The Impact of Fine Particulate Matters (PM10, PM2.5) from Incense Smokes on the Various Organ Systems: A Review of an Invisible Killer DOI
Virendra Kumar Yadav,

Sangha Bijekar,

Amel Gacem

et al.

Particle & Particle Systems Characterization, Journal Year: 2023, Volume and Issue: 41(5)

Published: Dec. 21, 2023

Abstract The drastic increase in industrialization has led to numerous adverse effects on the environment and human health. Respiratory tract disorders are one of major emerging global health issues that lead a high mortality rate every year. quality indoor outdoor air lowered last decade.The deteriorated by cooking, smoking, burning incense sticks or smoke. smoke released from contains gaseous products (carbon monoxide, nitrogen dioxide, oxide sulfur), particular matter (PM 10 , PM 2.5 ), volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs). These toxic components various sources pose significant risk environment. inhalation exposure incenses is hazardous as it inevitably culminates deadly organ‐related diseases. With such insights, present review article focuses characteristic attributes particulate other emphasizing healthcare environmental concerns.

Language: Английский

Machine Learning-Based CO2 Prediction for Office Room: A Pilot Study DOI Creative Commons
Nishant Raj Kapoor, Ashok Kumar, Anuj Kumar

et al.

Wireless Communications and Mobile Computing, Journal Year: 2022, Volume and Issue: 2022, P. 1 - 16

Published: March 7, 2022

Air pollution is increasing profusely in Indian cities as well throughout the world, and it poses a major threat to climate health of all living things. reason behind degraded indoor air quality (IAQ) urban buildings. Carbon dioxide (CO2) main contributor humans themselves are one generating sources this pollutant. The testing monitoring CO2 consume cost time require smart sensors. Thus, solve these limitations, machine learning (ML) has been used predict concentration inside an office room. This study based on data collected through real-time measurements CO2, number occupants, area per person, outdoor temperature, outer wind speed, relative humidity, index input parameters. In study, ten algorithms, namely, artificial neural network (ANN), support vector (SVM), decision tree (DT), Gaussian process regression (GPR), linear (LR), ensemble (EL), optimized GPR, EL, DT, SVM, were CO2. It found that GPR model performs better than other selected models terms prediction accuracy. result indicated can with highest accuracy having R , RMSE, MAE, NS, a20-index values 0.98874, 4.20068 ppm, 3.35098 0.9817, 1, respectively. be utilized by designers, researchers, healthcare professionals, city developers analyse for designing ventilation systems level

Language: Английский

Citations

50
Hierarchical and K-means clustering to assess thermal dissatisfaction and productivity in university classrooms DOI
Ana Maria Bueno, Inaiele Mendes da Luz, Iasmin Lourenço Niza

et al.

Building and Environment, Journal Year: 2023, Volume and Issue: 233, P. 110097 - 110097

Published: Feb. 14, 2023

Language: Английский

Citations

30
Artificial intelligence in civil engineering DOI
Nishant Raj Kapoor, Ashok Kumar, Anuj Kumar

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 74

Published: Jan. 1, 2024

Citations

11
Passive strategies for energy-efficient educational facilities: Insights from a mediterranean primary school DOI Creative Commons

Salah-Eddine Jaouaf,

Bourassia Bensaad, Mustapha Habib

et al.

Energy Reports, Journal Year: 2024, Volume and Issue: 11, P. 3653 - 3683

Published: March 22, 2024

This study investigates the thermal and energetic dynamics of primary school classrooms in a Mediterranean climate Khoualed Abdel Hakeem, Ain Temouchent County, Algeria. The research highlights significant optimizations by focusing on passive strategies such as external shading devices, Window-to-Wall Ratio (WWR), glazing types, building envelope adjustments. Our simulations, validated rigorously, showcase remarkable congruence with actual electricity consumption, affirming reliability efficacy our simulation model valuable predictive tool. A Vertical Shading Angle (VSA) 60° proves optimal, resulting an impressive 11% reduction Annual Energy Consumption (AEC). recommended WWR 30% demonstrates decrease AEC improves energy efficiency. Double Low Emissivity (Double-Low E) is found to be superior, 14% AEC. Achieving 50% shaded areas helps maintain well-balanced environment, 12% heating cooling requirements. integration optimized showcases 44% overall consumption. results highlight strategies, promoting energy-conscious ecologically responsible practices, advocating for their incorporation educational facilities, offering insights sustainable design.

Language: Английский

Citations

9
Transmission Probability of SARS-CoV-2 in Office Environment Using Artificial Neural Network DOI Creative Commons
Nishant Raj Kapoor, Ashok Kumar, Anuj Kumar

et al.

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 121204 - 121229

Published: Jan. 1, 2022

In this paper, curve-fitting and an artificial neural network (ANN) model were developed to predict R-Event. Expected number of new infections that arise in any event occurring over a total time space is termed as Real-time data for the office environment was gathered spring 2022 naturally ventilated room Roorkee, India, under composite climatic conditions. To ascertain merit proposed ANN models, performances approach compared against curve fitting regarding conventional statistical indicators, i.e., correlation coefficient, root mean square error, absolute Nash-Sutcliffe efficiency index, percentage a20-index. Eleven input parameters namely indoor temperature ( TIn ), relative humidity xmlns:xlink="http://www.w3.org/1999/xlink">RHIn area opening xmlns:xlink="http://www.w3.org/1999/xlink">AO occupants xmlns:xlink="http://www.w3.org/1999/xlink">O per person xmlns:xlink="http://www.w3.org/1999/xlink">AP volume xmlns:xlink="http://www.w3.org/1999/xlink">VP xmlns:xlink="http://www.w3.org/1999/xlink">CO 2 concentration air quality index xmlns:xlink="http://www.w3.org/1999/xlink">AQI outer wind speed xmlns:xlink="http://www.w3.org/1999/xlink">WS outdoor xmlns:xlink="http://www.w3.org/1999/xlink">TOut xmlns:xlink="http://www.w3.org/1999/xlink">RHOut ) used study R-Event value output. The primary goal research establish link between value; eventually providing prediction purposes. case study, coefficient 0.9992 0.9557, respectively. It shows model's higher accuracy than prediction. Results indicate performance (R=0.9992, RMSE=0.0018708, MAE=0.0006675, MAPE=0.8643816, NS=0.9984365, a20-index=0.9984300) reliable highly accurate R-event offices.

Language: Английский

Citations

31
Tropical climates and the interplay between IEQ and energy consumption in buildings: A review DOI Open Access
Ashutosh Kumar Verma, Vallary Gupta, Kopal Nihar

et al.

Building and Environment, Journal Year: 2023, Volume and Issue: 242, P. 110551 - 110551

Published: June 23, 2023

Language: Английский

Citations

20
Enhancing Sustainability of Corroded RC Structures: Estimating Steel-to-Concrete Bond Strength with ANN and SVM Algorithms DOI Open Access
Rohan Singh, Harish Chandra Arora, Alireza Bahrami

et al.

Materials, Journal Year: 2022, Volume and Issue: 15(23), P. 8295 - 8295

Published: Nov. 22, 2022

The bond strength between concrete and corroded steel reinforcement bar is one of the main responsible factors that affect ultimate load-carrying capacity reinforced (RC) structures. Therefore, prediction accurate has become an important parameter for safety measurements RC However, analytical models are not enough to estimate strength, as they built using various assumptions limited datasets. machine learning (ML) techniques named artificial neural network (ANN) support vector (SVM) have been used bar. considered input parameters in this research surface area specimen, cover, type bars, yield compressive diameter length, water/cement ratio, corrosion level bars. These were build ANN SVM models. reliability developed compared with twenty Moreover, analyzed results revealed precision efficiency higher radar plot Taylor diagrams also utilized show graphical representation best-fitted model. proposed model best model, a correlation coefficient 0.99, mean absolute error 1.091 MPa, root square 1.495 MPa. Researchers designers can apply precisely steel-to-concrete strength.

Language: Английский

Citations

26
Effects of school indoor visual environment on children's health outcomes: A systematic review DOI Creative Commons
Xue Meng, Mingxin Zhang, Mohan Wang

et al.

Health & Place, Journal Year: 2023, Volume and Issue: 83, P. 103021 - 103021

Published: July 2, 2023

Children's visual perceptions are critical for their comfort and health. This review explores the impacts of school indoor environment on children's health outcomes. A systematic search yielded 5704 articles, which 32 studies were reviewed. Five environmental themes identified: lighting, access to nature, window characteristics, art/environmental aesthetics, ergonomics/spatial arrangement. Results affirm that affects There disparities across themes, with more extensive evidence lighting but relatively limited in other areas. study suggests a need multi-disciplinary collaboration develop holistic perspective.

Language: Английский

Citations

14
Recent Achievements in Research on Thermal Comfort and Ventilation in the Aspect of Providing People with Appropriate Conditions in Different Types of Buildings—Semi-Systematic Review DOI Creative Commons
Katarzyna Ratajczak, Łukasz Amanowicz, Katarzyna Pałaszyńska

et al.

Energies, Journal Year: 2023, Volume and Issue: 16(17), P. 6254 - 6254

Published: Aug. 28, 2023

Ventilation systems are mainly responsible for maintaining the quality of indoor air. Together with thermal comfort maintenance systems, they create appropriate conditions living, working, learning, sleeping, etc., depending on type building. This explains high popularity research in this area. paper presents a review articles published years 2020–2023, which indexed Scopus database and found keywords “ventilation” “thermal comfort” conjunction building or predominant activity. Finally, 88 selected works five types buildings were discussed, namely offices, schools, hospitals, bedrooms, atriums. Data publications summarized tables, taking into account publishing year, country origin authors, keywords. In way, latest directions presented, groups dealing subject highlighted. For each building, synthetic conclusions summarizing results analyzed research. would be helpful scientists practitioners field ventilation order to organize knowledge short time up date showing how affects use by their users.

Language: Английский

Citations

13
The parameter of the Sick Building Syndrome: A systematic literature review DOI Creative Commons

Mohamed Sazif Mohamed Subri,

Kadir Arifin,

Muhamad Faiz Aiman Mohd Sohaimin

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(12), P. e32431 - e32431

Published: June 1, 2024

Sick Building Syndrome (SBS) is a collection of symptoms assumed to be related spending time in certain building, most typically workplace, but no specific cause has been identified. The need measure and assess various types parameters SBS crucial it important explore what parameter used the previous studies SBS. Therefore, this study aims systematically review that monitor This was conducted using PRISMA Statement search two scientific databases which were Scopus Web Science. After thorough tight process, total 55 articles have finalized selected for thematic analysis. Two themes identified a) Indoor Environmental Quality (IEQ) b) Occupant. also found spatial distribution pattern revealed research spread over 26 nations, with majority originating from United States China. In terms context, publications employed survey approach investigate parameters. Aside that, researched form building business building. would more impactful if researchers could incorporate both indoor environmental quality occupant factors into study, resulting holistic conclusions.

Language: Английский

Citations

5