On assessing the accuracy of air pollution models exploiting a strategic sensors deployment

Rita Tse; Davide Aguiari; Lorenzo Monti; Giovanni Pau; Catia Prandi; Paola Salomoni

doi:10.1145/3284869.3284880

On assessing the accuracy of air pollution models exploiting a strategic sensors deployment

Rita Tse
, Davide Aguiari
, Lorenzo Monti
, Giovanni Pau
, Catia Prandi
, Paola Salomoni

Faculty of Applied Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

Abstract

This paper presents a preliminary experiment done to identify potential problems and issues in setting up a testbed for air pollution measurement and modeling. Our final testbed, part of a joint research activity between the University of Bologna and the Macao Polytechnic Institute, will be composed of three lines of the air pollution sensors Canarin II and it will be used to produce spatio-temporal open data to test third-party air pollution models. Here, we present a preliminary experiment based on a single line of sensors, showing interesting insights into the actual open challenge of air pollution modeling techniques validation, taking into account the effects of air pollutant emissions sources, meteorology, atmospheric concentrations and urban vegetation.

Original language	English
Title of host publication	Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (formerly GOODTECHS), GOODTECHS 2018
Publisher	Association for Computing Machinery
Pages	55-58
Number of pages	4
ISBN (Electronic)	9781450365819
DOIs	https://doi.org/10.1145/3284869.3284880
Publication status	Published - 28 Nov 2018
Event	4th EAI International Conference on Smart Objects and Technologies for Social Good, GOODTECHS 2018 - Bologna, Italy Duration: 28 Nov 2018 → 30 Nov 2018

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	4th EAI International Conference on Smart Objects and Technologies for Social Good, GOODTECHS 2018
Country/Territory	Italy
City	Bologna
Period	28/11/18 → 30/11/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Air pollution modeling
Air quality sensors
Open data
Sensors deployment

Access to Document

10.1145/3284869.3284880

Cite this

Tse, R., Aguiari, D., Monti, L., Pau, G., Prandi, C., & Salomoni, P. (2018). On assessing the accuracy of air pollution models exploiting a strategic sensors deployment. In Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (formerly GOODTECHS), GOODTECHS 2018 (pp. 55-58). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3284869.3284880

Tse, Rita ; Aguiari, Davide ; Monti, Lorenzo et al. / On assessing the accuracy of air pollution models exploiting a strategic sensors deployment. Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (formerly GOODTECHS), GOODTECHS 2018. Association for Computing Machinery, 2018. pp. 55-58 (ACM International Conference Proceeding Series).

@inproceedings{366af63d38ca4e909cb658a430916427,

title = "On assessing the accuracy of air pollution models exploiting a strategic sensors deployment",

abstract = "This paper presents a preliminary experiment done to identify potential problems and issues in setting up a testbed for air pollution measurement and modeling. Our final testbed, part of a joint research activity between the University of Bologna and the Macao Polytechnic Institute, will be composed of three lines of the air pollution sensors Canarin II and it will be used to produce spatio-temporal open data to test third-party air pollution models. Here, we present a preliminary experiment based on a single line of sensors, showing interesting insights into the actual open challenge of air pollution modeling techniques validation, taking into account the effects of air pollutant emissions sources, meteorology, atmospheric concentrations and urban vegetation.",

keywords = "Air pollution modeling, Air quality sensors, Open data, Sensors deployment",

author = "Rita Tse and Davide Aguiari and Lorenzo Monti and Giovanni Pau and Catia Prandi and Paola Salomoni",

note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 4th EAI International Conference on Smart Objects and Technologies for Social Good, GOODTECHS 2018 ; Conference date: 28-11-2018 Through 30-11-2018",

year = "2018",

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doi = "10.1145/3284869.3284880",

language = "English",

series = "ACM International Conference Proceeding Series",

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Tse, R, Aguiari, D, Monti, L, Pau, G, Prandi, C & Salomoni, P 2018, On assessing the accuracy of air pollution models exploiting a strategic sensors deployment. in Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (formerly GOODTECHS), GOODTECHS 2018. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 55-58, 4th EAI International Conference on Smart Objects and Technologies for Social Good, GOODTECHS 2018, Bologna, Italy, 28/11/18. https://doi.org/10.1145/3284869.3284880

On assessing the accuracy of air pollution models exploiting a strategic sensors deployment. / Tse, Rita; Aguiari, Davide; Monti, Lorenzo et al.
Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (formerly GOODTECHS), GOODTECHS 2018. Association for Computing Machinery, 2018. p. 55-58 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents a preliminary experiment done to identify potential problems and issues in setting up a testbed for air pollution measurement and modeling. Our final testbed, part of a joint research activity between the University of Bologna and the Macao Polytechnic Institute, will be composed of three lines of the air pollution sensors Canarin II and it will be used to produce spatio-temporal open data to test third-party air pollution models. Here, we present a preliminary experiment based on a single line of sensors, showing interesting insights into the actual open challenge of air pollution modeling techniques validation, taking into account the effects of air pollutant emissions sources, meteorology, atmospheric concentrations and urban vegetation.

KW - Air pollution modeling

KW - Air quality sensors

KW - Open data

KW - Sensors deployment

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BT - Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (formerly GOODTECHS), GOODTECHS 2018

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Tse R, Aguiari D, Monti L, Pau G, Prandi C, Salomoni P. On assessing the accuracy of air pollution models exploiting a strategic sensors deployment. In Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good (formerly GOODTECHS), GOODTECHS 2018. Association for Computing Machinery. 2018. p. 55-58. (ACM International Conference Proceeding Series). doi: 10.1145/3284869.3284880

On assessing the accuracy of air pollution models exploiting a strategic sensors deployment

Abstract

Publication series

Conference

UN SDGs

Keywords

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