Hadoop-based distributed system for online prediction of air pollution based on Support Vector Machine

Z. Ghaemi*, M. Farnaghi, A. Alimohammadi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

10 Citations (Scopus)
31 Downloads (Pure)

Abstract

The critical impact of air pollution on human health and environment in one hand and the complexity of pollutant concentration behavior in the other hand lead the scientists to look for advance techniques for monitoring and predicting the urban air quality. Additionally, recent developments in data measurement techniques have led to collection of various types of data about air quality. Such data is extremely voluminous and to be useful it must be processed at high velocity. Due to the complexity of big data analysis especially for dynamic applications, online forecasting of pollutant concentration trends within a reasonable processing time is still an open problem. The purpose of this paper is to present an online forecasting approach based on Support Vector Machine (SVM) to predict the air quality one day in advance. In order to overcome the computational requirements for large-scale data analysis, distributed computing based on the Hadoop platform has been employed to leverage the processing power of multiple processing units. The MapReduce programming model is adopted for massive parallel processing in this study. Based on the online algorithm and Hadoop framework, an online forecasting system is designed to predict the air pollution of Tehran for the next 24 hours. The results have been assessed on the basis of Processing Time and Efficiency. Quite accurate predictions of air pollutant indicator levels within an acceptable processing time prove that the presented approach is very suitable to tackle large scale air pollution prediction problems.

Original languageEnglish
Title of host publicationInternational Archives Photogrammetry Remote Sensing Spatial Information Sciences
Subtitle of host publicationInternational Conference on Sensors & Models in Remote Sensing & Photogrammetry
EditorsH. Arefi, M. Motagh
PublisherInternational Society for Photogrammetry and Remote Sensing (ISPRS)
Pages215-219
Number of pages5
Volume40
Edition1W5
DOIs
Publication statusPublished - Nov 2015
Externally publishedYes
EventISPRS International Conference on Sensors and Models in Remote Sensing and Photogrammetry 2015 - Kish Island, Iran, Islamic Republic of
Duration: 23 Nov 201525 Nov 2015

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
PublisherCopernicus
ISSN (Print)1682-1750

Conference

ConferenceISPRS International Conference on Sensors and Models in Remote Sensing and Photogrammetry 2015
CountryIran, Islamic Republic of
CityKish Island
Period23/11/1525/11/15

Keywords

  • Big data
  • Distributed computing
  • Online prediction
  • Spatial analysis
  • Support Vector Machine
  • Urban air pollution
  • ITC-CV

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