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
IRJET- Analysis and Prediction of Air QualityIRJET Journal
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.
Implementation of Integration VaaMSN and SEMAR for Wide Coverage Air Quality ...TELKOMNIKA JOURNAL
The current air quality monitoring system cannot cover a large area, not real-time and has not
implemented big data analysis technology with high accuracy. The purpose of an integration Mobile
Sensor Network and Internet of Things system is to build air quality monitoring system that able to monitor
in wide coverage. This system consists of Vehicle as a Mobile Sensors Network (VaaMSN) as edge
computing and Smart Environment Monitoring and Analytic in Real-time (SEMAR) cloud computing.
VaaMSN is a package of air quality sensor, GPS, 4G Wi-Fi modem and single board computing. SEMAR
cloud computing has a time-series database for real-time visualization, Big Data environment and analytics
use the Support Vector Machines (SVM) and Decision Tree (DT) algorithm. The output from the system
are maps, table, and graph visualization. The evaluation obtained from the experimental results shows that
the accuracy of both algorithms reaches more than 90%. However, Mean Square Error (MSE) value of
SVM algorithm about 0.03076293, but DT algorithm has 10x smaller MSE value than SVM algorithm.
Evaluating Air Pollution Parameters Using Zigbee (IEEE 802.15.4)IOSR Journals
This document describes a system that uses Zigbee wireless technology and sensors to monitor air pollution parameters in real-time. The system includes sensor nodes that measure pollutants like CO2, SO2, and NO2 and transmit the data via Zigbee to a central receiver. The receiver interfaces with a GPS module and database to record and geotag the pollution levels. The system was tested with 4 transmitter nodes sending data to a single receiver node. Results showed graphs of pollution levels over time and across the different nodes, demonstrating real-time air quality monitoring.
Design and Implementation of Portable Outdoor Air Quality Measurement System ...IJECEIAES
Recently, there is increasing public awareness of the real time air quality due to air pollution can cause severe effects to human health and environments. The Air Pollutant Index (API) in Malaysia is measured by Department of Environment (DOE) using stationary and expensive monitoring station called Continuous Air Quality Monitoring stations (CAQMs) that are only placed in areas that have high population densities and high industrial activities. Moreover, Malaysia did not include particulate matter with the size of less than 2.5µm (PM2.5) in the API measurement system. In this paper, we present a cost effective and portable air quality measurement system using Arduino Uno microcontroller and four low cost sensors. This device allows people to measure API in any place they want. It is capable to measure the concentration of carbon monoxide (CO), ground level ozone (O3) and particulate matters (PM10 & PM2.5) in the air and convert the readings to API value. This system has been tested by comparing the API measured from this device to the current API measured by DOE at several locations. Based on the results from the experiment, this air quality measurement system is proved to be reliable and efficient.
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.
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.
Air pollution monitoring system using mobile gprs sensors array pptSaurabh Giratkar
ppt This paper contain brief introduction to vehicular pollution, effect of increase in vehicular pollution on environment as well on human health. To monitor this pollution wireless sensor network (WSN) system is proposed. The proposed system consists of a Mobile Data-Acquisition Unit (Mobile-DAQ) and a fixed Internet-Enabled Pollution Monitoring Server (Pollution-Server). The Mobile-DAQ unit integrates a single-chip microcontroller, air pollution sensors array, a General Packet Radio Service Modem (GPRS-Modem), and a Global Positioning System Module (GPS-Module). The Pollution-Server is a high-end personal computer application server with Internet connectivity. The Mobile-DAQ unit gathers air pollutants levels (CO, NO2, and SO2), and packs them in a frame with the GPS physical location, time, and date. The frame is subsequently uploaded to the GPRS-Modem and transmitted to the Pollution-Server via the public mobile network. A database server is attached to the Pollution- Server for storing the pollutants level for further usage by various clients such as environment protection agencies, vehicles registration authorities, and tourist and insurance companies.
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- Analysis and Prediction of Air QualityIRJET Journal
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.
Implementation of Integration VaaMSN and SEMAR for Wide Coverage Air Quality ...TELKOMNIKA JOURNAL
The current air quality monitoring system cannot cover a large area, not real-time and has not
implemented big data analysis technology with high accuracy. The purpose of an integration Mobile
Sensor Network and Internet of Things system is to build air quality monitoring system that able to monitor
in wide coverage. This system consists of Vehicle as a Mobile Sensors Network (VaaMSN) as edge
computing and Smart Environment Monitoring and Analytic in Real-time (SEMAR) cloud computing.
VaaMSN is a package of air quality sensor, GPS, 4G Wi-Fi modem and single board computing. SEMAR
cloud computing has a time-series database for real-time visualization, Big Data environment and analytics
use the Support Vector Machines (SVM) and Decision Tree (DT) algorithm. The output from the system
are maps, table, and graph visualization. The evaluation obtained from the experimental results shows that
the accuracy of both algorithms reaches more than 90%. However, Mean Square Error (MSE) value of
SVM algorithm about 0.03076293, but DT algorithm has 10x smaller MSE value than SVM algorithm.
Evaluating Air Pollution Parameters Using Zigbee (IEEE 802.15.4)IOSR Journals
This document describes a system that uses Zigbee wireless technology and sensors to monitor air pollution parameters in real-time. The system includes sensor nodes that measure pollutants like CO2, SO2, and NO2 and transmit the data via Zigbee to a central receiver. The receiver interfaces with a GPS module and database to record and geotag the pollution levels. The system was tested with 4 transmitter nodes sending data to a single receiver node. Results showed graphs of pollution levels over time and across the different nodes, demonstrating real-time air quality monitoring.
Design and Implementation of Portable Outdoor Air Quality Measurement System ...IJECEIAES
Recently, there is increasing public awareness of the real time air quality due to air pollution can cause severe effects to human health and environments. The Air Pollutant Index (API) in Malaysia is measured by Department of Environment (DOE) using stationary and expensive monitoring station called Continuous Air Quality Monitoring stations (CAQMs) that are only placed in areas that have high population densities and high industrial activities. Moreover, Malaysia did not include particulate matter with the size of less than 2.5µm (PM2.5) in the API measurement system. In this paper, we present a cost effective and portable air quality measurement system using Arduino Uno microcontroller and four low cost sensors. This device allows people to measure API in any place they want. It is capable to measure the concentration of carbon monoxide (CO), ground level ozone (O3) and particulate matters (PM10 & PM2.5) in the air and convert the readings to API value. This system has been tested by comparing the API measured from this device to the current API measured by DOE at several locations. Based on the results from the experiment, this air quality measurement system is proved to be reliable and efficient.
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.
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.
Air pollution monitoring system using mobile gprs sensors array pptSaurabh Giratkar
ppt This paper contain brief introduction to vehicular pollution, effect of increase in vehicular pollution on environment as well on human health. To monitor this pollution wireless sensor network (WSN) system is proposed. The proposed system consists of a Mobile Data-Acquisition Unit (Mobile-DAQ) and a fixed Internet-Enabled Pollution Monitoring Server (Pollution-Server). The Mobile-DAQ unit integrates a single-chip microcontroller, air pollution sensors array, a General Packet Radio Service Modem (GPRS-Modem), and a Global Positioning System Module (GPS-Module). The Pollution-Server is a high-end personal computer application server with Internet connectivity. The Mobile-DAQ unit gathers air pollutants levels (CO, NO2, and SO2), and packs them in a frame with the GPS physical location, time, and date. The frame is subsequently uploaded to the GPRS-Modem and transmitted to the Pollution-Server via the public mobile network. A database server is attached to the Pollution- Server for storing the pollutants level for further usage by various clients such as environment protection agencies, vehicles registration authorities, and tourist and insurance companies.
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.
Prediction of atmospheric pollution using neural networks model of fine parti...IJECEIAES
This work shows an application based on neural networks to determine the prediction of air pollution, especially particulate material of 2.5 micrometers length. This application is considered of great importance due to the impact on human health and high impact due to the agglomeration of people in cities. The implementation is performed using data captured from several devices that can be installed in specific locations for a particular geographical environment, especially in the locality of Kennedy in Bogotá. The model obtained can be used for the design of public policies that control air quality.
Smart environment project in thailand 2021 dr.obrom aranyaprukDr. Obrom Aranyapruk
The document discusses a smart environment and city project in Rayong, Thailand. Sensors were installed to monitor air quality factors like PM2.5, VOCs, SO2, NO2, O3, temperature and humidity across a 17 square kilometer area. Over 170 sensors collect and transmit data every 5 seconds to a server for analysis. The goals are to provide real-time air quality monitoring, classify pollution levels, and develop tools to help manage environmental conditions and health impacts in a smart city framework.
Quantification of rate of air pollution by means ofIJARBEST JOURNAL
To develop efficient strategies for pollution control, it is essential to assess
both the costs of control and the benefits that may result. These benefits will often include
improvements in public health, including reductions in both morbidity and premature
mortality. Until recently, there has been little guidance about how to calculate the benefits
of air pollution controls and how to use those estimates to assign priorities to different air
pollution control strategies. In this work, a method is described for quantifying the benefits
of reduced ambient concentrations of pollutants (such as ozone and particulate matter)
typically found in urban areas worldwide. The method applies the data on Jakara, Indonesia,
an area characterized by little wind, high population density (8 million people), congested
roads, and ambient air pollution. The magnitude of the benefits of pollution control depends
on the level of air pollution, the expected effects on health of the pollutants (dose-response),
the size of the population affected, and the economic value of these effects. In the case of
Jakarta, the methodology suggests that reducing exposure to lead and nitrogen dioxide
should also be a high priority. An important consequence of ambient lead pollution is a
reduction in learning abilities for children, measured as I.Q. loss. Apart from that, reducing
the proportion of respirable particles can reduce the amount of illness and premature
mortality.
The document describes a BeagleBone Black-based air quality monitoring system using IoT. It defines air pollution and lists common sources. It includes block diagrams of the system components including BeagleBone Black, MQ3 and MQ7 sensors for measuring air quality, and signal conditioners. It also provides details on interfacing the sensors with BeagleBone Black, software used including Debian OS, Python coding, and creating a web user interface using Plotly for displaying air quality data.
The document discusses issues and options for air pollution control in India. It outlines important steps already taken, such as establishing emission standards and fuel quality standards. However, it notes ongoing issues like pollution from coal power plants and small industries. Options proposed include strengthening enforcement of standards, promoting cleaner fuels and technologies, expanding air quality monitoring networks, and controlling pollution from sectors like transport and waste management.
Scientific Publication - Air Quality Monitoring (Scopus Buletinul Stiintific)Marco Brini
Low-cost sensors open new opportunities for air quality monitoring by allowing for higher spatial resolution and near real-time monitoring. A study evaluated using low-cost sensors to monitor critical situations like near schools and highways. Sensors for NO2, CO, and O3 were selected. Preliminary tests in Turin found low-cost O3 sensors detected peaks comparable to regulatory monitors. Based on the results, a strategy was developed for sensor networks in Trentino, Italy to monitor various industrial sites and residential/tourist areas. The approach aims to improve human health protection by detecting localized pollution peaks not seen by conventional monitoring systems.
This document summarizes a study that measured carbonaceous aerosol concentrations at an urban residential site in Agra, India from May to August 2011. The key findings include:
1) The average concentration of PM2.5 was 55.3±17.4 μg/m3, within prescribed limits. Organic carbon varied from 7.6 to 37.5 μg/m3 with an average of 18.2±6.4 μg/m3. Elemental carbon ranged from 1.2 to 9.4 μg/m3 with an average of 3.2±1.6 μg/m3.
2) Total carbonaceous aerosols accounted for 64.9%
Learn the Tricks to Get the Best from Your City Ambient Air Quality Monitorin...Prasad Modak
Cities operate ambient air quality monitoring networks but often do not analyze and interpret the data. Data gets simply "stacked". Networks are not configured correctly capturing the data trends and monitoring objectives. This presentation provides guidance and uses Mumbai's ambient air quality data to illustrate application
Monituring & control in air pollutionAMAN PANDEY
Monitoring is done to track air quality by collecting information on key indicators like SO2, smoke, and suspended particles which are measured daily by a central agency. Common monitoring methods include measuring SO2 levels through colorimetric or conductivity tests, determining smoke index by filtering air through paper and measuring stains, and collecting grit and dust using deposit gauges which are analyzed monthly. Air quality in major Indian cities has exceeded standards according to a national monitoring program, with coastal areas showing the highest levels of fine particulate matter.
This document describes a system that uses ZigBee wireless technology and sensors to monitor air pollution levels in an urban environment in real-time. The system measures levels of carbon monoxide, nitrogen dioxide, and sulfur dioxide using sensors connected to a microcontroller. The sensor data is sent to a central server via ZigBee modules and coordinators. The system aims to accurately measure pollution levels frequently to improve understanding of air quality and public health.
This document discusses criteria for setting ambient air quality standards. It outlines several factors that influence decision making for standards, including acceptable health risks, control costs, and scientific judgment. Standards are designed to protect public health from air pollution effects and may establish maximum concentrations. Primary standards protect health, while secondary standards protect welfare. Factors like meteorology, geography, exposure levels, health risks, economics and policies must be considered when setting standards.
Accuracy Improvement of PM Measuring Instrumentsijtsrd
The PM10 concentration in the underground areas should be monitored to protect the health of the commuters in the underground subway system. The purpose of this work is to study the reliability of the instruments using light scattering method to measure the PM10 concentrations continuously. A linear regression analysis method is used to improve the performance of the instruments using light scattering method. Some experimental results show that a linear regression technique would be very helpful for the performance improvement of light scattering instruments such as Air test PM2500 and HCT 4103. Tae-In Hyon | Gyu-Sik Kim "Accuracy Improvement of PM Measuring Instruments" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26722.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/26722/accuracy-improvement-of-pm-measuring-instruments/tae-in-hyon
IRJET- Indian Water Pollution Monitoring and Forecasting for Anomaly with...IRJET Journal
This document describes a proposed system to monitor and forecast water pollution in India using wireless sensor networks and machine learning techniques. Sensors would collect data on various water quality parameters like pH, nitrates, fecal coliform, biochemical oxygen demand, dissolved oxygen, and temperature from multiple locations. The data would be analyzed using machine learning algorithms to predict future pollution levels and identify anomalies. The system aims to reduce pollution by providing advanced monitoring and early warnings. Redundant sensor nodes and failure detection would ensure the system's reliability.
Carbon level detection of vehicle for preventing Air Pollution using IOT SensorsIJSRED
The document describes a system for detecting carbon levels in vehicle emissions using IoT sensors to prevent air pollution. The system uses sensors to measure the levels of carbon monoxide, carbon dioxide, methane, and other gases released by vehicles. If the gas levels exceed thresholds, the vehicle will be locked and can only be unlocked by an authorized official after servicing. The system notifies users when gas levels are high to service their vehicle before it gets locked. It aims to control air pollution and its impacts on global warming and human health. The architecture uses sensors connected to an ESP8266 controller over Wi-Fi to an Android app and database for monitoring and control.
IRJET- Pollution Monitoring System using RF CommunicationIRJET Journal
This document describes a pollution monitoring system that uses sensors and RF communication to monitor various air and noise pollution factors in real-time. The system consists of sensors to detect gases like carbon monoxide, nitrogen dioxide, sulfur dioxide, as well as dust, humidity, temperature and noise levels. The sensor data is transmitted using RF modules to a monitoring device like a computer. The monitoring system is intended to detect pollution levels and send alerts when thresholds are exceeded to protect human health.
Ambient Air Pollution Monitoring - A brief history from early UK measurements...IES / IAQM
Early ambient air pollution monitoring in the UK began in the 1950s in response to deadly smog events. This led to the first national monitoring network in the 1960s measuring smoke and sulfur dioxide. Understanding of complex photochemical smog developed in the 1970s from US experiences, widening monitoring to include other traffic-related pollutants. By the 1990s, many ambient air quality surveys had begun, facilitated by new instrumentation. Current strategies for monitoring individual sites involve defining clear objectives to design cost-effective programs considering parameters, timing, locations, and methods.
This document discusses air pollution and methods for sampling air quality. It defines air pollution as undesirable atmospheric substances including gases and particulate matter from sources like industries, vehicles and waste. There are two main sampling methods - continuous and time-averaged. Samples are then analyzed using physical, chemical and biological methods to determine concentration levels over time. Sampling locations and equipment depend on the study objectives. Regular monitoring measures substances like sulfur dioxide weekly to assess national ambient air quality.
Carbon Monoxide Monitoring System Based On Arduino-GSM for Environmental Moni...IJERA Editor
In recent years with tremendous progress in technology and growth in demand for vehicles, an individual fizzle to look after awful factors that occur due to improper maintenance of vehicles results in increase in air pollution and which results in disturbing environmental condition all over the world, that tends to raise global warming. In this paper “Carbon Monoxide Monitoring System Based on Arduino-GSM for Environmental Monitoring Application” is a system which detects the Carbon Monoxide (CO) gas coming out of a vehicle which is displayed on vehicle itself, so when the level of CO increases alerts will be sent to the owner of vehicle regarding maintenance of vehicle and if action is not taken regarding CO the vehicle is made to stop and later allowed to start the vehicle after given period. This cycle is continued to keep the CO free environment and also reduce human efforts to monitor each and every vehicle. The repetitively breaking down of a vehicle causes the owner to take serious action for reducing the CO of his vehicle.
Qualitative assessment of links between exposure to noise and air pollution a...IES / IAQM
The document summarizes research on the links between exposure to noise and air pollution, and socioeconomic status. Key findings include:
- Poorer groups often live and work in more polluted areas, and may be more susceptible to health impacts of pollution.
- Road traffic is a major source of both noise and air pollution in urban areas, where exposure is highest. Agriculture is a main source of air pollution.
- Research shows lower socioeconomic groups experience higher mortality and morbidity rates associated with air pollution exposure compared to higher socioeconomic groups.
- Children, the elderly, and those with pre-existing health conditions - who may be over-represented in lower socioeconomic groups - are more susceptible to health impacts of noise
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.
IRJET- Recognition of Future Air Quality Index using Artificial Neural NetworkIRJET Journal
This document proposes using an artificial neural network to predict future air quality index levels based on historical pollution data. It involves:
1. Collecting data on various air pollutants like SO2, NO2, PM from a government website.
2. Training a multilayer perceptron neural network model on the historical data to understand relationships between pollutant levels and air quality index.
3. Using the trained model to predict future air quality index levels for a specific location based on new pollutant data, allowing predictions for next day, next month, or future years.
The system aims to help predict air pollution levels to inform people and avoid health problems. It will provide location-specific analysis and forecasts
Prediction of atmospheric pollution using neural networks model of fine parti...IJECEIAES
This work shows an application based on neural networks to determine the prediction of air pollution, especially particulate material of 2.5 micrometers length. This application is considered of great importance due to the impact on human health and high impact due to the agglomeration of people in cities. The implementation is performed using data captured from several devices that can be installed in specific locations for a particular geographical environment, especially in the locality of Kennedy in Bogotá. The model obtained can be used for the design of public policies that control air quality.
Smart environment project in thailand 2021 dr.obrom aranyaprukDr. Obrom Aranyapruk
The document discusses a smart environment and city project in Rayong, Thailand. Sensors were installed to monitor air quality factors like PM2.5, VOCs, SO2, NO2, O3, temperature and humidity across a 17 square kilometer area. Over 170 sensors collect and transmit data every 5 seconds to a server for analysis. The goals are to provide real-time air quality monitoring, classify pollution levels, and develop tools to help manage environmental conditions and health impacts in a smart city framework.
Quantification of rate of air pollution by means ofIJARBEST JOURNAL
To develop efficient strategies for pollution control, it is essential to assess
both the costs of control and the benefits that may result. These benefits will often include
improvements in public health, including reductions in both morbidity and premature
mortality. Until recently, there has been little guidance about how to calculate the benefits
of air pollution controls and how to use those estimates to assign priorities to different air
pollution control strategies. In this work, a method is described for quantifying the benefits
of reduced ambient concentrations of pollutants (such as ozone and particulate matter)
typically found in urban areas worldwide. The method applies the data on Jakara, Indonesia,
an area characterized by little wind, high population density (8 million people), congested
roads, and ambient air pollution. The magnitude of the benefits of pollution control depends
on the level of air pollution, the expected effects on health of the pollutants (dose-response),
the size of the population affected, and the economic value of these effects. In the case of
Jakarta, the methodology suggests that reducing exposure to lead and nitrogen dioxide
should also be a high priority. An important consequence of ambient lead pollution is a
reduction in learning abilities for children, measured as I.Q. loss. Apart from that, reducing
the proportion of respirable particles can reduce the amount of illness and premature
mortality.
The document describes a BeagleBone Black-based air quality monitoring system using IoT. It defines air pollution and lists common sources. It includes block diagrams of the system components including BeagleBone Black, MQ3 and MQ7 sensors for measuring air quality, and signal conditioners. It also provides details on interfacing the sensors with BeagleBone Black, software used including Debian OS, Python coding, and creating a web user interface using Plotly for displaying air quality data.
The document discusses issues and options for air pollution control in India. It outlines important steps already taken, such as establishing emission standards and fuel quality standards. However, it notes ongoing issues like pollution from coal power plants and small industries. Options proposed include strengthening enforcement of standards, promoting cleaner fuels and technologies, expanding air quality monitoring networks, and controlling pollution from sectors like transport and waste management.
Scientific Publication - Air Quality Monitoring (Scopus Buletinul Stiintific)Marco Brini
Low-cost sensors open new opportunities for air quality monitoring by allowing for higher spatial resolution and near real-time monitoring. A study evaluated using low-cost sensors to monitor critical situations like near schools and highways. Sensors for NO2, CO, and O3 were selected. Preliminary tests in Turin found low-cost O3 sensors detected peaks comparable to regulatory monitors. Based on the results, a strategy was developed for sensor networks in Trentino, Italy to monitor various industrial sites and residential/tourist areas. The approach aims to improve human health protection by detecting localized pollution peaks not seen by conventional monitoring systems.
This document summarizes a study that measured carbonaceous aerosol concentrations at an urban residential site in Agra, India from May to August 2011. The key findings include:
1) The average concentration of PM2.5 was 55.3±17.4 μg/m3, within prescribed limits. Organic carbon varied from 7.6 to 37.5 μg/m3 with an average of 18.2±6.4 μg/m3. Elemental carbon ranged from 1.2 to 9.4 μg/m3 with an average of 3.2±1.6 μg/m3.
2) Total carbonaceous aerosols accounted for 64.9%
Learn the Tricks to Get the Best from Your City Ambient Air Quality Monitorin...Prasad Modak
Cities operate ambient air quality monitoring networks but often do not analyze and interpret the data. Data gets simply "stacked". Networks are not configured correctly capturing the data trends and monitoring objectives. This presentation provides guidance and uses Mumbai's ambient air quality data to illustrate application
Monituring & control in air pollutionAMAN PANDEY
Monitoring is done to track air quality by collecting information on key indicators like SO2, smoke, and suspended particles which are measured daily by a central agency. Common monitoring methods include measuring SO2 levels through colorimetric or conductivity tests, determining smoke index by filtering air through paper and measuring stains, and collecting grit and dust using deposit gauges which are analyzed monthly. Air quality in major Indian cities has exceeded standards according to a national monitoring program, with coastal areas showing the highest levels of fine particulate matter.
This document describes a system that uses ZigBee wireless technology and sensors to monitor air pollution levels in an urban environment in real-time. The system measures levels of carbon monoxide, nitrogen dioxide, and sulfur dioxide using sensors connected to a microcontroller. The sensor data is sent to a central server via ZigBee modules and coordinators. The system aims to accurately measure pollution levels frequently to improve understanding of air quality and public health.
This document discusses criteria for setting ambient air quality standards. It outlines several factors that influence decision making for standards, including acceptable health risks, control costs, and scientific judgment. Standards are designed to protect public health from air pollution effects and may establish maximum concentrations. Primary standards protect health, while secondary standards protect welfare. Factors like meteorology, geography, exposure levels, health risks, economics and policies must be considered when setting standards.
Accuracy Improvement of PM Measuring Instrumentsijtsrd
The PM10 concentration in the underground areas should be monitored to protect the health of the commuters in the underground subway system. The purpose of this work is to study the reliability of the instruments using light scattering method to measure the PM10 concentrations continuously. A linear regression analysis method is used to improve the performance of the instruments using light scattering method. Some experimental results show that a linear regression technique would be very helpful for the performance improvement of light scattering instruments such as Air test PM2500 and HCT 4103. Tae-In Hyon | Gyu-Sik Kim "Accuracy Improvement of PM Measuring Instruments" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26722.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/26722/accuracy-improvement-of-pm-measuring-instruments/tae-in-hyon
IRJET- Indian Water Pollution Monitoring and Forecasting for Anomaly with...IRJET Journal
This document describes a proposed system to monitor and forecast water pollution in India using wireless sensor networks and machine learning techniques. Sensors would collect data on various water quality parameters like pH, nitrates, fecal coliform, biochemical oxygen demand, dissolved oxygen, and temperature from multiple locations. The data would be analyzed using machine learning algorithms to predict future pollution levels and identify anomalies. The system aims to reduce pollution by providing advanced monitoring and early warnings. Redundant sensor nodes and failure detection would ensure the system's reliability.
Carbon level detection of vehicle for preventing Air Pollution using IOT SensorsIJSRED
The document describes a system for detecting carbon levels in vehicle emissions using IoT sensors to prevent air pollution. The system uses sensors to measure the levels of carbon monoxide, carbon dioxide, methane, and other gases released by vehicles. If the gas levels exceed thresholds, the vehicle will be locked and can only be unlocked by an authorized official after servicing. The system notifies users when gas levels are high to service their vehicle before it gets locked. It aims to control air pollution and its impacts on global warming and human health. The architecture uses sensors connected to an ESP8266 controller over Wi-Fi to an Android app and database for monitoring and control.
IRJET- Pollution Monitoring System using RF CommunicationIRJET Journal
This document describes a pollution monitoring system that uses sensors and RF communication to monitor various air and noise pollution factors in real-time. The system consists of sensors to detect gases like carbon monoxide, nitrogen dioxide, sulfur dioxide, as well as dust, humidity, temperature and noise levels. The sensor data is transmitted using RF modules to a monitoring device like a computer. The monitoring system is intended to detect pollution levels and send alerts when thresholds are exceeded to protect human health.
Ambient Air Pollution Monitoring - A brief history from early UK measurements...IES / IAQM
Early ambient air pollution monitoring in the UK began in the 1950s in response to deadly smog events. This led to the first national monitoring network in the 1960s measuring smoke and sulfur dioxide. Understanding of complex photochemical smog developed in the 1970s from US experiences, widening monitoring to include other traffic-related pollutants. By the 1990s, many ambient air quality surveys had begun, facilitated by new instrumentation. Current strategies for monitoring individual sites involve defining clear objectives to design cost-effective programs considering parameters, timing, locations, and methods.
This document discusses air pollution and methods for sampling air quality. It defines air pollution as undesirable atmospheric substances including gases and particulate matter from sources like industries, vehicles and waste. There are two main sampling methods - continuous and time-averaged. Samples are then analyzed using physical, chemical and biological methods to determine concentration levels over time. Sampling locations and equipment depend on the study objectives. Regular monitoring measures substances like sulfur dioxide weekly to assess national ambient air quality.
Carbon Monoxide Monitoring System Based On Arduino-GSM for Environmental Moni...IJERA Editor
In recent years with tremendous progress in technology and growth in demand for vehicles, an individual fizzle to look after awful factors that occur due to improper maintenance of vehicles results in increase in air pollution and which results in disturbing environmental condition all over the world, that tends to raise global warming. In this paper “Carbon Monoxide Monitoring System Based on Arduino-GSM for Environmental Monitoring Application” is a system which detects the Carbon Monoxide (CO) gas coming out of a vehicle which is displayed on vehicle itself, so when the level of CO increases alerts will be sent to the owner of vehicle regarding maintenance of vehicle and if action is not taken regarding CO the vehicle is made to stop and later allowed to start the vehicle after given period. This cycle is continued to keep the CO free environment and also reduce human efforts to monitor each and every vehicle. The repetitively breaking down of a vehicle causes the owner to take serious action for reducing the CO of his vehicle.
Qualitative assessment of links between exposure to noise and air pollution a...IES / IAQM
The document summarizes research on the links between exposure to noise and air pollution, and socioeconomic status. Key findings include:
- Poorer groups often live and work in more polluted areas, and may be more susceptible to health impacts of pollution.
- Road traffic is a major source of both noise and air pollution in urban areas, where exposure is highest. Agriculture is a main source of air pollution.
- Research shows lower socioeconomic groups experience higher mortality and morbidity rates associated with air pollution exposure compared to higher socioeconomic groups.
- Children, the elderly, and those with pre-existing health conditions - who may be over-represented in lower socioeconomic groups - are more susceptible to health impacts of noise
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.
IRJET- Recognition of Future Air Quality Index using Artificial Neural NetworkIRJET Journal
This document proposes using an artificial neural network to predict future air quality index levels based on historical pollution data. It involves:
1. Collecting data on various air pollutants like SO2, NO2, PM from a government website.
2. Training a multilayer perceptron neural network model on the historical data to understand relationships between pollutant levels and air quality index.
3. Using the trained model to predict future air quality index levels for a specific location based on new pollutant data, allowing predictions for next day, next month, or future years.
The system aims to help predict air pollution levels to inform people and avoid health problems. It will provide location-specific analysis and forecasts
IRJET- Air Pollution Prediction using Machine LearningIRJET Journal
This document describes a study that uses machine learning algorithms to predict air pollution levels in Pune, India. Specifically, it uses a multilayer perceptron neural network model to more accurately predict pollution levels compared to traditional linear regression. The study collects pollution data from 2000-2018 on pollutants like SO2, NO2, CO, PM10 and Ozone from the Central Pollution Control Board. It then preprocesses the data to handle missing values before training the multilayer perceptron model. The trained model is presented through a mobile app to provide accurate short-term air pollution predictions and help address Pune's significant air quality issues.
Air Pollution Prediction using Machine LearningIRJET Journal
This document discusses using machine learning algorithms to predict air pollution levels. Sensors are used to collect data on air quality, smoke and dust levels. This data is fed into a KNN machine learning model for training and testing. The KNN model achieved 99.1% accuracy in predicting air quality levels based on the Air Quality Index. Machine learning is effective for analyzing large environmental datasets and making accurate pollution predictions to help monitor air quality and reduce health issues from air pollution.
IRJET- Air Pollution Prediction System for Smart City using Data Mining T...IRJET Journal
This document discusses using data mining techniques to predict air pollution levels in a smart city. It begins with background on the health impacts of various air pollutants like particulate matter, nitrogen dioxide, sulfur dioxide, and carbon monoxide. It then describes using a multivariate, multistep time series approach with a random forest algorithm to predict future air pollution levels based on past and current pollution data as well as other attributes like temperature, wind speed, humidity, traffic levels, and the previous day's air quality. Finally, it reviews several related works that used techniques like neural networks, linear regression, extreme learning learning, and decision trees to predict pollution trends in other cities and compares their limitations and accuracies.
HOSTILE GAS MONITORING SYSTEM USING IoTIRJET Journal
1. The document describes a hostile gas monitoring system using IoT that monitors air pollution levels. It uses sensors to detect pollutants like CO, NO2, O3, and particulate matter.
2. The system uses an Arduino board connected to gas sensors and a WiFi module to transmit sensor data to a cloud database on the ThingSpeak server. This allows for continuous remote monitoring of pollution levels and analysis of the data.
3. The system is intended to be deployed in any location to monitor indoor or outdoor air quality and identify highly polluted areas so remedial measures can be taken.
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.
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 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
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.
EDD Project A35 group. final.pdf Department of ENTCMihirDatir1
This document describes an Arduino-based air monitoring system project. It includes an introduction describing the importance of air quality monitoring. It then lists the components of the system, which uses sensors to measure parameters like temperature, humidity, and carbon dioxide levels. The methodology section explains how the Arduino board will read analog voltage values from the sensors and use those to monitor air quality levels. It will control a filter fan if thresholds are exceeded. The system aims to continuously track air quality and display results to increase pollution awareness. It provides a low-cost solution to monitor indoor and outdoor air quality.
IRJET - Air Quality Index – A Study to Assess the Air QualityIRJET Journal
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.
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
IRJET- Web-Based Air and Noise Pollution Monitoring and Alerting SyetemIRJET Journal
This document proposes an IOT-based system to monitor air and noise pollution levels in a particular region using sensors connected to a Raspberry Pi microcontroller. The sensors detect parameters like gas, humidity, and sound levels, and send the data via GSM module to the cloud for remote monitoring and analysis. The system also includes an alerting mechanism to notify users if pollution levels exceed certain thresholds.
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.
This document describes research using genetic programming (GP) and artificial neural networks (ANN) to develop short-term air quality forecast models for Pune, India. 36 models were developed using daily average meteorological and pollutant concentration data from 2005-2008 to predict concentrations of SOx, NOx, and particulate matter one day in advance. The models were designed to be robust in situations where complete input data is unavailable. Performance of the GP and ANN models was evaluated based on correlation, error, and other statistical measures. The research found that the GP models generally performed better than the ANN models, especially in cases with incomplete data, and had the advantage of generating equation-based forecasts.
IRJET- Aircop – An Air Pollution Monitoring DeviceIRJET Journal
1. The document describes a device called AIRCOP that was developed for remote monitoring of air pollution factors using Internet of Things technology.
2. AIRCOP monitors carbon monoxide, air quality, particulate matter, temperature, humidity, atmospheric pressure, and wind speed using low-cost sensors.
3. The sensor data is sent to a cloud-based IoT platform called Thingspeak where it is stored and visualized, allowing continuous monitoring of environmental conditions.
ANALYSIS AND DESIGN OF VYTILA’S WATCH TOWER INTO AIR PURIFICATION SYSTEMIRJET Journal
This document discusses a student project that aims to design Vytila's traffic watch tower in Kerala, India to also function as an air purification tower. It begins with an introduction on air pollution issues in India. The objectives are then outlined which include collecting air quality data, designing 3D models of the tower, and structuring the design. Next, the methodology, current air quality data from various sources, and emissions standards are presented. The document provides a detailed analysis of air pollution levels and causes in Kerala, with Thiruvananthapuram being the only city currently monitored. The goal of the project is to help address outdoor air pollution issues in the area through retrofitting the existing watch tower.
Review on Environment Monitoring System and Energy EfficiencyIJERA Editor
The Environment monitoring is one of the applications of wireless sensor network. The most serious environment pollution is air pollution because different air pollutant causes damage to human health and causes global warming. To avoid such effect on human health and climate change Environment monitoring systems are used. This paper provides the short overview of different environmental air pollution monitoring systems and Energy efficiency in WSN to reduced the power consumption of system.
Similar to IRJET - Prediction of Air Pollutant Concentration using Deep Learning (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.
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.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all