Monitoring and analyzing air quality is of primary importance to encourage more sustainable lifestyles and plan corrective actions. This paper presents the design and end-To-end implementation1 of a real-world urban air quality data collection and analytics use case which is a part of the TRAFAIR (Understanding Traffic Flows to Improve Air Quality) European project [1, 2]. This implementation is related to the project work done in Modena city, Italy, starting from distributed low-cost multi-sensor IoT devices installation, LoRa network setup, data collection at LoRa server database, ML-based anomaly measurement detection plus cleaning, sensor calibration, central control and visualization using designed SenseBoard [3].
Air Quality Sensor Network Data Acquisition, Cleaning, Visualization, and Analytics: A Real-world IoT Use Case / Rollo, Federica; Sudharsan, Bharath; Po, Laura; Breslin, John. - (2021), pp. 67-68. (Intervento presentato al convegno 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2021 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2021 tenutosi a Virtual, USA nel September 21--26, 2021) [10.1145/3460418.3479277].
Air Quality Sensor Network Data Acquisition, Cleaning, Visualization, and Analytics: A Real-world IoT Use Case
Federica Rollo;Laura Po;
2021
Abstract
Monitoring and analyzing air quality is of primary importance to encourage more sustainable lifestyles and plan corrective actions. This paper presents the design and end-To-end implementation1 of a real-world urban air quality data collection and analytics use case which is a part of the TRAFAIR (Understanding Traffic Flows to Improve Air Quality) European project [1, 2]. This implementation is related to the project work done in Modena city, Italy, starting from distributed low-cost multi-sensor IoT devices installation, LoRa network setup, data collection at LoRa server database, ML-based anomaly measurement detection plus cleaning, sensor calibration, central control and visualization using designed SenseBoard [3].File | Dimensione | Formato | |
---|---|---|---|
AIr_quality_IoT_analytics_poster.pptx
Open access
Tipologia:
Altro
Dimensione
10.03 MB
Formato
Microsoft Powerpoint XML
|
10.03 MB | Microsoft Powerpoint XML | Visualizza/Apri |
Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris