J 2021

Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign

NOVAK, Rok; Ioannis PETRIDIS; David KOCMAN; Johanna Amalia ROBINSON; Tjasa KANDUC et al.

Základní údaje

Originální název

Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign

Autoři

NOVAK, Rok; Ioannis PETRIDIS; David KOCMAN; Johanna Amalia ROBINSON; Tjasa KANDUC; Dimitris CHAPIZANIS; Spyros KARAKITSIOS; Benjamin FLUCKIGER; Danielle VIENNEAU; Ondřej MIKEŠ; Céline DEGRENDELE; Ondřej SÁŇKA; Saul Garcia DOS SANTOS-ALVES; Thomas MAGGOS; Demetra PARDALI; Asimina STAMATELOPOULOU; Dikaia SARAGA; Marco Giovanni PERSICO; Jaideep VISAVE; Alberto GOTTI a Dimosthenis SARIGIANNIS

Vydání

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, BASEL, MDPI AG, 2021, 1660-4601

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14310/21:00124127

Organizace

Přírodovědecká fakulta – Masarykova univerzita – Repozitář

EID Scopus

Klíčová slova anglicky

data fusion; multi-sensor; data visualization; data treatment; participant reports; air quality; exposure assessment

Návaznosti

CZ.02.1.01/0.0/0.0/16_013/0001315, interní kód Repo. EF16_013/0001761, projekt VaV. EF17_043/0009632, projekt VaV. 690105, interní kód Repo. 857560, interní kód Repo. RECETOX RI, velká výzkumná infrastruktura. ACTRIS-CZ II, velká výzkumná infrastruktura.
Změněno: 9. 6. 2025 00:50, RNDr. Daniel Jakubík

Anotace

V originále

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.

Přiložené soubory