@inproceedings{cc6e40f2ed484cd3aad15a73ab7a6b59,
title = "Wireless sensing system for prediction indoor air quality",
abstract = "In recent years, increased awareness of health issues and environmental protection, and the introduction of regulations regarding air quality, have created a demand for air quality monitoring technology. By combining wireless sensing technology and the ARIMA prediction model, an intelligent air quality monitoring system was constructed, which uses the ARIMA model to predict the carbon dioxide trend, thus providing capabilities beyond just monitoring. Experimental results show advantages of the proposed system; the prediction model, when historical data was collected at fifty-minute intervals, had a maximum error rate of 7.18% and a minimum error rate of 0.06%, showing promise for predicting future trends.",
keywords = "ARIMA, Indoor Air Quality, Prediction, Wireless sensor networks",
author = "Yu, {Tsang Chu} and Lin, {Chung Chih} and Lee, {Ren Guey} and Tseng, {Chao Heng} and Liu, {Shi Ping}",
year = "2012",
doi = "10.1109/HSIC.2012.6213022",
language = "英语",
isbn = "9781467306751",
series = "2012 4th International High Speed Intelligent Communication Forum, HSIC 2012, Proceeding",
pages = "103--105",
booktitle = "2012 4th International High Speed Intelligent Communication Forum, HSIC 2012, Proceeding",
note = "2012 4th International High Speed Intelligent Communication Forum, HSIC 2012 ; Conference date: 10-05-2012 Through 11-05-2012",
}