English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Today’s generation of motor vehicles is equipped with numerous sensors collecting a variety of sensor data. These sensors are primarily designed to internally control miscellaneous comfort and safety functions but are also offering potential to be used externally in cross-sectoral applications, such as water management use cases. At this point, the general suitability of vehicle sensor data for realtime agglomeration of precipitation information using the example of Emscher and Lippe region is one of the key issues of the research project mobileVIEW. A major challenge in implementation in order to be able to conduct spatio-temporal adjustments of precipitation data is to derive valid precipitation values from vehicle sensor measurements. For this purpose, a decision tree trained with historical precipitation radar data is used to derive precipitation intensities from a combination of rain related measurements with additional environmental values based on the position of the vehicle. Emerging potential for runoff forecasting and heavy rainfall nowcasting is analysed within the operational flood early warning system based on Delft-FEWS.

agit journal

Ableitung von Echtzeit-Niederschlagsinformationen aus mobilen Kfz-Sensordaten / Derivation of Real-Time Precipitation Information Using Mobile Vehicle Sensor Data