Open Data for Environment Sensing: Crowdsourcing Geolocation Data

Trieu, Ngoan Thanh and Williams, Zachary E. S. and Dorville, Jean-François M. and Huynh, Hiep Xuan and Rodin, Vincent and Pottier, Bernard (2020) Open Data for Environment Sensing: Crowdsourcing Geolocation Data. EAI Endorsed Transactions on Context-aware Systems and Applications, 7 (20): e4. ISSN 2409-0026

[thumbnail of eai.12-5-2020.164496.pdf]
eai.12-5-2020.164496.pdf - Published Version
Available under License Creative Commons Attribution No Derivatives.

Download (1MB) | Preview


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.

Item Type: Article
Uncontrolled Keywords: Open Data, Web Semantic, Environment Sensing, Geolocation Data, And Environmental Simulation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 14 Sep 2020 11:14
Last Modified: 14 Sep 2020 11:14

Actions (login required)

View Item
View Item