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Crowdsensing Air Quality with Camera-enabled Mobile Devices


Authors: Z. Pan, H. Yu, C. Miao, and C. Leung
Title: Crowdsensing Air Quality with Camera-enabled Mobile Devices
Abstract: Crowdsensing of air quality is a useful way to improve public awareness and supplement local air quality monitoring data. However, current air quality monitoring approaches are either too sophisticated, costly or bulky to be used effectively by the mass. In this paper, we describe AirTick, a mobile app that can turn any camera enabled smart mobile device into an air quality sensor, thereby enabling crowdsensing of air quality. AirTick leverages image analytics and deep learning techniques to produce accurate estimates of air quality following the Pollutant Standards Index (PSI). We report the results of an initial experimental and empirical evaluations of AirTick. The AirTick tool has been shown to achieve, on average, 87% accuracy in day time operation and 75% accuracy in night time operation. Feedbacks from 100 test users indicate that they perceive AirTick to be highly useful and easy to use. Our results provide a strong positive case for the benefits of applying artificial intelligence techniques for convenient and scalable crowdsensing of air quality.
Keywords: 
Conference Name: 29th Conference on Innovative Applications of Artificial Intelligence (IAAI'17)
Location: San Francisco, USA
Publisher: AAAI
Year: 2017
Accepted PDF File: Crowdsensing_Air_Quality_with_Camera-enabled_Mobile_Devices_accepted.pdf
Permanent Link: http://aaai.org/ocs/index.php/IAAI/IAAI17/paper/view/14171
Reference: Z. Pan, H. Yu, C. Miao, and C. Leung, “Crowdsensing air quality with camera-enabled mobile devices,” in Proceedings of the 29th Conference on Innovative Applications of Artificial Intelligence (IAAI’17). AAAI, February 2017, pp. 4728–4733.
bibtex: 
@inproceedings{LILY-c110, 
    author	= {Pan, Zhengxiang and Yu, Han and Miao, Chunyan and Leung, Cyril},
    title	= {Crowdsensing Air Quality with Camera-enabled Mobile Devices},  
    booktitle	= {Proceedings of the 29th Conference on Innovative Applications of Artificial Intelligence (IAAI'17)}, 
    year		= {2017}, 
    month	= {February}, 
    pages	= {4728-4733}, 
    location	= {San Francisco, USA},
    publisher	= {AAAI},
 }