CAVisAP: Context-Aware Visualization of Outdoor Air Pollution with IoT PlatformsShow others and affiliations
2019 (English)In: 2019 International Conference on High Performance Computing & Simulation (HPCS), IEEE, 2019, p. 84-91Conference paper, Published paper (Refereed)
Abstract [en]
Air pollution is a severe issue in many big cities due to population growth and the rapid development of the economy and industry. This leads to the proliferating need to monitor urban air quality to avoid personal exposure and to make savvy decisions on managing the environment. In the last decades, the Internet of Things (IoT) is increasingly being applied to environmental challenges, including air quality monitoring and visualization. In this paper, we present CAVisAP, a context-aware system for outdoor air pollution visualization with IoT platforms. The system aims to provide context-aware visualization of three air pollutants such as nitrogen dioxide (NO 2 ), ozone (O 3 ) and particulate matter (PM 2.5 ) in the city of Melbourne, Australia. In addition to the primary context as location and time, CAVisAP takes into account users’ pollutant sensitivity levels and color vision impairments to provide personalized pollution maps. Experiments are conducted to validate the system and results are discussed.
Place, publisher, year, edition, pages
IEEE, 2019. p. 84-91
Series
International Conference on High Performance Computing & Simulation (HPCS)
Keywords [en]
context-aware, location-based, data visualization, air pollution, Internet of Things, environmental monitoring
National Category
Computer and Information Sciences
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-80754DOI: 10.1109/HPCS48598.2019.9188167Scopus ID: 2-s2.0-85072975370OAI: oai:DiVA.org:ltu-80754DiVA, id: diva2:1466004
Conference
The 2019 International Conference on High Performance Computing & Simulation (HPCS 2019), 15-19 July, 2019, Dublin, Ireland
Note
ISBN för värdpublikation: 978-1-7281-4484-9, 978-1-7281-4485-6
2020-09-102020-09-102025-02-18Bibliographically approved