Data-based Empirical Modeling of Fire and EMS Apparatus Performance

Authors: Alex Temes*, Deccan International
Topics: Spatial Analysis & Modeling, Geographic Information Science and Systems, Medical and Health Geography
Keywords: Fire, EMS, GIS, Optimization, Complex Modeling
Session Type: Virtual Paper
Presentation File: No File Uploaded


Both in the US and abroad, Fire and EMS agencies are tasked with maximizing performance and minimizing costs. one of the ways they can work to achieve this is using empirical data to support algorithmic modeling of performance projections. Using data and complex algorithms, Fire and EMS agencies can be empowered to make data-driven decisions that can help better serve critically-underserved communities, address hazardous situations, and maximize access to high-quality emergent and/or low acuity Medical services. This paper presentation will discuss how this data is collected, prepared, and expressed in a GIS-based application, and then applied to complex, real-world scenarios. Some examples of topics to be discussed including the modeling of Fire and Rescue Boat performance, the modeling of alternative staffing strategies and how these strategies impact Key Performance Indicators (KPIs) used for both internal operations and international accreditation. In addition, this presentation will also touch on methods of apparatus optimization, reviewing the processes that can be taken to find the appropriate deployments for apparatus or placement of facilities. This paper presentation will seek to demonstrate the relationship between academia, private industry, and public safety agencies by outlining the relationships these industries have with one another, and how each helps drive the other two to improve. Applicable fields of study that will be discussed include Geography/GIS, Public and Fire/EMS Administration, Data Science, Operations Research/Industrial Engineering and Complex Optimization Modeling.

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