Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing
Because the number of air quality measurement stations governed by a public authority is limited, many methodologies have been developed in order to integrate low-cost sensors and to improve the spatial density of air quality measurements. However, at the large-scale level, the integration of a huge...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/3/1026 |
| _version_ | 1827658712812093440 |
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| author | Ivan Popović Ilija Radovanovic Ivan Vajs Dejan Drajic Nenad Gligorić |
| author_facet | Ivan Popović Ilija Radovanovic Ivan Vajs Dejan Drajic Nenad Gligorić |
| author_sort | Ivan Popović |
| collection | DOAJ |
| description | Because the number of air quality measurement stations governed by a public authority is limited, many methodologies have been developed in order to integrate low-cost sensors and to improve the spatial density of air quality measurements. However, at the large-scale level, the integration of a huge number of sensors brings many challenges. The volume, velocity and processing requirements regarding the management of the sensor life cycle and the operation of system services overcome the capabilities of the centralized cloud model. In this paper, we present the methodology and the architectural framework for building large-scale sensing infrastructure for air quality monitoring applicable in urban scenarios. The proposed tiered architectural solution based on the adopted fog computing model is capable of handling the processing requirements of a large-scale application, while at the same time sustaining real-time performance. Furthermore, the proposed methodology introduces the collection of methods for the management of edge-tier node operation through different phases of the node life cycle, including the methods for node commission, provision, fault detection and recovery. The related sensor-side processing is encapsulated in the form of microservices that reside on the different tiers of system architecture. The operation of system microservices and their collaboration was verified through the presented experimental case study. |
| first_indexed | 2024-03-09T23:08:30Z |
| format | Article |
| id | doaj.art-15d646a8dd0543b6bc540081d4a8f01a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T23:08:30Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-15d646a8dd0543b6bc540081d4a8f01a2023-11-23T17:49:22ZengMDPI AGSensors1424-82202022-01-01223102610.3390/s22031026Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog ComputingIvan Popović0Ilija Radovanovic1Ivan Vajs2Dejan Drajic3Nenad Gligorić4University of Belgrade, School of Electrical Engineering, Bulevar Kralja Aleksandra 73, 11120 Belgrade, SerbiaUniversity of Belgrade, School of Electrical Engineering, Bulevar Kralja Aleksandra 73, 11120 Belgrade, SerbiaUniversity of Belgrade, School of Electrical Engineering, Bulevar Kralja Aleksandra 73, 11120 Belgrade, SerbiaUniversity of Belgrade, School of Electrical Engineering, Bulevar Kralja Aleksandra 73, 11120 Belgrade, SerbiaDunavNET, DNET Labs, Bulevar Oslobodjenja 133, 21000 Novi Sad, SerbiaBecause the number of air quality measurement stations governed by a public authority is limited, many methodologies have been developed in order to integrate low-cost sensors and to improve the spatial density of air quality measurements. However, at the large-scale level, the integration of a huge number of sensors brings many challenges. The volume, velocity and processing requirements regarding the management of the sensor life cycle and the operation of system services overcome the capabilities of the centralized cloud model. In this paper, we present the methodology and the architectural framework for building large-scale sensing infrastructure for air quality monitoring applicable in urban scenarios. The proposed tiered architectural solution based on the adopted fog computing model is capable of handling the processing requirements of a large-scale application, while at the same time sustaining real-time performance. Furthermore, the proposed methodology introduces the collection of methods for the management of edge-tier node operation through different phases of the node life cycle, including the methods for node commission, provision, fault detection and recovery. The related sensor-side processing is encapsulated in the form of microservices that reside on the different tiers of system architecture. The operation of system microservices and their collaboration was verified through the presented experimental case study.https://www.mdpi.com/1424-8220/22/3/1026air qualityfog computingsensor faultmicroservicesmanagement life cycle |
| spellingShingle | Ivan Popović Ilija Radovanovic Ivan Vajs Dejan Drajic Nenad Gligorić Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing Sensors air quality fog computing sensor fault microservices management life cycle |
| title | Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing |
| title_full | Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing |
| title_fullStr | Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing |
| title_full_unstemmed | Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing |
| title_short | Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing |
| title_sort | building low cost sensing infrastructure for air quality monitoring in urban areas based on fog computing |
| topic | air quality fog computing sensor fault microservices management life cycle |
| url | https://www.mdpi.com/1424-8220/22/3/1026 |
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