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
Typ výsledku
Článek v odborném periodiku
Stát vydavatele
Švýcarsko
Utajení
není předmětem státního či obchodního tajemství
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14310/21:00124127
Organizace
Přírodovědecká fakulta – Masarykova univerzita – Repozitář
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.
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.
Zobrazeno: 3. 5. 2026 09:51