Fire emergency response systems information requirements' data model for situational awareness of responders: A goal-directed task analysis

Building fire emergencies are considered a high-risk domain for significant loss of lives and property. Accurate information and Situational Awareness (SA) enable fire responders to make timely decisions and perform safe operations during fire emergencies. Although information technologies such as Building Information Modeling (BIM) and the Internet of Things (IoT) have the potential to supply information and support the decision-making processes of fire emergency response, the provided data are not necessarily the needed information at the operation level. This paper uses Goal-Directed Task Analysis (GDTA) to define fire emergency responders' SA Goals, Decisions, and Information (GDI) requirements. The semi-structured scenario-based interviews were conducted with ten Municipal fire department experts to determine GDI requirements. Based on the identified requirements, the SA-oriented use-case and sequence data models for decision-support Fire Emergency Information Systems (FERS) were developed to reveal the dynamic aspect of the FERS and to describe how the system should behave to enhance the SA of responders. The use-case data model visualizes the possible interactions of fire responders with the system, and the sequence data models visualize the order of the interactions and the call/return messages between the lifelines of the FERS. The validation of the GDI requirements and data models were performed by obtaining experts' feedback, and based on the feedback; the models were finalized. The SA GDI requirements and data models can eventually be helpful for FERS's user-friendly graphical interface design to support responders with higher SA. The FERS, which has comprehension and projection levels of information, will enhance effective decision-making, especially in cases where the skills and training of the firefighters are not sufficient to direct the emergency response.