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2022 ◽  
Vol 7 ◽  
Author(s):  
Nahla Al Qassimi ◽  
Chuloh Jung

Due to hot desert weather, residents of the United Arab Emirates (UAE) spend 90% of their time indoors, and the interior environment of the newly built apartments with inappropriate material and ventilation is causing sick building syndrome (SBS), faster than in any other country. NASA studies on indoor air pollutants indicate that the usage of 15–18 air-purifying plants in 18–24 cm diameter containers can clean the air in an average 167.2 m2 house (approximately one plant per 9.2 m2). This study investigates the effect of three different types of air-purifying plants, Pachira aquatica, Ficus benjamina, and Aglaonema commutatum, in reducing volatile organic compounds (VOCs) and formaldehyde (CH2O) in hot desert climate. An experiment is performed in which the CH2O and VOCs concentrations are measured in two laboratory spaces (Room 1 and Room 2). Different volumes (5 and 10% of the laboratory volume) of target plants are installed in Room 1, whereas Room 2 is measured under the same conditions without plants for comparison. The results show that the greater the planting volume (10%), the greater is the reduction effect of each VOCs. In summer in hot desert climate, the initial concentration (800 µg/cm3) of CH2O and VOCs is higher, and the reduction amount is higher (534.5 µg/cm3) as well. The reduction amount of CH2O and toluene (C7H8) is particularly high. In the case of C7H8, the reduction amount (45.9 µg/cm3) is higher in summer with Aglaonema commutatum and Ficus benjamina. It is statistically proven that Ficus benjamina is most effective in reducing CH2O and C7H8 in an indoor space in hot desert climate. The findings of this study can serve as basic data for further improving the indoor air quality using only air-purifying plants in hot desert climate of the United Arab Emirates.


2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Peng Wang ◽  
Jing Yang ◽  
Jianpei Zhang

Unlike outdoor trajectory prediction that has been studied many years, predicting the movement of a large number of users in indoor space like shopping mall has just been a hot and challenging issue due to the ubiquitous emerging of mobile devices and free Wi-Fi services in shopping centers in recent years. Aimed at solving the indoor trajectory prediction problem, in this paper, a hybrid method based on Hidden Markov approach is proposed. The proposed approach clusters Wi-Fi access points according to their similarities first; then, a frequent subtrajectory based HMM which captures the moving patterns of users has been investigated. In addition, we assume that a customer’s visiting history has certain patterns; thus, we integrate trajectory prediction with shop category prediction into a unified framework which further improves the predicting ability. Comprehensive performance evaluation using a large-scale real dataset collected between September 2012 and October 2013 from over 120,000 anonymized, opt-in consumers in a large shopping center in Sydney was conducted; the experimental results show that the proposed method outperforms the traditional HMM and perform well enough to be usable in practice.


Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 105
Author(s):  
Ibrahim Al-Helal ◽  
Abdullah Alsadon ◽  
Samy Marey ◽  
Abdullah Ibrahim ◽  
Mohamed Shady ◽  
...  

In arid regions, drastic seasonal variations in the climatic parameters are common; thus, a high potential of geothermal effects for heating/cooling applications is expected. However, such applications are very limited in these regions due to the lack of information about underground temperature profiles of the surface and shallow zones. Therefore, this study aims to (i) measure the underground temperature profile for one year to determine the optimum depth for burying EAHE pipes; (ii) examine the possibility of water vapour condensation occurring in the buried EAHE pipes, if the air let into the pipes was humid; and (iii) quantify the maximum cooling/heating capacity, if an EAHE was implemented. The results show that a 3-meter depth is optimal to bury EAHE pipes, where the ground temperature is 32 °C in the summer and 29 °C in the winter. These temperatures would provide a maximum cooling/heating capacity of 1000/890 MJ day−1 for each 1 m3 of humid air exhausted from a greenhouse. If the EAHE were to operate in a closed loop with a greenhouse, the condensation of water vapour in the EAHE pipes would be impossible during the cooling process. The results of this study are useful for designers using geothermal effects for indoor space cooling and heating in arid regions.


Buildings ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 59
Author(s):  
Zhixing Li ◽  
Yukai Zou ◽  
Mimi Tian ◽  
Yuxi Ying

This paper first analyzes the climate characteristics of five typical cities in China, including Harbin, Beijing, Shanghai, Shenzhen and Kunming. Then, based on Grasshopper, Ladybug and Honeybee analysis software, according to the indoor layout of typical residential buildings, this research extracts design parameters such as the depth and width of different rooms and their window-to-wall ratios etc., to establish a climate responsive optimization design process with indoor lighting environment comfort, with heating and cooling demand as the objective functions. Meanwhile, based on Monte Carlo simulation data, ANN (Artificial Neural Network) is used to establish a prediction model to analyze the sensitivity of interior design parameters under different typical cities’ climatic conditions. The study results show that the recommended values for the total width and total depth of indoor units under the climatic conditions of each city are both approximately 14.97 m and 7.88 m. Among them, under the climatic conditions of Harbin and Shenzhen, the design parameters of residential interiors can take the recommended value of UDI optimal or nZEB optimal. While the recommended values of window-to-wall ratios for the north bedroom, master bedroom and living room in Shanghai residential interiors are 0.26, 0.32 and 0.33, respectively. The recommended value of the window-to-wall ratio of the master bedroom in Kunming residences is 0.36, and that of the remaining rooms is between 0.15 and 0.18. The recommended values of window-to-wall ratios for the master bedroom and living room in Beijing residences are 0.41 and 0.59, respectively, and that for the remaining rooms are 0.15. The multi-objective optimization process based on parametric performance simulation used in the study can effectively assist architects in making energy-saving design decisions in the preliminary stage, allowing architects to have a case to follow in the actual design operation process.


Materials ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 354
Author(s):  
Huaguo Chen ◽  
Cheuk Lun Chow ◽  
Denvid Lau

Aluminum windows are crucial components of building envelopes since they connect the indoor space to the external environment. Various external causes degrade or harm the functioning of aluminum windows. In this regard, inspecting the performance of aluminum windows is a necessary task to keep buildings healthy. This review illustrates the deterioration mechanisms of aluminum windows under various environmental conditions with an intention to provide comprehensive information for developing damage protection and inspection technologies. The illustrations reveal that moisture and chloride ions have the most detrimental effect on deteriorating aluminum windows in the long run, while mechanical loads can damage aluminum windows in a sudden manner. In addition, multiple advanced inspection techniques potential to benefit assessing aluminum window health state are discussed in order to help tackle the efficiency problem of traditional visual inspection. The comparison among those techniques demonstrates that infrared thermography can help acquire a preliminary defect profile of inspected windows, whereas ultrasonic phased arrays technology demonstrates a high level of competency in analyzing comprehensive defect information. This review also discusses the challenges in the scarcity of nanoscale corrosion information for insightful understandings of aluminum window corrosion and reliable window inspection tools for lifespan prediction. In this regard, molecular dynamics simulation and artificial intelligence technology are recommended as promising tools for better revealing the deterioration mechanisms and advancing inspection techniques, respectively, for future directions. It is envisioned that this paper will help upgrade the aluminum window inspection scheme and contribute to driving the construction of intelligent and safe cities.


Buildings ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 15
Author(s):  
Pei Zhou ◽  
Songjie Wang ◽  
Zhao Jin ◽  
Gongsheng Huang ◽  
Jian Zhu ◽  
...  

An indoor high and open space is characterized by high mobility of people and uneven temperature distribution, so the conventional design and operation of air conditioning systems makes it difficult to regulate the air conditioning system precisely and efficiently. Thus, a Wireless Sensor Network was constructed in an indoor space located in Hong Kong to monitor the indoor environmental parameters of the space and improve the temperature control effectively. To ensure the continuity of the measurement data, three algorithms for reconstructing temperature, relative humidity and carbon dioxide data were implemented and compared. The results demonstrate the accuracy of support vector regression model and multiple linear regression model is higher than Back Propagation neural network model for reconstructing temperature data. Multiple linear regression is the most convenient from the perspective of program complexity, computing speed and difficulty in obtaining input conditions. Based on the data we collected, the traditional single-input-single-output control, zonal temperature control and the proposed zonal demand control methods were modeled on a Transient System Simulation Program (TRNSYS) control platform, the thermal coupling between the subzones without physical partition was taken into account, and the mass transfer between the virtual boundaries was calculated by an external CONTAM program. The simulation results showed the proposed zonal demand control can alleviate the over-cooling or over-heating phenomenon in conventional temperature control, thermal comfort and energy reduction is enhanced as well.


Author(s):  
Mohammed Abdul Baseer ◽  
Khusroo Ahmed Ansari ◽  
Anant A. Takalkar

Background: ICDS scheme represents one of the largest programmes, which is a symbol of India’s commitment to its children, providing pre-school education on one hand and breaking the today vicious cycle of malnutrition, morbidity, reduced learning capacity and mortality on the other hand.Methods: The present study was taken up to assess the infrastructure and services of anganwadi centers. Community based cross sectional observational study was conducted by involving 92 anganwadi centers in Kalaburagi city.Results: Out of 92 AWCs studied, 52 (56.5%) were belonged to Government set up whereas 40 i.e.; 43.5% were on rental basis. Safe drinking water was available in 81 i.e.; 88% of AWCs, toilet facility was available in 34 i.e.; 37% of AWCs. Adequate outdoor space was available in 54 i.e.; 58.7% of AWCs. Adequate indoor space was available in 72 i.e.; 78.3% of AWCs. Adequate kitchen space was available in 65 i.e.; 70.7% of AWCs. Adequate food storage facility was available in 70 i.e.; 76.1% of AWCs and in 22 i.e.; 23.9% it was not adequate. In 30 i.e.; 32.6% of AWCs, source of fuel use was LPG.Conclusions: Safe drinking water was available in majority of AWCs. Almost one third of anganwadi have inadequate space. Majority of anganwadi have maintained sufficient number of registers. Outdoor and indoor game kits and equipment’s were available at majority of AWCs.


Author(s):  
Junsik Park ◽  
Gurjoong Kim

South Korea’s social distancing policies on public transportation only involve mandatory wearing of masks and prohibition of food intake, similar to policies on other indoor spaces. This is not because public transportation is safe from coronavirus disease 2019 (COVID-19), but because no suitable policies based on accurate data have been implemented. To relieve fears regarding contracting COVID-19 infection through public transportation, the government should provide accurate information and take appropriate measures to lower the risk of COVID-19. This study aimed to develop a model for determining the risk of COVID-19 infection on public transportation considering exposure time, mask efficiency, ventilation rate, and distance. The risk of COVID-19 infection on public transportation was estimated, and the effectiveness of measures to reduce the risk was assessed. The correlation between the risk of infection and various factors was identified through sensitivity analysis of major factors. The analysis shows that, in addition to the general indoor space social distancing policy, ventilation system installation, passenger number reduction in a vehicle, and seat distribution strategies were effective. Based on these results, the government should provide accurate guidelines and implement appropriate policies.


Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8078
Author(s):  
Petter Stefansson ◽  
Fredrik Karlsson ◽  
Magnus Persson ◽  
Carl Magnus Olsson

Quantifying the number of occupants in an indoor space is useful for a wide variety of applications. Attempts have been made at solving the task using passive infrared (PIR) motion sensor data together with supervised learning methods. Collecting a large labeled dataset containing both PIR motion sensor data and ground truth people count is however time-consuming, often requiring one hour of observation for each hour of data gathered. In this paper, a method is proposed for generating such data synthetically. A simulator is developed in the Unity game engine capable of producing synthetic PIR motion sensor data by detecting simulated occupants. The accuracy of the simulator is tested by replicating a real-world meeting room inside the simulator and conducting an experiment where a set of choreographed movements are performed in the simulated environment as well as the real room. In 34 out of 50 tested situations, the output from the simulated PIR sensors is comparable to the output from the real-world PIR sensors. The developed simulator is also used to study how a PIR sensor’s output changes depending on where in a room a motion is carried out. Through this, the relationship between sensor output and spatial position of a motion is discovered to be highly non-linear, which highlights some of the difficulties associated with mapping PIR data to occupancy count.


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