Back to Search Start Over

An Open Framework for Participatory PM2.5 Monitoring in Smart Cities

Authors :
Ling-Jyh Chen
Yao-Hua Ho
Hu-Cheng Lee
Hsuan-Cho Wu
Hao-Min Liu
Hsin-Hung Hsieh
Yu-Te Huang
Shih-Chun Candice Lung
Source :
IEEE Access, Vol 5, Pp 14441-14454 (2017)
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

As the population in cities continues to increase rapidly, air pollution becomes a serious issue from public health to social economy. Among all pollutants, fine particulate matters (PM2.5) directly related to various serious health concerns, e.g., lung cancer, premature death, asthma, and cardiovascular and respiratory diseases. To enhance the quality of urban living, sensors are deployed to create smart cities. In this paper, we present a participatory urban sensing framework for PM2.5 monitoring with more than 2500 devices deployed in Taiwan and 29 other countries. It is one of the largest deployment project for PM2.5 monitor in the world as we know until May 2017. The key feature of the framework is its open system architecture, which is based on the principles of open hardware, open source software, and open data. To facilitate the deployment of the framework, we investigate the accuracy issue of low-cost particle sensors with a comprehensive set of comparison evaluations to identify the most reliable sensor. By working closely with government authorities, industry partners, and maker communities, we can construct an effective eco-system for participatory urban sensing of PM2.5 particles. Based on our deployment achievements to date, we provide a number of data services to improve environmental awareness, trigger on-demand responses, and assist future government policymaking. The proposed framework is highly scalable and sustainable with the potential to facilitate the Internet of Things, smart cities, and citizen science in the future.

Details

Language :
English
ISSN :
21693536
Volume :
5
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.1c40948904323a42c6e60aa4f5f36
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2017.2723919