Research Article
Open Data for Environment Sensing: Crowdsourcing Geolocation Data
@ARTICLE{10.4108/eai.12-5-2020.164496, author={Ngoan Thanh Trieu and Zachary E. S. Williams and Jean-Fran\`{e}ois M. Dorville and Hiep Xuan Huynh and Vincent Rodin and Bernard Pottier}, title={Open Data for Environment Sensing: Crowdsourcing Geolocation Data}, journal={EAI Endorsed Transactions on Context-aware Systems and Applications}, volume={7}, number={20}, publisher={EAI}, journal_a={CASA}, year={2020}, month={5}, keywords={Open Data, Web Semantic, Environment Sensing, Geolocation Data, And Environmental Simulation}, doi={10.4108/eai.12-5-2020.164496} }- Ngoan Thanh Trieu
Zachary E. S. Williams
Jean-François M. Dorville
Hiep Xuan Huynh
Vincent Rodin
Bernard Pottier
Year: 2020
Open Data for Environment Sensing: Crowdsourcing Geolocation Data
CASA
EAI
DOI: 10.4108/eai.12-5-2020.164496
Abstract
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.
Copyright © 2020 Ngoan Thanh Trieu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
