Decison-making in incident response

Project description

How can AI-driven decision-support systems improve the efficiency and accuracy of decision-making by firefighters during emergency situations?
Our project explores this central question by developing a prototype that combines speech recognition, AI analysis, and real-time data processing. Fire commanders receive immediate recommendations through the application, based on emergency calls, building information, and sensor input. The focus is on providing fast, clear, and reliable support in situations where every second counts.

Context

This project operates within the domain of public safety and emergency response, with a specific focus on firefighting interventions. Firefighters are required to make rapid decisions under extreme pressure, often with incomplete information. Current procedures leave little room for technological support during active incidents. At the same time, technologies such as Artificial Intelligence (AI), machine learning, and speech recognition are advancing rapidly, with the potential to play a valuable role in time-critical decision-making in the future.

In this project, we explore how AI could contribute to faster and more well-founded decisions during emergency situations. To do so, we are developing a working prototype that analyzes emergency calls and building data, uses speech recognition for hands-free input, and provides tactical recommendations to the commander. Although current regulations do not yet allow the use of AI in the field by fire departments, this project serves as exploratory research into the possibilities of these emerging technologies.

The prototype provides a concrete demonstration of how AI and real-time data processing can work together in a high-pressure professional environment. The aim is not only technical development, but also to offer insight into what may be possible in the near future and what will be required technically, practically, and ethically to get there. With this, we hope to contribute to a future-proof fire service that is ready for the digital transition.

Results

The most important outcome of our project is demonstrating the potential of emerging technologies such as Artificial Intelligence and real-time data processing within the context of firefighting interventions. By developing a functional prototype, we have shown how AI could support faster and more well-founded decision-making during emergency situations in the future.

Our prototype includes a basic model capable of analyzing emergency call data and building information to generate strategic recommendations. What makes this particularly valuable is that the AI also explains the reasoning behind its advice, giving users insight into the underlying logic. This increases trust in the system and supports its potential future use in a critical operational environment.

In addition, we designed a dashboard that provides a quick and visual overview of key information during and after an intervention. This aims to assist firefighters with situational awareness, evaluation, and reducing information overload. The interface is designed with simplicity and speed in mind two essential requirements from the field.

Another innovation within the project is the concept of the “safebox”: a digital tool within the application that supports interim decision-making and safety checks on the scene. This feature aims to reduce risks and help prevent human error.

In terms of Technology Readiness Level (TRL), our project is positioned around level 3: the concept has been clearly defined, a working prototype has been built, and validation is planned. With this project, we are laying the groundwork for further testing, development, and discussions about the role of AI in the future of firefighting.