Utilization of Innovative Digital Tools for Efficient and Smart Fire Fighting

Purpose and goal:

The project´s fundamental concept is that enhanced utilization of data from a building can provide decision support, leading to a more efficient and safer fire service response in the event of a fire.

The project will investigate how data from various types of sensors in building structures can be integrated with a digital fire model (digital twin) to improve firefighting operations. This integration can occur in both the preventive and operational area. An important part of the research involves examining the types of data that can be collected and how it can enhance the decision-making.

Expected results and effects:

Today, in many cases, the fire service must rely on what they observe externally during a building fire, and it may be sufficient in simpler structures. However, in larger and more complex buildings, it becomes more challenging. The project has the potential to demonstrate that rescue operations can be carried out more safely and efficiently if the incident commander has access to decision support based on data coming from sensors within the building.

Therefore, the project has the potential to bring about a change in how rescue operations are conducted in complex building structures. Approach and implementation:

The project begins with an inventory of sensors and fire protection information for i.e. "smart firefighting". Subsequently, a digital fire model is created using computer simulations and machine learning. By gathering sensor data, the fire model can be used to describe current and predict future conditions within a building.

Experiments are conducted to assess the model´s reliability, and the usability of sensors and the fire model for the fire service is tested during practical rescue exercises.