Mobile monitoring of air pollution using low cost sensors to visualize spatio-temporal variation of pollutants at urban hotspots

Sm, Shiva Nagendra; Yasa, Pavan Reddy; Narayana, M V; Khadirnaikar, Seema; Rani, Pooja

doi:10.1016/j.scs.2018.10.006

Cited by 79 publications

(42 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To further validate the choice of our PM-sensor (namely the NOVA PM SDS011), we carried out a small experiment at our University. We placed the sensor next to the more sophisticated OPC-N3 optical particle counter from Alphasense [34] (The latter's data quality has already been evaluated and validated in different studies [14,35,36]). Three measurement runs using both sensors were conducted.…”

Section: Sensor Node Evaluationmentioning

confidence: 99%

“…The sensors were deployed on bicycles going in loops on a predefined path in the city of Lubbock, Texas. The authors of [14] introduce the smart personal air quality monitoring system (SPAMS), which collects O 3 , NO 2 , CO, and PM 2.5 , temperature, and relative humidity, while on the move. They investigated the calibration and data validation before presenting some results of their measurement campaign in different spots of the city of Chennai, India.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

MoreAir: A Low-Cost Urban Air Pollution Monitoring System

Gryech

Ben-Aboud

Guermah

et al. 2020

Sensors

View full text Add to dashboard Cite

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.

show abstract

Section: Sensor Node Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MoreAir: A Low-Cost Urban Air Pollution Monitoring System

Gryech

Ben-Aboud

Guermah

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Real time trends, historical trends, alerts and reports are accessed by a user by using the web application. In future number of nodes can be increased, so user can monitor the air quality over a large area [2] and this system can be integrated with google weather or similar services so thatthe public caneasily access the air quality data.…”

Section: Discussionmentioning

confidence: 99%

Development of an IoT based Air Quality Monitoring System

2019

IJITEE

View full text Add to dashboard Cite

The proposed work aims for a large-scale air pollutant monitoring for ambient and indoor environments. This system is developed to measure various environmental parameters. Sourceof pollutants can be identified by analyzing the data collected from the various sensor nodes, so that air quality can be monitored by applying engineering science and data. This is achieved by installing multiple sensor stations in various locations such as hospitals, factories, Offices, streets and weather stations. These sensor stations measure the environmental parameters such as PM2.5, PM10, Sulphate (SOx), Nitrate (NOx), Ozone(O3), Volatile Organic Compounds (VOC), Temperature and Humidity. The sensor stations communicate with cloud over HTTP protocol. Each station has ESP 8266 smart controller which captures the sensor data and creates forms theJavaScript Object Notation (JSON) data packets that mainly consists of sensor data along with node address. These packets will be sent to the cloud over HTTP protocol. The user can access the air quality data from the web application.

show abstract

“…Irwin M. Hutten [5] proposed air filter applications to control air pollution. Shiva Nagendra et al [6] presented the Chennai city air quality monitoring system, the results indicated that the PM 2.5 absorption was the highest in busy traffic sites, and the higher concentrations of CO 2 , NO 2 , and O 3 were observed while traveling by bus in the morning, evening and afternoon. This result was obtained from different days in a week.…”

Section: Literature Reviewmentioning

confidence: 99%

A Distinctive Symmetric Analyzation of Improving Air Quality Using Multi-Criteria Decision Making Method under Uncertainty Conditions

et al. 2020

View full text Add to dashboard Cite

This world has a wide range of technologies and possibilities that are available to control air pollution. Still, finding the best solution to control the contamination of the air without having any impact on humans is a complicated task. This proposal helps to improve the air quality using the multi-criteria decision making method. The decision to improve air quality is a challenging problem with today’s technology and environmental development level. The multi-criteria decision making method is quite often faced with conditions of uncertainty, which can be tackled by employing fuzzy set theory. In this paper, based on an objective weighting method (CCSD), we explore the improved fuzzy MULTIMOORA approach. We use the classical Interval-Valued Triangular Fuzzy Numbers (IVTFNs), viz. the symmetric lower and upper triangular numbers, as the basis. The triangular fuzzy number is identified by the triplets; the lowest, the most promising, and the highest possible values, symmetric with respect to the most promising value. When the lower and upper membership functions are equated to one, we get the normalized interval-valued triangular fuzzy numbers, which consist of symmetric intervals. We evaluate five alternatives among the four criteria using an improved MULTIMOORA method and select the best method for improving air quality in Tamil Nadu, India. Finally, a numerical example is illustrated to show the efficiency of the proposed method.

show abstract

Mobile monitoring of air pollution using low cost sensors to visualize spatio-temporal variation of pollutants at urban hotspots

Cited by 79 publications

References 34 publications

MoreAir: A Low-Cost Urban Air Pollution Monitoring System

MoreAir: A Low-Cost Urban Air Pollution Monitoring System

Development of an IoT based Air Quality Monitoring System

A Distinctive Symmetric Analyzation of Improving Air Quality Using Multi-Criteria Decision Making Method under Uncertainty Conditions

Contact Info

Product

Resources

About