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EXAMPLE IDEA: Online Early Warning System for Flooding (Sustainable Portfolio Idea)

Short description (max. 250 characters)
Generation of new Siemens business based on the results of the EU funded project "UrbanFlood" ( Project goal is the development of an Internet based service platform for early warning systems. This platform will be validated for monitoring of dike and dam quality in order to forecast future dike breaches and flooding effects.

Key benefits (max. 250 characters)
More than 100 millions of people would benefit due to better protection of their lives, their houses, and their goods. Siemens and its employees would get a new business related to environmental monitoring.

Detailed description (max. 500 words)
Purpose of dikes is flood protection. Often they are too weak rather than too low. Sensor networks shall provide early warnings in case of critical changes. Sensor data have to be aggregated and evaluated. Finally, automatic decision support has to be provided based on warnings, alarms and if-then scenarios of dike breaches. An IT infrastructure for international, distributed early-warning systems will be developed combining technologies such as cloud computing, virtualization, machine learning (artificial intelligence) methods for the automated calibration of sensor networks, automated sensor data validation, and automated generation of (correct) alarms. Visualization of results for authorities and general public will be on multi-touch panels. Main idea was the participation of Corporate Technology's research group "Monitoring and Preventive Control" in such research project funded by EU, in order to work on new, sustainable business opportunities for Siemens. Siemens is work package leader for system integration and responsible for the core technology "machine learning". Results of this project will be running prototypes validated at three dikes/dams in Amsterdam, London and St. Petersburg.

Differentiating factor
Purpose of the project is the system integration of existing technologie for an early warning system devoted to dike quality monitoring. Unique selling point is the application of machine learning methods for the automated calibration of sensor networks, the automated indicator generation out of numerous sensors, and the automated data and alarm aggregation.

Additional Information
This is a business opportunity generated by climate change and advances in new IT technologies. Such an IT platform for early warning systems can be applied for other scenarios such as volcano eruptions, earth quakes, storms, tsunamis, etc. Monitoring of structures could be extended by bridges, tunnels, and buildings.

dam, dike, environmental monitoring, flood protection, machine learning methods, online early warning system, water

Buildings, Factory of the future



Status: in discussion

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Number: 000001

submitted: 15.05.2012