Building Fire Modeling With Occupant Detection and Voice Links
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Solution Overview
Problem
In multi-occupancy buildings, especially in MRHR environments, there is a lack of effective information available to Fire & Rescue Services during fires, including the status of the fire, occupant distribution, building layout, and medical conditions, which hampers firefighting efficiency and occupant safety.
Innovation Solution
A computer-implemented method using thermal sensors and carbon dioxide sensors to detect fire and people, combined with real-time voice and data communication, constructs dynamic models of fire and occupant locations, enabling probabilistic simulations of firefighting interventions and evacuation routes, leveraging cloud computing and machine learning for real-time data processing and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual patrolling service is employed to detect fires, then fire detection capability is provided, but operational cost increases and efficiency decreases
Solution Approach 1:
The system enables automatic fire detection through interconnected appliances that autonomously monitor temperature and carbon dioxide levels, eliminating the need for manual patrolling while maintaining continuous surveillance capability
Solution Approach 2:
Manual mechanical patrolling is replaced with electronic sensing systems that use thermal and gas detection to automatically identify fire conditions, transforming a labor-intensive process into an automated electronic monitoring system
2Loss of information
If comprehensive data collection and probabilistic modeling is implemented, then firefighting decision-making is improved, but computational complexity and data processing requirements increase
Solution Approach 1:
Building data such as layouts, construction materials, and occupant information are collected and stored in advance before fires occur, allowing the system to rapidly process and model fire scenarios without the complexity of real-time data gathering during emergencies
Solution Approach 2:
The system continuously compares actual sensor readings against probabilistic fire models to refine predictions and update fire spread scenarios in real-time, improving accuracy while managing computational load through iterative refinement
3Ease of operation
If real-time voice communication between appliances and remote devices is enabled, then communication capability is improved, but system complexity increases
Solution Approach 1:
The appliance integrates multiple functions including environmental sensing, fire detection, occupant detection, and voice communication within a single device, reducing the need for separate communication infrastructure and simplifying the overall system architecture
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
Enhances firefighting efficiency and occupant safety by providing accurate, real-time information on fire spread and occupant locations, allowing for targeted interventions and optimized evacuation plans, reducing injury risks for both occupants and firefighters.
Implementation Method 1
each equipped with thermal sensors and carbon dioxide sensors arranged within a building and configured to detect locations of elevated temperature
Implementation Method 2
carbon dioxide sensors arranged within a building and configured to detect locations of elevated temperature and ambient carbon dioxide levels
Data Source
AI summary
The described invention relates to a computer-implemented method for determining fire safety and occupant safety information, comprising: receiving data from a plurality of Appliances, each equipped with thermal sensors, carbon dioxide detectors and real-time voice communication capabilities, arranged within a building and configured to detect locations of elevated temperature and ambient carbon dioxide levels within the building; wherein one or more of said Appliances are arranged to detect elevated temperatures and levels of carbon dioxide indicative of the presence or risk of fire, and one or more of said Appliances are arranged to detect elevated temperatures indicative of body heat and carbon dioxide levels indicative of respiration and therefore the presence of one or more people, and enabling communication between occupants and a remote person to determine any special medical priorities of said occupants; analysing the received data to determine a first location corresponding to the presence or risk of fire and a second location corresponding to the presence of one or more people; using data corresponding to the first and second locations to construct virtual (i.e., computer-generated) dynamic real-time models of the current state of the fire and probabilistic models of the likely physical development of the fire, and by reference to pre-determined policies defining courses of action to be taken in different fire hazard scenarios, communicating and representing data according to the appropriate policy response. Furthermore, proposed firefighting interventions can be sent as data to the processing unit and the impact of such interventions can be included in the probabilistic fire models, enabling real-time simulation of the impact of said proposed interventions and interpretation of the likely results, using machine learning to improve the accuracy of the simulations. In this way, evacuation priorities and firefighting methods can be better targeted and occupants can be more safely evacuated from the building; resulting in reduced injury risk for occupants and firefighters due to enhanced intelligence on the status and likely development of the fire.