Towards a low-cost, full-service air quality data archival system

Argyris Samourkasidis, Ioannis N. Athanasiadis

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

3 Citations (Scopus)

Abstract

We present our explorations towards a low-cost solution for creating an autonomous environmental data archival system. AiRCHIVE is a software platform for providing open access to sensor data with different ways, that account for machine interoperability. It is built with Raspberry Pi, a low-cost, pocket-size computer, and Air Pi a low-cost amateur sensory kit for air quality monitoring. Raspberry Pi with AirPi allowed us to easily capture raw sensor data and store them in a local database, and with AiRCHIVE we deployed "on sensor" a web server that provides with a set of services for data preprocessing and dissemination, including an implementation of OGC/SOS services and the OAI/PMH harvesting protocol.
Original languageEnglish
Title of host publicationProceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, iEMSs 2014
EditorsD.P. Ames, N.W.T. Quinn, A.E. Rizzoli
PublisherInternational Environmental Modelling and Software Society
Pages1192-1199
Volume2
ISBN (Print)9788890357442
Publication statusPublished - 2014
Event7th International Congress on Environmental Modelling and Software, iEMSs 2014 - San Diego, United States
Duration: 15 Jun 201419 Jun 2014

Conference

Conference7th International Congress on Environmental Modelling and Software, iEMSs 2014
CountryUnited States
CitySan Diego
Period15/06/1419/06/14

Keywords

  • Environmental data archive
  • Low-cost sensors
  • Metadata harvesting
  • Open archives
  • Semantic web
  • Sensor observations
  • Sharing and reuse
  • SOS

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  • Cite this

    Samourkasidis, A., & Athanasiadis, I. N. (2014). Towards a low-cost, full-service air quality data archival system. In D. P. Ames, N. W. T. Quinn, & A. E. Rizzoli (Eds.), Proceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, iEMSs 2014 (Vol. 2, pp. 1192-1199). International Environmental Modelling and Software Society. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=1188&context=iemssconference