Fire Spread Prediction Using Prioritized Facility Event Devices
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Solution Overview
Problem
Incident commanders lack the ability to accurately predict the spread of a fire within a facility, identify safe and unsafe areas for firefighters, and receive real-time data on fire progression during emergencies.
Innovation Solution
A system that utilizes event devices to detect fire spread, sorts devices into priority levels based on proximity and detected variables, and provides real-time data to predict fire spread and display safe and unsafe areas using a computing device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time data collection from multiple event devices is implemented, then fire spread prediction accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the facility into multiple zones with event devices distributed throughout, collecting data from individual devices and aggregating it to predict fire spread. This segmentation allows accurate local measurements while managing system complexity through modular data collection from discrete units rather than a monolithic system.
Solution Approach 2:
Event devices serve multiple functions: detecting fire conditions, providing location data, and contributing to predictive modeling. This multi-functionality reduces the need for separate specialized equipment, thereby improving prediction accuracy without proportionally increasing system complexity.
2Productivity
If event devices are sorted into priority levels based on proximity and detected variables, then response efficiency is improved, but information processing complexity increases
Solution Approach 1:
The system applies different priority levels to different event devices based on their specific location, proximity to detected fire, and local environmental variables. This local differentiation optimizes resource allocation and response efficiency by focusing attention on high-priority areas while simplifying processing for low-priority zones.
Solution Approach 2:
The system dynamically changes the priority parameter of event devices based on real-time detected variables such as temperature, smoke density, and proximity to fire origin. This dynamic parameter adjustment improves response efficiency by adapting to changing fire conditions while using established algorithms to manage processing complexity.
Data Source
AI summary
Devices, systems, and methods for predicting fire spread in a facility are described herein. In some examples, one or more embodiments include a computing device comprising a processor and a memory having instructions stored thereon which, when executed by the processor, cause the processor to receive an indication of a fire detected by an event device of a plurality of event devices installed in a facility, sort the plurality of event devices into a plurality of priority levels based on a determined likelihood of fire spread to each of the plurality of event devices, receive data collected by the plurality of event devices during the fire, and provide, via an interface, graphical information descriptive of a spread of the fire based on the received data.