Zigbee Based Wireless Air Pollution Monitoring System Using Low Cost and Energy Efficient Sensors

2014 ◽  
Vol 10 (9) ◽  
pp. 456-460 ◽  
Author(s):  
Mr.Vasim K. Ustad ◽  
◽  
Prof.A.S. Mali ◽  
Mr.Suhas S.Kibile
Keyword(s):  
Air Pollution ◽  
Monitoring System ◽  
Energy Efficient ◽  
Low Cost ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring

scholarly journals Geolocation based air pollution mobile monitoring system

2021 ◽  
Vol 23 (1) ◽  
pp. 162
Author(s):  
Aya Mazin Talib ◽  
Mahdi Nsaif Jasim
Keyword(s):  
Air Pollution ◽  
Monitoring System ◽  
Low Cost ◽  
Solid Particles ◽  
Pollution Monitoring ◽  
Liquid Droplets ◽  
Air Pollution Monitoring ◽  
Governmental Organizations ◽  
Data Mining Algorithms ◽  
Tree Classifier

Air pollution is conducted to harmful substances like solid particles, gases or liquid droplets. More pollutants CO, SO2, NOx, CO2.This research is proposed the design and implementation of mobile, low cost and accurate air pollution monitoring system using Arduino microcontroller and gas sensor like MQ2, MQ131, MQ135, MQ136, DHT22, measuring materials mentioned above, smoke, Acetone, Alcohol, LPG, Toluene, temperature, humidity and GPS sensor”NEO-6M” that track the location of air pollution data, and display the analysis result on ESRI maps. The system also save the results on SQL server DB. The data is classified using data mining algorithms, presenting the result on a map helps governmental organizations, nature guards, and ecologists to analyze data in real time to simplify the decision making process. The proposed system uses J48 pruning tree classifier generated using cross validation of fold (10) with highest accuracy 100%, while IBK ≈99.67, Naïve bays ≈90.89, and SVM ≈81.4. It’s found that the common air quality for Baghdad (study area) is between (“Good”, “Satisfactory”, and “Moderately”) for 1835 records of air samples during (January and February 2021) time period.

scholarly journals Low-cost air pollution monitoring system—an opportunity for reducing the health risk associated with physical activity in polluted air

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10041
Author(s):  
Zenon Nieckarz ◽  
Jerzy A. Zoladz
Keyword(s):  
Physical Activity ◽  
Air Pollution ◽  
Air Quality ◽  
Monitoring System ◽  
Low Cost ◽  
Time Of Day ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring ◽  
Identical Construction ◽  
The City

The issue of air pollution by particulate matter (PM) concerns many places in the world. At the same time, many residents undertake physical activity (recreation, rehabilitation, sport) in the open air. Generally, the amount of dust concentration depends on both the place (center or periphery of the city) and the time of day. In the present study we describe the outcome of monitoring of the state of air pollution by particle matter (PM10) in the Kraków agglomeration area in order to show that it can provide information concerning air quality in the area where people practice varied kinds of sports in the open air. The measurements of PM10 have been made by a few stations with identical construction working as one network. The details of the air pollution monitoring system and its data quality verification have been described. The network stations made multipoint observations across the Kraków Metropolitan Area during the year 2017 in eight locations. The locations selected represent a diverse spectrum of terrain conditions in which the Kraków agglomeration community undertakes physical activity. For most months of 2017, the minimum monthly average 4-hour PM10 concentrations were recorded between 10–14 h, regardless of location, whereas the maximum was between 18–22. We also noticed a huge differences in the average monthly value of PM10 in some locations within the Kraków agglomeration—ranging between 4.9–339.0 µg m−3. This indicates that some regions of the city are more suitable for performance of physical activity in the open air than others. In conclusion, we postulate that a low-cost air pollution monitoring system is capable of providing valuable information concerning air quality in a given region, which seems to be of importance also to people who practice varied sports activities in the open air.

scholarly journals MoreAir: A Low-Cost Urban Air Pollution Monitoring System

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 998 ◽  
Author(s):  
Ihsane Gryech ◽  
Yassine Ben-Aboud ◽  
Bassma Guermah ◽  
Nada Sbihi ◽  
Mounir Ghogho ◽  
...  
Keyword(s):  
Air Pollution ◽  
Monitoring System ◽  
Urban Areas ◽  
Low Cost ◽  
Urban Air Pollution ◽  
Pollution Monitoring ◽  
Geographical Information ◽  
Urban Air ◽  
Air Pollution Monitoring ◽  
Deployment Strategy

MoreAir is a low-cost and agile urban air pollution monitoring system. This paper describes the methodology used in the development of this system along with some preliminary data analysis results. A key feature of MoreAir is its innovative sensor deployment strategy which is based on mobile and nomadic sensors as well as on medical data collected at a children’s hospital, used to identify urban areas of high prevalence of respiratory diseases. Another key feature is the use of machine learning to perform prediction. In this paper, Moroccan cities are taken as case studies. Using the agile deployment strategy of MoreAir, it is shown that in many Moroccan neighborhoods, road traffic has a smaller impact on the concentrations of particulate matters (PM) than other sources, such as public baths, public ovens, open-air street food vendors and thrift shops. A geographical information system has been developed to provide real-time information to the citizens about the air quality in different neighborhoods and thus raise awareness about urban pollution.

scholarly journals H2020 project CAPTOR dataset: raw data collected by low-cost MOX ozone sensors in a real air pollution monitoring network.

Data in Brief ◽  
2021 ◽  
pp. 107127
Author(s):  
Jose M. Barcelo-Ordinas ◽  
Pau Ferrer-Cid ◽  
Jorge Garcia-Vidal ◽  
Mar Viana ◽  
Ana Ripoll
Keyword(s):  
Air Pollution ◽  
Low Cost ◽  
Monitoring Network ◽  
Pollution Monitoring ◽  
Raw Data ◽  
Air Pollution Monitoring

IoT Enabled an Open Framework for Air Pollution Monitoring System

2020 ◽  
Author(s):  
B.H. Sudantha ◽  
Manchanayaka MALSK ◽  
Nilantha Premakumara ◽  
Chamani Shiranthika ◽  
C. Premachandra ◽  
...  
Keyword(s):  
Air Pollution ◽  
Monitoring System ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring ◽  
Open Framework
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