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CAVisAP: Context-Aware Visualization of Outdoor Air Pollution with IoT Platforms

EasyChair Preprint no. 942

9 pagesDate: April 28, 2019


Recently air pollution became a severe issue in many big cities due to population growth and rapid development of economy and industry. This led to proliferating need to monitor urban air quality in order to avoid personal exposure as well as to make savvy decisions on managing the environment. In the last decades 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 (NO2), ozone (O3) and particulate matter (PM2.5) in the city of Melbourne, Australia. In addition to 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.

Keyphrases: air pollution, context-aware, data visualization, environmental monitoring, Internet of Things, location-based

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Meruyert Nurgazy and Arkady Zaslavsky and Prem Prakash Jayaraman and Sylvain Kubler and Karan Mitra and Saguna Saguna},
  title = {CAVisAP: Context-Aware Visualization of Outdoor Air Pollution with IoT Platforms},
  howpublished = {EasyChair Preprint no. 942},
  doi = {10.29007/9ld4},
  year = {EasyChair, 2019}}
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