scholarly journals Intelligent Air Pollution Monitoring System for Smart Cities Using IoT and Machine Learning

2021 ◽  
Vol 10 (2) ◽  
pp. 1399-1407
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Smart Cities ◽  
Machine Learning Algorithms ◽  
Control Measures ◽  
Pollution Monitoring ◽  
World Health ◽  
Air Pollution Monitoring ◽  
Pollution Levels ◽  
The World

Today, almost everything is going under automation. Air pollution has become one of the major crises across the globe. According to the report of the World Health Organization (WHO), around 580,000 people died due to air pollution. This document deals with the effective monitoring of air pollution systems. The proposed technique uses machine learning algorithms for the intelligent monitoring of air pollution. The concept of the Internet of Things (IoT) is implemented in the system to make it more reliable and accessible from anywhere throughout the world. ESP32 is used as a microprocessor for decision making purposes. The system uses Arduino software to build an algorithm. The DHT11 module is used to sense the humidity as well as temperature. MQ-2, MQ-7 and MQ-135 are used for sensing the level of methane, carbon monoxide and for measuring air quality, respectively. A buzzer is used to identify any unusual condition. Our work considers pollution caused by vehicles and provides an in-the-moment solution that does not directly monitor pollution levels, as well as control measures for reducing traffic in extremely polluted areas. This system will undoubtedly be on humans' behalf in such a way that a smart city will have much less time for spending, and there will undoubtedly be other industries, and the air will undoubtedly be extra polluted, and this device will undoubtedlyallow people to understand how safe the air is.

Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study

2021 ◽  
Author(s):  
Paul D Rosero-Montalvo ◽  
Vivian F López-Batista ◽  
Ricardo Arciniega-Rocha ◽  
Diego H Peluffo-Ordóñez
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Classification Performance ◽  
Pollution Monitoring ◽  
Machine Learning Techniques ◽  
Related Factors ◽  
Air Pollution Monitoring ◽  
Pollution Levels ◽  
Learning Techniques ◽  
High Pollution

Abstract Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.

Design and Improvement of Air Pollution Monitoring System based on IoT Network for Smart Cities

2020 ◽  
Vol 48 (1) ◽  
pp. 03-04
Author(s):  
Yvon Blanchard
Keyword(s):  
Air Pollution ◽  
Urban Communities ◽  
Monitoring System ◽  
Smart Cities ◽  
Physical World ◽  
Pollution Monitoring ◽  
Dynamic Capacity ◽  
Air Pollution Monitoring ◽  
Ecological Boundary

Ecological boundary observing has become significant worry in present day megalopolis because of transformation and progression. Presently, air pollution is a major issue for individual’s wellbeing in urban communities that experienced the more feature, for example, the traffic, modern, or backwoods fire or contaminated skies. The planned framework utilizes IOT which gives an affordable and a viable framework to screen air effluence level specifically territory. IOT engages tremendous extent of elements and physical world subtleties. For offer intriguing administrations, to trade and impart data, IOT installs availability with dynamic capacity among gadgets can be utilized. The methodology of framework characterizes a modified structure of IOT pedestal checking gadgets which decide the degrees of poisonous in gaspresent over air.

Web-Based Machine Learning Application for Heart Disease Prediction

2022 ◽  
pp. 383-393
Author(s):  
Lokesh M. Giripunje ◽  
Tejas Prashant Sonar ◽  
Rohit Shivaji Mali ◽  
Jayant C. Modhave ◽  
Mahesh B. Gaikwad
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Random Forest ◽  
Web Application ◽  
Machine Learning Algorithms ◽  
World Health ◽  
Web Based ◽  
The World ◽  
Comprehensive Survey ◽  
Health Organization

Risk because of heart disease is increasing throughout the world. According to the World Health Organization report, the number of deaths because of heart disease is drastically increasing as compared to other diseases. Multiple factors are responsible for causing heart-related issues. Many approaches were suggested for prediction of heart disease, but none of them were satisfactory in clinical terms. Heart disease therapies and operations available are so costly, and following treatment, heart disease is also costly. This chapter provides a comprehensive survey of existing machine learning algorithms and presents comparison in terms of accuracy, and the authors have found that the random forest classifier is the most accurate model; hence, they are using random forest for further processes. Deployment of machine learning model using web application was done with the help of flask, HTML, GitHub, and Heroku servers. Webpages take input attributes from the users and gives the output regarding the patient heart condition with accuracy of having coronary heart disease in the next 10 years.

scholarly journals Visual Data Analysis and Simulation Prediction for COVID-19 in Saudi Arabia Using SEIR Prediction Model

2021 ◽  
Vol 17 (08) ◽  
pp. 154
Author(s):  
Shakir Khan
Keyword(s):  
Machine Learning ◽  
Saudi Arabia ◽  
Prediction Models ◽  
Preventive Measures ◽  
Future Trend ◽  
Control Measures ◽  
World Health ◽  
Seir Model ◽  
The World ◽  
Health Organization

<p>The World Health Organization (WHO) reported the COVID-19 epidemic a global health emergency on January 30 and confirmed its transformation into a pandemic on March 11. China has been the hardest hit since the virus's outbreak, which may date back to late November. Saudi Arabia realized the danger of the Coronavirus in March 2020, took the initiative to take a set of pre-emptive decisions that preceded many countries of the world, and worked to harness all capabilities to confront the outbreak of the epidemic. Several researchers are currently using various mathematical and machine learning-based prediction models to estimate this pandemic's future trend. In this work, the SEIR model was applied to predict the epidemic situation in Saudi Arabia and evaluate the effectiveness of some epidemic control measures, and finally, providing some advice on preventive measures.</p>

scholarly journals Research on an Iot Based Air Pollution Monitoring System

2019 ◽  
Vol 8 (9S2) ◽  
pp. 553-558
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Life Forms ◽  
Pollution Monitoring ◽  
Wireless Sensor ◽  
Pollution Level ◽  
Air Pollution Monitoring ◽  
Pollution Levels ◽  
Different Sources

Humankind, moving to a period centered upon improvement has overlooked the significance of supportability and has been the real guilty party behind the rising Pollution levels in the world's air among all other living life forms. The Pollution levels at certain spots have come to such high degrees that they have begun hurting our very own It will being. An IoT based Air Pollution observing framework incorporates a MQ Series sensor interfaced to a Node MCU outfitted with an ESP8266 WLAN connector to send the sensor perusing to a Thing Speak cloud. Further extent of this work incorporates an appropriate AI model to foresee the air Pollution level and an anticipating model, which is fundamentally a subset of prescient displaying. As age of poisonous gases from ventures, vehicles and different sources is immensely expanding step by step, it winds up hard to control the dangerous gases from dirtying the unadulterated air. In this paper a practical air Pollution observing framework is proposed. This framework can be utilized for observing Pollutions in demeanor of specific territory and to discover the air peculiarity or property examination. The obligated framework will concentrate on the checking of air poisons concentrate with the assistance of mix of Internet of things with wireless sensor systems. The investigation of air quality should be possible by figuring air quality index (AQI)

Air Pollution Monitoring Using WSN in Cement Factory

2018 ◽  
Vol 15 (2) ◽  
pp. 616-620 ◽  
Author(s):  
G. Anitha ◽  
V. Vijayakumari ◽  
S. Malathy ◽  
S. Jaipriya
Keyword(s):  
Air Pollution ◽  
Human Population ◽  
Industrial Revolution ◽  
Sensor Nodes ◽  
Pollution Monitoring ◽  
Wireless Sensor ◽  
Air Pollution Monitoring ◽  
The World ◽  
Pollutant Level ◽  
Cement Factories

Industrial revolution has started to rule the world in all aspects. As a result of this, pollutant level of contagious gas in the atmosphere is increasing at an alarming rate. The pollutants in the atmosphere create imbalance in ecosystem which in turn affects the health of human population. Although there existmany methodologies to check the pollutant level in atmosphere, it still remains a challenge for certain cement factories and chemical industries to keep a check on it. Such imbalances can be controlled by using appropriate air pollution monitoring system. OPSIS, Uras26, Magnos27 and CODEL are the methods which exist in cement factories to check the pollutant level during the emission from chimney only. Wireless Sensor Network is a versatile technology that can sense, monitor, measure, and gather information. The decision can be made from the collected information. This paper proposes how sensor nodes are deployed in cement factories at various stages of manufacturing process, how the pollutant is measured and conveyed to authority through a communication medium.

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