Publication Type

Journal Article

Version

publishedVersion

Publication Date

8-2018

Abstract

For the health and safety of the public, it is essential to measure spatiotemporal distribution of air pollution in a region and thus monitor air quality in a fine-grain manner. While most of the sensing-based commercial applications available until today have been using fixed environmental sensors, the use of personal devices such as smartphones, smartwatches, and other wearable devices has not been explored in depth. These kinds of devices have an advantage of being with the user continuously, thus providing an ability to generate accurate and well-distributed spatiotemporal air pollution data. In this paper, we review the studies (especially in the last decade) done by various researchers using different kinds of environmental sensors highlighting related techniques and issues. We also present important studies of measuring impact and emission of air pollution on human beings and also discuss models using which air pollution inhalation can be associated to humans by quantifying personal exposure with the use of human activity detection. The overarching aim of this review is to provide novel and key ideas that have the potential to drive pervasive and individual centric and yet accurate pollution monitoring techniques which can scale up to the future needs.

Keywords

Crowdsensing, activity recognition, sensing, air pollution maps, smart environments, ubiquitous sensing, mobile sensing, air pollution monitoring, exposure estimation

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Areas of Excellence

Digital transformation

Publication

Environmental Monitoring and Assessment

Volume

190

Issue

9

First Page

1

Last Page

21

ISSN

0167-6369

Identifier

10.1007/s10661-018-6940-8

Publisher

Springer

Additional URL

https://doi.org/10.1007/s10661-018-6940-8

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