The ROBUST project set out to create a fully integrated, cross‑disciplinary earthquake early‑warning and response system that covers the entire chain from seismic detection to rapid damage assessment and user‑specific information delivery. The system was designed for the seismic environment of the Lower Rhine Bay, one of Germany’s most seismically active regions, and was demonstrated on a bridge structure and an industrial plant. The feasibility of the complete solution was validated by simulating representative earthquake scenarios on a shaking table, confirming that the system can detect seismic events, estimate damage in near real‑time, and issue timely warnings to stakeholders.
On the technical side, the project developed an optimally laid out distributed seismic sensor network. A methodology for spatial optimisation of seismic stations was introduced, and a catalogue of earthquake scenarios for the Lower Rhine Bay was compiled. The existing network was densified using the new optimisation scheme, resulting in a higher spatial resolution that improves event localisation and magnitude estimation. The real‑time network component was built on decentralised intelligent sensor nodes that perform on‑board data processing and risk‑based evaluation. These nodes integrate user‑specific criteria and feed results into a communication platform managed by the partner FOKUS. The platform supports the dissemination of warnings to end users and interfaces with the national Katwarn system.
The project also produced a sensor‑based condition monitoring concept for critical infrastructure. A risk‑based assessment method was developed to classify infrastructure according to usage and safety requirements. Monitoring concepts were derived that combine accelerometers, MEMS sensors, strain gauges, and environmental sensors (temperature, wind). For the bridge prototype, six high‑resolution, low‑noise accelerometers, eight MEMS accelerometers, and eight strain gauges were installed, together with a weather station. In the chemical plant prototype, six high‑resolution two‑axis seismic accelerometers, eight MEMS accelerometers, and eight strain gauges were deployed, all meeting IP67 and UV‑resistant cabling standards. Data from these sensors are processed locally, and state‑of‑structure information is visualised in Building Information Models (BIM) created by RWTH Aachen. The BIM integration allows for rapid damage detection and supports decision‑making for maintenance and emergency response.
Performance results include the successful real‑time detection of simulated seismic events on the shaking table, with warning times sufficient for the activation of emergency protocols. The monitoring prototypes achieved accurate identification of structural responses, and the integration with BIM enabled a coherent visual representation of damage states. The communication platform demonstrated reliable dissemination of alerts to users and compatibility with existing national warning systems.
Collaboration was organised around four work packages. RWTH Aachen led the risk assessment, monitoring concept development, state analysis, and BIM integration. The German Research Centre for Geosciences (GFZ) was responsible for seismic network optimisation, scenario cataloguing, and network densification. FOKUS handled the communication platform, decentralised warning services, and fallback concepts. Wölfel contributed to infrastructure classification, network integration, and risk‑based threshold definition. Additional partners such as BASF PLT and National Instruments supplied sensor hardware and performed field testing. The project ran over a four‑year period, concluding in December 2023, and was funded by German research agencies under a national research programme.