Multi-Spectral Fire Detection Camera Selection
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Solution Overview
Problem
Fire prevention monitoring systems struggle to maintain high analysis quality under changing climatic conditions and fail to detect fires in critical visibility conditions, such as darkness, rain, haze, or fog, and lack detailed vegetation monitoring capabilities.
Innovation Solution
A fire prevention and detection method utilizing a multi-spectral monitoring system with PTZ video cameras operating in near-infrared, thermal infrared, ultraviolet, and visible light ranges, along with environmental detection means, which selects the best-performing camera based on entropy values and environmental data for adaptive analysis, and includes a self-calibration step to automatically adjust to changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single video camera operating in visible light range is used, then the system structure is simple, but the analysis quality deteriorates under changing climatic conditions and critical visibility conditions
Solution Approach 1:
The patent employs multiple video cameras operating in different spectral ranges (visible light, near-infrared, thermal infrared, ultraviolet) to provide universal monitoring capability across various climatic conditions. Each camera type serves specific functional purposes: visible light for general observation, near-infrared for penetration through haze/fog, thermal infrared for heat detection, and ultraviolet for vegetation monitoring. This multi-functional approach ensures reliable analysis quality regardless of environmental conditions.
2Adaptability or versatility
If multiple video cameras operating in different spectral ranges are used, then the adaptability to changing climatic conditions improves, but the device complexity increases
Solution Approach 1:
The patent implements dynamic selection of the best-performing camera based on real-time environmental data and entropy values. The control unit continuously monitors conditions (temperature, humidity, visibility) and automatically switches between different camera types to optimize performance. This dynamic adaptation mechanism allows the system to maintain high reliability while managing the complexity of multiple cameras through intelligent automation rather than static configuration.
Solution Approach 2:
The system employs feedback mechanisms where environmental detection means continuously monitor climatic conditions and feed this information to the control unit. The control unit uses this feedback to calculate entropy values for different camera outputs and select the optimal camera for current conditions. This closed-loop feedback system enables automatic optimization of monitoring quality without requiring manual intervention, effectively managing system complexity.
3Measurement precision
If environmental detection means and multiple spectral cameras are used, then the detection precision in critical visibility conditions improves, but the loss of time for data processing and camera switching increases
Solution Approach 1:
The system performs preliminary calculations of entropy values for different camera types based on environmental data before actual fire detection is needed. By pre-computing which camera will be most effective under current conditions, the system eliminates the need for time-consuming real-time analysis during critical detection moments. This preliminary action ensures rapid camera selection and minimizes processing delays when actual fire detection is required.
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
Ensures high-quality analysis and effective fire detection across varying environmental conditions, including critical visibility conditions, while providing detailed vegetation monitoring, with rapid adaptation and optimized performance through the use of multiple spectral ranges and entropy-based camera selection.
Implementation Method 1
at least a first video camera (11) operating within a near-infrared range (NIR); at least a second video camera (12) operating within a thermal infrared range (FIR); at least a third video camera (13) operating within an ultraviolet range (UV)
Implementation Method 2
the control unit (30) calculates, for each video camera (11, 12, 13), an entropy value of an image obtained by the video camera (11, 12, 13)
Data Source
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Figure 2
AI summary
The present invention relates to a method for fire prevention and/or detection through a monitoring system (1) comprising: - a plurality of video cameras (10); - environmental detection means (20) for detecting some parameters relating to the area to be monitored; - a control unit (30) adapted to receive and analyse the data coming from said plurality of video cameras (10) and from said environmental detection means (20). The invention is characterized in that said control unit (30) implements the following steps: a) it controls the traverse for positioning said plurality of video cameras (10), said plurality of video cameras (10) comprising at least a first video camera (11) operating within the near infrared range (NIR), at least a second video camera (12) operating within the thermal infrared range (FIR), and at least a third video camera (13) operating within the ultraviolet range (UV), b) it selects the best performing video camera (11, 12, 13) among said plurality of video cameras (10) on the basis of a entropy value of an image obtained by each video camera (11, 12, 13) and as a function of the data detected by said detection means (20).