Critical Infrastructure Monitoring in CBRNe Scenarios: A reliable and robust communication network for distributed multimodal sensors

Kurzfassung

The malicious misuse of CBRNe agents can be used to inflict extensive damage to critical infrastructure and terrorize public society. The effects of such attacks can range from financial and or structural drawbacks to significant casualties. Recent terror attacks in Cucuta (2021) or Kabul (2021) demonstrate the need to protect infrastructures such as airports, power plants, and transportation infrastructure. In the face of these modern-day threats, the need for a reliable and effective monitoring system for critical infrastructure has become increasingly important. We propose concepts and templates as well as a prototypical implementation for such a technical solution, utilizing a meshed, distributed data network for the combination and fusion of multimodal heterogeneous sensors or sensor systems. The network is made up of both mobile and static nodes that provide analog and digital sensor interfaces as well as communication modules and energy management. The wireless meshing ability provides a highly scalable and adaptable solution that can be easily integrated into any infrastructure. The concept also includes special throwable sensor nodes that, combined with their meshing abilities, enable the use of such sensors in situations without any existing communication infrastructures (i.e. areas of catastrophic events) to quickly rollout a custom communication network. Since mobility is an important factor, our solution is focused on energy efficiency and energy harvesting wherever possible, to enable non-stationary nodes to operate for extended periods without the need for a power source. In addition to the network, we propose concepts for a reliable "data sink", on which central data fusion/signal processing is handled. The central data fusion engine provides the ability to detect anomalies, identify patterns, and predict events before they occur. The fused and analyzed data is made available using open APIs for the consummation by i.e. digital twins. This will enable operators of critical infrastructures to simulate and predict the behavior of their systems, allowing them to make proactive decisions and reduce the likelihood of disasters. Our proposed solution is well-suited for CBRNE scenarios and can provide an effective means for monitoring and responding to potential threats. The self-deploying meshed network architecture and energy-efficient design make it a highly adaptable solution that can be deployed in any situation. The central data fusion/signal processing and API for digital twins make it a comprehensive solution that provides enhanced situational awareness and enables proactive decision-making.