EAI Endorsed Transactions on Context-aware Systems and Applications (May 2020)

Open Data for Environment Sensing: Crowdsourcing Geolocation Data

  • Ngoan Trieu,
  • Zachary Williams,
  • Jean-François Dorville,
  • Hiep Huynh,
  • Vincent Rodin,
  • Bernard Pottier

DOI
https://doi.org/10.4108/eai.12-5-2020.164496
Journal volume & issue
Vol. 7, no. 20

Abstract

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There are numerous situations where the digital representation of the environment appears critical for understanding and decision-making: threats on soils, water, seashores, risk of fires, pollutions are evident applications. If spatial cellular decomposition is evidence in the more common applications, there remains a large field for environment and activities modelling. The integration and composition of several information sources is perhaps the main difficulty with the need to deal with data interpretation and semantics inside concurrent simulators. Besides, the data on population, people's behaviours, people's perceptions are essential in environmental assessments, where the technical aspect is not counted as much as the common acceptance of impact technology. We provide a model for building environmental services with open data systems. A case study is given for getting information from the public about their relationship with freshwater and its scarcity in Jamaica.

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