Duration: 1–2 years

Abstract

Effective pre-incident briefing is critical for ensuring situational awareness and operational readiness in firefighting missions. However, current briefing practices are often based on static maps, fragmented building documentation, and limited real-time data integration.

This project develops an AI-enhanced Mixed Reality (MR) system for pre-incident briefing that integrates Internet of Things (IoT) sensor data, building information models (BIM), and real-time hazard intelligence into an immersive spatial environment.

The system enables firefighters to explore building layouts in MR prior to deployment while receiving context-aware insights, including occupancy estimates, fire safety infrastructure, hazardous zones, and sensor-derived environmental conditions. Explainable AI components support the interpretation of risk indicators and the generation of data-driven recommendations.

The objective is to improve preparedness, reduce cognitive load during entry, and enhance strategic decision-making before and during emergency response operations.

Research Objectives

The project pursues the following core objectives:

• Development of MR-based briefing environments:

  Design immersive pre-incident briefing tools that combine building models, IoT sensor streams, and AI-generated situational insights.

• Integration of real-time IoT and environmental data:

  Fuse distributed sensor networks with spatial building representations to provide up-to-date information on fire risk, occupancy, and environmental conditions.

• Explainable AI for decision support:

  Develop interpretable AI modules that translate complex sensor and model data into actionable insights for firefighters.

• Support for spatial and cognitive preparedness:

  Investigate how MR-based pre-briefing improves spatial understanding, route planning, and cognitive readiness before entering incident environments.

• Evaluation in operationally relevant scenarios:

  Assess system effectiveness in simulated pre-incident briefing exercises with professional firefighters, focusing on situational awareness and decision confidence.

Expected Impact

The project is expected to significantly enhance preparedness and decision-making quality in firefighting operations through improved pre-incident situational awareness.

By integrating IoT data, building information models, and AI-driven analysis into MR environments, firefighters can access a comprehensive and spatially grounded understanding of incident sites before deployment.

This leads to improved operational planning, reduced uncertainty during entry, and enhanced safety for both responders and affected populations.

In the long term, the project contributes to the development of intelligent, data-driven emergency preparedness systems that support faster, safer, and more informed intervention strategies.

Contact
Dr. Sara Scheffer
Email: sara.scheffer@tuwien.ac.at
© TU Wien