Our results prove the applicability and feasibility of our system and illustrate the viability of deep learning methods for PIR-based localization and tracking. We also show that our dataset can be converted for coordinate estimation so that deep learning methods and particle filter approaches can be applied to estimate coordinates. As a result, the best performer achieves a distance error of 0.25 m.