dataFLUT

The idea.

The “datenFLUT” project aims to develop an IoT-based modular demonstrator for real-time data acquisition from IoT (Internet of Things) sensors in the context of flood events.

For this purpose, various modular measurement sensor systems (level meters, flow sensors, pressure sensors, radar sensors, ultrasonic sensors, inlet monitoring) will be used in the demonstrator in combination with sensors for recording precipitation (so-called tipping-bucket rain gauges).

The data collection and the review of data quality should serve as the basis for the design of a real-time early warning system for a subsequent application, in which the IoT (Internet of Things) and the prospective use of artificial intelligence (AI) play a major role, encompassing all relevant components. In this preliminary project, the initial foundations and methods for flood and flood early warning systems are to be developed jointly and collaboratively.

The goal is to use this demonstrator to develop the methodological framework for a real-time early warning system in which IoT (Internet of Things) sensors and artificial intelligence (AI) play a key role. Various level sensors (pressure sensors, radar sensors, ultrasonic sensors) will be used in combination with rain gauges. The watercourse will be monitored by detecting precipitation events and tracking water levels.

In this demonstrator, various rain events will be simulated on the model to demonstrate how flooding can be detected early in combination with various modular measurement sensors (multi-sensor technology), how to process the data (data analysis), and what measures can be taken to prevent damage (damage prevention). In addition, the demonstrator provides an opportunity to observe and test the haptic integration into such a system “live” on site (hardware integration) and to compare it in the context of different installation scenarios.

For this purpose, the path of the water from the precipitation event through the gutter into the cistern and on to the lake or river is simulated. To illustrate this in practice, a stormwater sewer and corresponding retention infrastructure will be installed. The goal is to demonstrate interdependencies, such as how early strategic and reactive management can reduce the load on the stormwater sewer, as well as how blockages in inlets or sewers can be detected at an early stage. The sensor data is visualized in real time via a dashboard, and the future ubiquitous IoT sensor technology of the smart city should be made tangible here in the context of water management through a haptic representation of the digital twin. The demonstrator’s structure should remain mobile and modular so that it can be expanded at any time according to the application and the required sensors.

Challenge.

The most recent instances of high water and flooding caused by heavy rain events in the summer of 2021—as well as the events of 2018 in Saarland, which have not yet been forgotten—have demonstrated just how crucial flood protection is for municipalities, cities, state governments, and the federal government. Heavy rainfall events, in particular, are often localized, and the accuracy of forecasts depends on many local factors, such as the surrounding areas that serve as precipitation storage or soil conditions. A reliable IoT sensor system is indispensable not only during disasters but also for making informed decisions and for infrastructure planning.

Project partners.