Forecasting the flow of urban pollution with cellular automata

Sukanya Benjavanich, Ziauddin Ursani, David Corne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Urban pollution is a growing health hazard in many urban centres across the globe. Prominent sources of pollution include diesel and gasoline vehicles, as well as manufacturing plants, power generation processes, and other industrial activity. In order to help understand and address pollution levels, a number of cities are installing sensor arrays; these installations will in future support monitoring and tracking of pollutants, and also underpin a range of possibilities for forecasting and mitigation. In this paper we describe an approach which forecasts the future flow and intensity of pollutants around an urban area, given recent historic sensor streams. The approach employs a cellular automaton, whose parameters are learned and adapted online by an evolutionary algorithm.

Original languageEnglish
Title of host publication5th IFIP Conference on Sustainable Internet and ICT for Sustainability (SustainIT)
PublisherIEEE
ISBN (Electronic)9783901882999
DOIs
Publication statusPublished - 14 Jun 2018

Keywords

  • Big data
  • Cellular automata
  • Evolutionary algorithm
  • Forecasting
  • Pollution

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Renewable Energy, Sustainability and the Environment

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  • Cite this

    Benjavanich, S., Ursani, Z., & Corne, D. (2018). Forecasting the flow of urban pollution with cellular automata. In 5th IFIP Conference on Sustainable Internet and ICT for Sustainability (SustainIT) [8379801] IEEE. https://doi.org/10.23919/SustainIT.2017.8379801