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This document discusses air pollution prediction using machine learning techniques. It begins with an introduction to air pollution, defining it as the introduction of harmful substances into the atmosphere. The six main criteria air pollutants are then described: ozone, particulate matter, carbon monoxide, nitrogen dioxide, sulfur dioxide, and lead. Common machine learning techniques for air pollution prediction are also introduced, including supervised learning algorithms like random forests and support vector machines, and unsupervised learning algorithms like k-means clustering. The document concludes that machine learning provides opportunities for improved air pollution prediction by analyzing historical pollution data.
A Literature Review on Ambient Air Quality Monitoring Near the Solid Waste Di...IRJET Journal
This document presents a literature review on ambient air quality monitoring near a solid waste disposal site in Harihar Taluk, Davangere District, Karnataka, India. It discusses methodologies used in previous studies to determine concentration levels of air pollutants like particulate matter, sulfur dioxide, and nitrogen dioxide near solid waste sites. It also reviews how previous studies have calculated and predicted air quality index values based on measured pollutant concentrations. The objectives of the literature review are to determine pollutant concentration levels near the Harihar solid waste site and compare them to national standards, and to calculate and predict air quality index values for the site.
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Construction sites are important source of air pollution emitting pollutants like PM10, etc. which adversely affect human health especially the respiratory system. The present study aims at monitoring of PM10, health condition of workers, evaluation of API (Air Pollution Index) and development of correlation between API and human health in the vicinity of construction sites. In the present study relevant literature review has also been carried out to study and analyze the impact of air pollution on human health. Reconnaissance survey of 19 selected construction sites in Delhi-NCR has been conducted for the period January 2013 to December 2013 and health related data of people in the vicinity of construction sites has been collected individually through a questionnaire. The air quality data (for pollutant PM10) for the area in which the selected construction sites lie has been obtained from the continuous monitoring stations of Central Pollution Control Board. The monthly average PM10 concentration in the ambient air for the study period has been obtained for all the sites. The annual average PM10 level of all the sites has been estimated and compared with the prescribed value. Also the air pollution index (API) (for pollutant PM10) has been calculated for each site and compared with the percentage of people suffering with respiratory problems at the respective sites. The results show that the construction sites where the value of API for PM10 is higher there the percentage of people suffering with respiratory diseases has also been higher.
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This document discusses using multiple regression analysis to predict air quality factors based on atmospheric pollutant data from an Italian city. The study uses hourly concentration data for CO, hydrocarbons, benzene, nitrogen oxides, and nitrogen dioxide from 2004-2005. Regression coefficients are estimated to determine how variables correlate with each other. Evaluation metrics like R-squared and adjusted R-squared are calculated, and actual vs predicted values are graphed. The results show the regression model can effectively predict air quality factors based on pollutant concentrations. Future work could involve using deep learning on real-time data.
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The document analyzes air pollution levels in the city of Kozhikode, India before, during, and after COVID-19 lockdowns. It finds that levels of particulate matter and other pollutants decreased during lockdowns when traffic and industrial activity were reduced but increased again after lockdowns ended as normal activity resumed. The study concludes that vehicles and industries are major contributors to air pollution in Kozhikode and recommends actions like promoting electric vehicles and renewable energy to improve air quality.
STUDY ON AMBIENT AIR QUALITY MONITORING FROM GOVT POLYTECHNIC COLLEGE TO GUTT...IRJET Journal
This document summarizes a study on ambient air quality monitoring between Government Polytechnic College and Guttur Road in Harihara City, India. Air quality was monitored over two months at five sites for pollutants SPM, SO2, and NO2. In April and May, air quality was best at A K Colony and Guttur Road with an impact of minimal. Government Polytechnic College and Shivamogga Circle had satisfactory air quality with minor impacts. Harapanahalli Circle had the highest pollution levels and moderate impacts including breathing difficulties. Overall, the study found air quality within permissible limits according to the air quality index.
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This document discusses using a hybrid machine learning technique combining differential evolution and random forest methods to predict air pollution levels. It analyzes data on various pollutants from two cities in India - Delhi and Patna. The proposed approach is experimentally validated to achieve better performance compared to independent classifiers and multi-label classifiers in terms of accuracy, area under the curve, success index and correlation. Differential evolution is used to initialize population and optimize candidate solutions. Random forest creates an ensemble of decision trees to make predictions. The hybrid method is tested on predicting carbon monoxide, nitrogen dioxide and benzene levels using data from a monitoring station in Delhi.
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This document discusses a study on assessing air quality in Delhi, India using the Air Quality Index (AQI). It provides background on air pollution and the importance of measuring AQI. The study calculates daily AQI values over three years for Delhi based on concentrations of pollutants like NO2, SO2, SPM and RSPM. The results show AQI values were regularly unhealthy around 200. SPM and RSPM correlated most strongly with AQI, suggesting they are major contributors to air pollution. Stricter measures are needed to address rising levels of particulate matter and improve air quality.
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This document discusses air pollution prediction using machine learning techniques. It begins with an introduction to air pollution, defining it as the introduction of harmful substances into the atmosphere. The six main criteria air pollutants are then described: ozone, particulate matter, carbon monoxide, nitrogen dioxide, sulfur dioxide, and lead. Common machine learning techniques for air pollution prediction are also introduced, including supervised learning algorithms like random forests and support vector machines, and unsupervised learning algorithms like k-means clustering. The document concludes that machine learning provides opportunities for improved air pollution prediction by analyzing historical pollution data.
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This document presents a literature review on ambient air quality monitoring near a solid waste disposal site in Harihar Taluk, Davangere District, Karnataka, India. It discusses methodologies used in previous studies to determine concentration levels of air pollutants like particulate matter, sulfur dioxide, and nitrogen dioxide near solid waste sites. It also reviews how previous studies have calculated and predicted air quality index values based on measured pollutant concentrations. The objectives of the literature review are to determine pollutant concentration levels near the Harihar solid waste site and compare them to national standards, and to calculate and predict air quality index values for the site.
Impact of Air Quality on Human Health In The Vicinity of Construction Sites i...IJERA Editor
Construction sites are important source of air pollution emitting pollutants like PM10, etc. which adversely affect human health especially the respiratory system. The present study aims at monitoring of PM10, health condition of workers, evaluation of API (Air Pollution Index) and development of correlation between API and human health in the vicinity of construction sites. In the present study relevant literature review has also been carried out to study and analyze the impact of air pollution on human health. Reconnaissance survey of 19 selected construction sites in Delhi-NCR has been conducted for the period January 2013 to December 2013 and health related data of people in the vicinity of construction sites has been collected individually through a questionnaire. The air quality data (for pollutant PM10) for the area in which the selected construction sites lie has been obtained from the continuous monitoring stations of Central Pollution Control Board. The monthly average PM10 concentration in the ambient air for the study period has been obtained for all the sites. The annual average PM10 level of all the sites has been estimated and compared with the prescribed value. Also the air pollution index (API) (for pollutant PM10) has been calculated for each site and compared with the percentage of people suffering with respiratory problems at the respective sites. The results show that the construction sites where the value of API for PM10 is higher there the percentage of people suffering with respiratory diseases has also been higher.
Prediction of Air Quality Influential Factors with AtmosphericAir Present Pol...IRJET Journal
This document discusses using multiple regression analysis to predict air quality factors based on atmospheric pollutant data from an Italian city. The study uses hourly concentration data for CO, hydrocarbons, benzene, nitrogen oxides, and nitrogen dioxide from 2004-2005. Regression coefficients are estimated to determine how variables correlate with each other. Evaluation metrics like R-squared and adjusted R-squared are calculated, and actual vs predicted values are graphed. The results show the regression model can effectively predict air quality factors based on pollutant concentrations. Future work could involve using deep learning on real-time data.
AIR POLLUTION IMPACT ON ENVIRONMENT IN KOZHIKODE CITYIRJET Journal
The document analyzes air pollution levels in the city of Kozhikode, India before, during, and after COVID-19 lockdowns. It finds that levels of particulate matter and other pollutants decreased during lockdowns when traffic and industrial activity were reduced but increased again after lockdowns ended as normal activity resumed. The study concludes that vehicles and industries are major contributors to air pollution in Kozhikode and recommends actions like promoting electric vehicles and renewable energy to improve air quality.
AIR POLLUTION IMPACT ON ENVIRONMENT IN KOZHIKODE CITYIRJET Journal
This document analyzes air pollution in Kozhikode City, India. It finds that strong population growth and increased waste, vehicles, and industry have led to worsening air quality. The study examines air pollutant levels in Kozhikode using data from the Pollution Control Board. It analyzes data from 2019-2021 during pre-lockdown, lockdown, and post-lockdown periods of the COVID-19 pandemic. The lockdown reduced traffic and industrial activities, decreasing air pollution temporarily. Particulate matter, nitrogen oxides, sulfur dioxide, and ammonia levels fluctuated over time. Vehicle emissions and industrial activities were major contributors to air pollution, which worsened air quality and health. Str
The document presents information on emerging technologies for air quality monitoring. It discusses various air pollutants like particulate matter, carbon monoxide, nitrogen oxides, and sulfur dioxides. It also describes different air sampling processes and the application of air quality index (AQI) to report daily air quality levels. The document outlines the objectives to analyze air quality data from pollution control boards and use sensors to provide cautionary values to alert people and improve air quality. It discusses literature review on indoor air quality and wireless sensor networks for air monitoring.
STUDY OF AIR QUALITY MONITORING OF NEARBY AREAS OF MUMBAI METRO STATION DURIN...IRJET Journal
This study analyzed air quality near 3 metro construction sites in Mumbai over a period of time. Air pollutants such as PM2.5, PM10, SO2, NOx, and CO were monitored using dust sampling instruments. The highest pollution levels were found at the Churchgate site, followed by Hutatma Chowk, with the lowest levels at Vidhanbhawan. Ventilation was found to be a key factor affecting pollutant concentrations. Pedestrian traffic also impacted PM2.5 levels. Maintaining open ventilation and limiting pedestrian congestion could help reduce underground pollution during construction. Regular monitoring is important to ensure standards are met and mitigate health impacts on surrounding communities.
Assessment of Ambient Air Quality of Hoshangabad of M.P.ijtsrd
Air quality assessment is frequently driven by the need to determine whether a standard or guideline has been exceeded. This overshadows another objective of air quality assessment providing the information needed to estimate population exposure to air pollution and the effects on the health of the population. In this study analysis of air pollutants such as PM10, PM2.5, SO2, and NO2, were assessed to determine the ambient air quality of Hoshangabad City. The PM10 and PM2.5 were found moderate for residential area i.e. Meenakshi Chowk and higher than the permissible limit for other monitoring stations. Seasonal variation of PM10 and PM2.5 showed that in winter air quality becomes worst due to low temperature and humidity particulate matter condenses in lower atmosphere. Gaseous air pollutants SO2, and NOx were well below the permissible limit in all the sampling station in all three study years. Seasonal values for SO2 and NO2 were also found within the permissible limits at all the stations and in all the seasons. Deepa Rajput | Dr. O. N. Choubey "Assessment of Ambient Air Quality of Hoshangabad of M.P." Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd59941.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/environmental-science/59941/assessment-of-ambient-air-quality-of-hoshangabad-of-mp/deepa-rajput
Studies on Ambient Air Quality Monitoring Near the Solid Waste Disposal Site ...IRJET Journal
This study monitored ambient air quality near a solid waste disposal site in Harihar Taluk, Davangere District, India. Parameters like suspended particulate matter (SPM), sulfur dioxide (SO2), and nitrogen dioxide (NO2) were measured using a high-volume air sampler at locations north, south, east, west, and 500m/1.5km from the site. The air quality index (AQI) was calculated and found to range from 0-50, indicating air quality was within national standards and safe for employees. While SPM levels were close to industrial zone standards, SO2 and NO2 concentrations met national ambient air quality standards guidelines at all locations during the study period.
This document presents a framework for visualizing air quality data. It involves collecting data on various air pollutants, preprocessing the data, using a machine learning model to predict an Air Quality Index, and visualizing the results. Specifically, it trains a random forest regression model on data from the Central Pollution Control Board to predict the AQI based on parameters like PM2.5, PM10, NO2, etc. It then implements the model to make real-time predictions using an API and stores the results in a database. These predictions are visualized on an interactive web page to show users the current air quality levels. The framework aims to help people monitor local air quality and help government organizations address areas with poor air quality.
Seasonal Air Pollution Variation in Delhi (2019): A Case Study using by the G...IRJET Journal
This document summarizes a study on seasonal air pollution variation in Delhi, India in 2019. The study analyzed data from 39 air quality monitoring stations in Delhi to examine concentrations of PM10, PM2.5, NO2, SO2, O3, and CO. Pollution levels were generally higher in winter compared to monsoon season due to factors like agricultural stubble burning, vehicle emissions, and weather phenomena like fog and mist. Using an air quality index, the study found pollution levels in winter ranged from satisfactory to severe, while monsoon levels ranged from good to satisfactory. Pollution levels tended to be higher on weekday working days compared to weekends.
Ambient Air Quality in China - The Impact of Particulate and Gaseous Pollutan...comller
China faces serious air quality challenges due to high levels of outdoor and indoor air pollution that exceed quality standards. Ambient air pollution increases health risks in the population. Enhanced air cleaning devices that combine technologies like HEPA filters, activated carbon, and silver nanoparticles are available to effectively remove air pollutants including PM10, PM2.5, formaldehyde, ozone, sulfur dioxide, nitrogen dioxide, and volatile organic compounds in order to improve indoor air quality. Testing of these devices in cities like Beijing, Shanghai, and Guangzhou show their effectiveness at reducing common pollutants.
An environmental impact assessment was conducted for a proposed integrated steel plant in Odisha, India. The summary finds:
1) Ambient air quality monitoring found existing PM10 and PM2.5 levels above national standards in the project area. Dispersion modeling also predicted the plant would significantly increase air pollution.
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A Deep Learning Based Air Quality PredictionDereck Downing
The document discusses using deep learning techniques to predict air quality. Specifically, it proposes using a Long Short-Term Memory (LSTM) model to predict hourly air quality index values. The LSTM model is trained on historical air quality and meteorological data. The proposed LSTM model is found to outperform existing models at predicting air quality, as measured by a lower root mean square error (RMSE) value for predictions. The document aims to develop techniques for accurately forecasting air quality to help address increasing air pollution issues.
Analysis and Prediction of Air Quality in IndiaIRJET Journal
This document discusses analyzing and predicting air quality in India using machine learning algorithms. The authors collected air quality data from various Indian cities from 2018 to 2021, including levels of pollutants like PM2.5, PM10, NO2, O3, and SO2. They analyzed trends over time and the impact of lockdowns. Different time series forecasting algorithms (ARIMA, Prophet, LSTM, ETS) were used to predict future air quality levels. ARIMA provided the best predictions. The analyses and predictions were developed into a dashboard application to visualize trends and comparisons of the different algorithms. The work provides a model for predicting air quality that can help identify heavily polluted regions and reverse air pollution in India
An Analytical Survey on Prediction of Air Quality Indexijtsrd
A drastic increase of modernization gives birth to many industries and automobiles, which intern becomes the very common reason for the environmental issues like Air and water pollutions. Air pollution is the immediate affecting factors in our life, which contaminates the air that we breathe to cause serious health hazards. So it is very important to predict the Air quality index for the future coming days so that proper prompt action can be taken by the concern authorities to curb the same. The air quality reading for the different gases can be collect through the physical sensors and these readings can be used to predict the future Air quality index. Machine learning is acting as the catalyst in this prediction scenario to predict the accurate Air quality index for the future instance. Most of the learning systems need a huge amount of the data for the learning purpose and it is not possible to provide this every time. So it is a need to predict the air quality index by using considerable less amount of past instance data, This paper mainly concentrates on analyzing the past work in prediction of air quality index using machine learning and try to evaluate their flaws and to estimate the new possible way of prediction using machine learning. Suraj Kapse | Akshay Kurumkar | Vighnesh Manthapurvar | Prof. Rajesh Tak "An Analytical Survey on Prediction of Air Quality Index" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28072.pdf Paper URL: https://www.ijtsrd.com/engineering/information-technology/28072/an-analytical-survey-on-prediction-of-air-quality-index/suraj-kapse
This document discusses air pollution indices and how they are used. Air pollution indices transform weighted air pollution parameter values like SPM, SO2, CO, NO2, O3, and hydrocarbons into a single number to simply and clearly indicate the air quality level. They inform the public about daily pollution changes, help compare cities, and evaluate enforcement policies. Common calculation methods include relating parameters to standards, averaging ratios to standards, and assigning sub-index values within parameter ranges. Air pollution indices provide a useful way to track air quality changes and facilitate comparisons.
Monitoring and assessment of air quality with reference to dust particles (pm...eSAT Publishing House
This document summarizes a study on monitoring and assessing air quality with respect to dust particles (PM10 and PM2.5) in the urban environment of Visakhapatnam, India. Sampling was conducted in residential, commercial, and industrial areas from October 2013 to August 2014. The average PM2.5 and PM10 concentrations were within limits in residential areas but moderate to high in commercial and industrial areas. Exceedance factor levels indicated moderate pollution for residential areas and moderate to high pollution for commercial and industrial areas. There is a need for management measures like improved public transport and green spaces to combat particulate air pollution in the study areas.
IRJET- Assessment and Characterization of Dust in Surface Mine at Differe...IRJET Journal
This document summarizes a study that assessed and characterized dust levels at different working conditions in a surface mine. Dust was monitored using high volume samplers to measure particulate matter levels of PM10 and PM2.5 at both a core working zone and buffer village zone. Higher dust concentrations of both PM10 and PM2.5 were found at the core working zone compared to the buffer village zone, with some villages near operations recording even higher levels than the core zone. The results indicate that mining activities generate airborne dust and that dust levels decrease with increasing distance from operations. Characterizing the dust is important for understanding health impacts and mitigating pollution.
IRJET- IoT based Air Pollution Monitoring System to Create a Smart EnvironmentIRJET Journal
This document describes an IoT-based air pollution monitoring system that uses sensors and the Arduino microcontroller to collect real-time air quality data from specific locations. The data is analyzed against a threshold and sent to authorities if pollution levels exceed limits. It also activates an alert system to warn surrounding people. The system aims to remotely monitor pollution without human interaction using Internet of Things technology. This creates a smart environment for reducing health issues from industrial activities by finding solutions to harmful gas emissions.
Analysis Of Air Pollutants Affecting The Air Quality Using ARIMAIRJET Journal
This document discusses analyzing air pollutants affecting air quality using the ARIMA time series model. It begins with an abstract describing the decreasing air quality due to factors like traffic and industry. It then discusses predicting and forecasting the Air Quality Index using time series models like ARIMA. The document reviews literature on previous studies analyzing air pollution data using techniques like neural networks and random forests. It describes preprocessing time series air pollution data to address missing values and assess stationarity before deploying the ARIMA model to make predictions.
Analysis Of A Severe Air Pollution Episode In India During Diwali Festival ...Emily Smith
This document analyzes a severe air pollution episode in India during Diwali in late October and November 2016. Air quality index was observed to vary from poor to severe in northern and western India, but was satisfactory to moderate in the south and east. The causes of high pollution levels were examined. Fireworks during Diwali contributed to increased particulate matter, sulfur dioxide, nitrogen oxides and benzene levels in New Delhi, Lucknow, Jaipur and Ahmedabad on Diwali day compared to before and after. Prolonged high pollution in many areas also indicated the importance of biomass burning across India apart from Diwali effects on air quality.
IRJET- Air Pollution Monitoring System using the Internet of ThingsIRJET Journal
This document describes an air pollution monitoring system using the Internet of Things (IoT). The system uses sensors to detect harmful gases like CO2, NOx, and smoke. It displays the air quality levels in parts per million on an LCD screen and online. When pollution levels exceed a threshold, an alarm is activated. The system measures temperature and humidity as well. Data is sent to a web server via WiFi so that air quality can be monitored remotely. The goal is to provide real-time air quality information to raise awareness and help reduce pollution by informing people about pollution levels in different areas.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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3) Based on estimated annual emissions of 9433 tons of PM, 13,131 tons of NOx, and 11,642 tons of SO2, a health impact assessment was conducted and found significant impacts from increased
IRJET - Prediction of Air Pollutant Concentration using Deep LearningIRJET Journal
This document describes a study that used artificial neural networks to predict PM2.5 air pollutant concentration levels in Manali, Chennai, India. The study collected data on PM2.5 levels as well as factors like NO2, SO2, CO, relative humidity, and wind speed over a three year period. An artificial neural network model with feed-forward backpropagation was developed using this data, with 6 input nodes (for each pollutant/factor) and 1 output node (for PM2.5 levels). The model was trained on 70% of the data and tested on the remaining 15%, achieving a correlation coefficient between predicted and observed PM2.5 of 0.8. The study demonstrated that artificial neural
A Deep Learning Based Air Quality PredictionDereck Downing
The document discusses using deep learning techniques to predict air quality. Specifically, it proposes using a Long Short-Term Memory (LSTM) model to predict hourly air quality index values. The LSTM model is trained on historical air quality and meteorological data. The proposed LSTM model is found to outperform existing models at predicting air quality, as measured by a lower root mean square error (RMSE) value for predictions. The document aims to develop techniques for accurately forecasting air quality to help address increasing air pollution issues.
Analysis and Prediction of Air Quality in IndiaIRJET Journal
This document discusses analyzing and predicting air quality in India using machine learning algorithms. The authors collected air quality data from various Indian cities from 2018 to 2021, including levels of pollutants like PM2.5, PM10, NO2, O3, and SO2. They analyzed trends over time and the impact of lockdowns. Different time series forecasting algorithms (ARIMA, Prophet, LSTM, ETS) were used to predict future air quality levels. ARIMA provided the best predictions. The analyses and predictions were developed into a dashboard application to visualize trends and comparisons of the different algorithms. The work provides a model for predicting air quality that can help identify heavily polluted regions and reverse air pollution in India
An Analytical Survey on Prediction of Air Quality Indexijtsrd
A drastic increase of modernization gives birth to many industries and automobiles, which intern becomes the very common reason for the environmental issues like Air and water pollutions. Air pollution is the immediate affecting factors in our life, which contaminates the air that we breathe to cause serious health hazards. So it is very important to predict the Air quality index for the future coming days so that proper prompt action can be taken by the concern authorities to curb the same. The air quality reading for the different gases can be collect through the physical sensors and these readings can be used to predict the future Air quality index. Machine learning is acting as the catalyst in this prediction scenario to predict the accurate Air quality index for the future instance. Most of the learning systems need a huge amount of the data for the learning purpose and it is not possible to provide this every time. So it is a need to predict the air quality index by using considerable less amount of past instance data, This paper mainly concentrates on analyzing the past work in prediction of air quality index using machine learning and try to evaluate their flaws and to estimate the new possible way of prediction using machine learning. Suraj Kapse | Akshay Kurumkar | Vighnesh Manthapurvar | Prof. Rajesh Tak "An Analytical Survey on Prediction of Air Quality Index" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28072.pdf Paper URL: https://www.ijtsrd.com/engineering/information-technology/28072/an-analytical-survey-on-prediction-of-air-quality-index/suraj-kapse
This document discusses air pollution indices and how they are used. Air pollution indices transform weighted air pollution parameter values like SPM, SO2, CO, NO2, O3, and hydrocarbons into a single number to simply and clearly indicate the air quality level. They inform the public about daily pollution changes, help compare cities, and evaluate enforcement policies. Common calculation methods include relating parameters to standards, averaging ratios to standards, and assigning sub-index values within parameter ranges. Air pollution indices provide a useful way to track air quality changes and facilitate comparisons.
Monitoring and assessment of air quality with reference to dust particles (pm...eSAT Publishing House
This document summarizes a study on monitoring and assessing air quality with respect to dust particles (PM10 and PM2.5) in the urban environment of Visakhapatnam, India. Sampling was conducted in residential, commercial, and industrial areas from October 2013 to August 2014. The average PM2.5 and PM10 concentrations were within limits in residential areas but moderate to high in commercial and industrial areas. Exceedance factor levels indicated moderate pollution for residential areas and moderate to high pollution for commercial and industrial areas. There is a need for management measures like improved public transport and green spaces to combat particulate air pollution in the study areas.
IRJET- Assessment and Characterization of Dust in Surface Mine at Differe...IRJET Journal
This document summarizes a study that assessed and characterized dust levels at different working conditions in a surface mine. Dust was monitored using high volume samplers to measure particulate matter levels of PM10 and PM2.5 at both a core working zone and buffer village zone. Higher dust concentrations of both PM10 and PM2.5 were found at the core working zone compared to the buffer village zone, with some villages near operations recording even higher levels than the core zone. The results indicate that mining activities generate airborne dust and that dust levels decrease with increasing distance from operations. Characterizing the dust is important for understanding health impacts and mitigating pollution.
IRJET- IoT based Air Pollution Monitoring System to Create a Smart EnvironmentIRJET Journal
This document describes an IoT-based air pollution monitoring system that uses sensors and the Arduino microcontroller to collect real-time air quality data from specific locations. The data is analyzed against a threshold and sent to authorities if pollution levels exceed limits. It also activates an alert system to warn surrounding people. The system aims to remotely monitor pollution without human interaction using Internet of Things technology. This creates a smart environment for reducing health issues from industrial activities by finding solutions to harmful gas emissions.
Analysis Of Air Pollutants Affecting The Air Quality Using ARIMAIRJET Journal
This document discusses analyzing air pollutants affecting air quality using the ARIMA time series model. It begins with an abstract describing the decreasing air quality due to factors like traffic and industry. It then discusses predicting and forecasting the Air Quality Index using time series models like ARIMA. The document reviews literature on previous studies analyzing air pollution data using techniques like neural networks and random forests. It describes preprocessing time series air pollution data to address missing values and assess stationarity before deploying the ARIMA model to make predictions.
Analysis Of A Severe Air Pollution Episode In India During Diwali Festival ...Emily Smith
This document analyzes a severe air pollution episode in India during Diwali in late October and November 2016. Air quality index was observed to vary from poor to severe in northern and western India, but was satisfactory to moderate in the south and east. The causes of high pollution levels were examined. Fireworks during Diwali contributed to increased particulate matter, sulfur dioxide, nitrogen oxides and benzene levels in New Delhi, Lucknow, Jaipur and Ahmedabad on Diwali day compared to before and after. Prolonged high pollution in many areas also indicated the importance of biomass burning across India apart from Diwali effects on air quality.
IRJET- Air Pollution Monitoring System using the Internet of ThingsIRJET Journal
This document describes an air pollution monitoring system using the Internet of Things (IoT). The system uses sensors to detect harmful gases like CO2, NOx, and smoke. It displays the air quality levels in parts per million on an LCD screen and online. When pollution levels exceed a threshold, an alarm is activated. The system measures temperature and humidity as well. Data is sent to a web server via WiFi so that air quality can be monitored remotely. The goal is to provide real-time air quality information to raise awareness and help reduce pollution by informing people about pollution levels in different areas.
Similar to Assessment of Variation in Concentration of Air Pollutants Within Monitoring Stations in Mumbai (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.