Digital Twin Fire Risk Evaluation for Early Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing fire detection systems only notify users after a fire occurs, leading to potential delays in response and increased casualties and property damage.
Innovation Solution
A fire prevention system utilizing sensors that communicate via radio frequency, a digital twin calculation unit, and a server that calculates a fire index and provides an evaluation tool with color-coded risk zones for improved visibility and timely response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fire sensors are used to detect fire occurrence, then fire detection capability is provided, but response time is delayed and golden time is exceeded
Solution Approach 1:
The system performs preliminary actions by continuously monitoring fire risk indicators (heat, smoke, flame, gas) before actual fire occurrence. The digital twin model simulates fire scenarios in advance, and the evaluation tool calculates fire indices proactively, enabling early warning and preparedness responses before the fire fully develops, thus preventing golden time loss.
Solution Approach 2:
The system implements feedback mechanisms where sensor data is continuously fed into the digital twin model, which then updates the fire risk evaluation. The evaluation tool provides real-time feedback on fire indices and risk levels, allowing the system to adjust monitoring intensity and alert thresholds dynamically, improving response timing based on evolving risk conditions.
2Measurement precision
If comprehensive fire monitoring is implemented with multiple sensors and digital twin modeling, then fire risk detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the fire monitoring function into distinct modular components: first sensors for fire detection, second sensors for facility monitoring, digital twin calculation unit for modeling, big data receiving unit for data management, and evaluation tool for risk assessment. Each module operates independently but integrates through standardized interfaces, reducing overall system complexity while maintaining comprehensive monitoring capability.
Solution Approach 2:
The digital twin calculation unit serves multiple functions simultaneously: it processes data from various sensor types, runs fire scenario simulations, calculates fire indices, and generates evaluation tool outputs. This multi-functionality consolidates what would otherwise require separate systems, improving measurement precision without proportionally increasing complexity.
3Productivity
If real-time fire index calculation and evaluation tool generation are performed, then timely fire risk information is provided, but computational resource consumption increases
Solution Approach 1:
The system performs fire index calculations and evaluation tool generations periodically rather than continuously. The evaluation tool is updated at predetermined intervals or when significant changes occur in fire risk indicators, allowing the system to provide timely information while reducing computational resource consumption by avoiding constant recalculations of the entire fire scenario model.
Solution Approach 2:
The digital twin model performs partial calculations focused on the most critical fire risk factors rather than exhaustive simulation of all possible scenarios. The evaluation tool selectively processes and displays only the most relevant fire index components and risk assessments, providing timely information with reduced computational effort by omitting less critical calculations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables early detection and visualization of fire risk, allowing users to respond promptly and reduce damage, thereby enhancing fire prevention reliability.
Implementation Method 1
generating fire information by detecting at least one of heat, smoke, flame, and gas
Implementation Method 2
generating fire information by detecting at least one of heat, smoke, flame, and gas
Implementation Method 3
perform radio frequency (RF) communication with each other
Data Source
AI summary
A fire prevention system according to an embodiment of the present invention may include a plurality of first sensors that generate fire information and perform radio frequency (RF) communication with each other, a plurality of second sensors, and a first server that performs the RF communication with the plurality of first sensors and the plurality of second sensors, and the first server may include a digital twin calculation unit, a big data receiving unit that receives big data from an external second server, a server memory, a server communication unit, an area classification unit that divides information into a plurality of portions, a fire index calculation unit that calculates a fire index, and an evaluation tool calculation unit that calculates an evaluation tool that visually implements the fire index in each of the plurality of portions.