A machine learning based PM2.5 forecasting framework using internet of environmental things

Sachit Mahajan, Hao Min Liu, Ling-Jyh Chen, Tzu Chieh Tsai

研究成果: 書貢獻/報告類型會議貢獻

摘要

Information and communication technologies have been widely used to achieve the objective of smart city development. A smart air quality sensing and forecasting system is an important part of a smart city. In this paper, we present an approach to accurately forecast hourly fine particulate matter (PM2.5). An Internet of Things (IoT) framework comprising of Airbox Devices for PM2.5 monitoring has been used to acquire the data. Our main focus is to achieve high forecasting accuracy with reduced computation time. We use a hybrid model to do the forecast and a grid based system to cluster the monitoring stations based on the geographical distance. The experimentation and evaluation is done using Airbox Devices data from 119 stations in Taichung area of Taiwan. We are able to demonstrate that a proper clustering based on geographical distance can reduce the forecasting error rate and also the computation time.

原文英語
主出版物標題IoT as a Service - Third International Conference, IoTaaS 2017, Proceedings
編輯Yi-Bing Lin, Ilsun You, Der-Jiunn Deng, Chun-Cheng Lin
發行者Springer Verlag
頁面170-176
頁數7
ISBN(列印)9783030004095
DOIs
出版狀態已發佈 - 2018 一月 1
事件3rd International Conference on IoT as a Service, IoTaaS 2017 - Taichun, 臺灣
持續時間: 2017 九月 202017 九月 22

出版系列

名字Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
246
ISSN(列印)1867-8211

其他

其他3rd International Conference on IoT as a Service, IoTaaS 2017
國家臺灣
城市Taichun
期間17/9/2017/9/22

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • 引用此

    Mahajan, S., Liu, H. M., Chen, L-J., & Tsai, T. C. (2018). A machine learning based PM2.5 forecasting framework using internet of environmental things. 於 Y-B. Lin, I. You, D-J. Deng, & C-C. Lin (編輯), IoT as a Service - Third International Conference, IoTaaS 2017, Proceedings (頁 170-176). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; 卷 246). Springer Verlag. https://doi.org/10.1007/978-3-030-00410-1_20