Sensors are quickly becoming ubiquitous and can be found in a vast range of environments. The increase of sensor systems is accompanied by an increasing volume of data, as well as an increasing heterogeneity of devices, data formats, and measurement procedures. Shared semantic definitions help not only with data integration from multiple sources, but can also assist in integrating data into temporal and spatial contexts. It is well recognized that ontologies have an important role to play in data integration. In this research work, an ontology by integration is developed for floods risk prevision based on continuous measurements of water parameters gathered in the watersheds and along the sewers and delivered to simulation models. The objective of this ontology is to promote the interoperability of components across hydrologic/hydraulic and wireless sensor network domains in order to forecast flooding risk scenarios. © Springer International Publishing Switzerland 2015.

cited By 0; Conference of 2nd National Conference on Sensors, 2014 ; Conference Date: 19 February 2014 Through 21 February 2014; Conference Code:112979