Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors
Conventional air quality monitoring has been traditionally carried out in a few fixed places with expensive measuring equipment. This results in sparse spatial air quality data, which do not represent the real air quality of an entire area, e.g., when hot spots are missing. To obtain air quality dat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/3/945 |
| _version_ | 1797318161920425984 |
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| author | Abdul Samad Joschka Kieser Ioannis Chourdakis Ulrich Vogt |
| author_facet | Abdul Samad Joschka Kieser Ioannis Chourdakis Ulrich Vogt |
| author_sort | Abdul Samad |
| collection | DOAJ |
| description | Conventional air quality monitoring has been traditionally carried out in a few fixed places with expensive measuring equipment. This results in sparse spatial air quality data, which do not represent the real air quality of an entire area, e.g., when hot spots are missing. To obtain air quality data with higher spatial and temporal resolution, this research focused on developing a low-cost network of cloud-based air quality measurement platforms. These platforms should be able to measure air quality parameters including particulate matter (PM10, PM2.5, PM1) as well as gases like NO, NO<sub>2</sub>, O<sub>3</sub>, and CO, air temperature, and relative humidity. These parameters were measured every second and transmitted to a cloud server every minute on average. The platform developed during this research used one main computer to read the sensor data, process it, and store it in the cloud. Three prototypes were tested in the field: two of them at a busy traffic site in Stuttgart, Marienplatz and one at a remote site, Ötisheim, where measurements were performed near busy railroad tracks. The developed platform had around 1500 € in materials costs for one Air Quality Sensor Node and proved to be robust during the measurement phase. The notion of employing a Proportional–Integral–Derivative (PID) controller for the efficient working of a dryer that is used to reduce the negative effect of meteorological parameters such as air temperature and relative humidity on the measurement results was also pursued. This is seen as one way to improve the quality of data captured by low-cost sensors. |
| first_indexed | 2024-03-08T03:48:29Z |
| format | Article |
| id | doaj.art-0f0f9088f2884f4e9c3a84e1ec309a12 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T03:48:29Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0f0f9088f2884f4e9c3a84e1ec309a122024-02-09T15:22:21ZengMDPI AGSensors1424-82202024-02-0124394510.3390/s24030945Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost SensorsAbdul Samad0Joschka Kieser1Ioannis Chourdakis2Ulrich Vogt3Institute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, GermanyInstitute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, GermanyInstitute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, GermanyInstitute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, GermanyConventional air quality monitoring has been traditionally carried out in a few fixed places with expensive measuring equipment. This results in sparse spatial air quality data, which do not represent the real air quality of an entire area, e.g., when hot spots are missing. To obtain air quality data with higher spatial and temporal resolution, this research focused on developing a low-cost network of cloud-based air quality measurement platforms. These platforms should be able to measure air quality parameters including particulate matter (PM10, PM2.5, PM1) as well as gases like NO, NO<sub>2</sub>, O<sub>3</sub>, and CO, air temperature, and relative humidity. These parameters were measured every second and transmitted to a cloud server every minute on average. The platform developed during this research used one main computer to read the sensor data, process it, and store it in the cloud. Three prototypes were tested in the field: two of them at a busy traffic site in Stuttgart, Marienplatz and one at a remote site, Ötisheim, where measurements were performed near busy railroad tracks. The developed platform had around 1500 € in materials costs for one Air Quality Sensor Node and proved to be robust during the measurement phase. The notion of employing a Proportional–Integral–Derivative (PID) controller for the efficient working of a dryer that is used to reduce the negative effect of meteorological parameters such as air temperature and relative humidity on the measurement results was also pursued. This is seen as one way to improve the quality of data captured by low-cost sensors.https://www.mdpi.com/1424-8220/24/3/945low-cost sensorsgas sensorsPM sensorsair quality sensorselectrochemical low-cost sensorsair pollutants |
| spellingShingle | Abdul Samad Joschka Kieser Ioannis Chourdakis Ulrich Vogt Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors Sensors low-cost sensors gas sensors PM sensors air quality sensors electrochemical low-cost sensors air pollutants |
| title | Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors |
| title_full | Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors |
| title_fullStr | Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors |
| title_full_unstemmed | Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors |
| title_short | Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors |
| title_sort | developing a cloud based air quality monitoring platform using low cost sensors |
| topic | low-cost sensors gas sensors PM sensors air quality sensors electrochemical low-cost sensors air pollutants |
| url | https://www.mdpi.com/1424-8220/24/3/945 |
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