2026-04-29T05:37:41Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/142992025-05-12T09:28:02Zcom_20.500.12105_2052com_20.500.12105_2051col_20.500.12105_19610
Repisalud
author
Novak, Rok
author
Petridis, Ioannis
author
Kocman, David
author
Robinson, Johanna Amalia
author
Kanduč, Tjaša
author
Chapizanis, Dimitris
author
Karakitsios, Spyros
author
Flückiger, Benjamin
author
Vienneau, Danielle
author
Mikeš, Ondřej
author
Degrendele, Céline
author
Sáňka, Ondřej
author
Garcia Dos Santos-Alves, Saul
author
Maggos, Thomas
author
Pardali, Demetra
author
Stamatelopoulou, Asimina
author
Saraga, Dikaia
author
Persico, Marco Giovanni
author
Visave, Jaideep
author
Gotti, Alberto
author
Sarigiannis, Dimosthenis
funder
Unión Europea. Comisión Europea. H2020
funder
Slovenian Research Agency
funder
Ministry of Education, Youth and Sports (República Checa)
2022-05-06T10:15:10Z
2022-05-06T10:15:10Z
2021-11-04
Int J Environ Res Public Health. 2021 Nov 4;18(21):11614.
http://hdl.handle.net/20.500.12105/14299
34770131
10.3390/ijerph182111614
1660-4601
International Journal of Environmental Research and Public Health
Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended.
eng
Air quality
Data fusion
Data treatment
Data visualization
Exposure assessment
Multi-sensor
Participant reports
Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign
research article
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