Fire and Smoke Detection Using Image BLOB Analysis
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Solution Overview
Problem
Existing fire and smoke detection systems are limited to enclosed spaces and require multiple sensors for early detection, often missing fires until they have developed significantly, and are ineffective in outdoor environments.
Innovation Solution
A method and system using image capturing devices with wide-angle lenses to detect fire and smoke by processing images for Binary Large Objects (BLOBs) and contours, applying background subtraction, shape analysis, and intensity calculations to identify smoke and fire in both indoor and outdoor environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used for early detection of fire and smoke, then detection sensitivity is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces traditional mechanical/physical sensors (particle sampling, temperature sampling, humidity sampling) with an optical-based video camera system. The camera captures visual information of fire and smoke, and image processing algorithms analyze the captured frames to detect fire and smoke characteristics. This substitution reduces hardware complexity while maintaining detection capability.
Solution Approach 2:
The video camera system performs multiple functions: it detects both fire and smoke simultaneously, works in both indoor and outdoor environments, and can operate over long distances. A single camera unit replaces what would traditionally require multiple specialized sensors, achieving multi-functionality and reducing system complexity.
2Reliability
If detection sensors are installed at ceilings or hidden places, then safety of the system is improved, but detection time is delayed until fire develops significantly
Solution Approach 1:
The patent transitions from point-based sensor detection (ceiling-mounted or hidden sensors detecting only immediate surroundings) to area-based visual detection (camera capturing wide field of view). By using wide-angle lenses and analyzing multiple pixels across the image frame, the system can detect fire and smoke from a distance and across a larger area, reducing detection delay while maintaining safety.
Solution Approach 2:
The system continuously captures and analyzes video frames in real-time, performing preliminary detection before fire and smoke reach the intensity levels that traditional sensors would detect. The image processing algorithms identify early signs of fire and smoke in the captured frames, enabling earlier warning while the system remains safely positioned.
3Adaptability or versatility
If traditional sensors are used, then detection is limited to enclosed spaces, but adapting to outdoor environments requires significant modification
Solution Approach 1:
The video camera system is inherently universal and can operate in both indoor and outdoor environments without requiring different sensor types. The camera captures visual information regardless of the environment, and the image processing algorithms adapt to detect fire and smoke characteristics in various lighting and atmospheric conditions, achieving environmental versatility with minimal modification.
Solution Approach 2:
The system adjusts detection parameters (such as sensitivity thresholds, color space transformations, and feature detection criteria) based on environmental conditions. The image processing algorithms can handle variations in lighting, background complexity, and atmospheric conditions, allowing the same hardware to function effectively across different environments without physical modification.
4Area of stationary object
If cameras with wide angle lens are used to expand detection coverage, then area of coverage is improved, but image processing complexity increases
Solution Approach 1:
The image processing system segments the wide-angle video frame into multiple regions or focuses on specific areas of interest (such as detecting smoke plumes, fire regions, or movement patterns). By dividing the complex image analysis into smaller tasks (background subtraction, feature extraction, pattern recognition), the system can handle large coverage areas without overwhelming processing complexity.
Solution Approach 2:
The system extracts only the relevant features from the wide-angle video frames (such as smoke texture, fire color, movement patterns, or thermal characteristics) rather than processing every pixel in detail. This selective extraction of key features reduces processing complexity while maintaining detection accuracy across the expanded coverage area.
Data Source
AI summary
This invention relates to a method and system for detecting fire and smoke. The system comprises a processor, a memory and instructions stored on the memory and executable by the processor to: receive a sequence of images from a plurality of cameras; sampling the sequence of images at a certain interval; process each of the sampled images to form a first processed image and a second processed image; extract Binary Large Objects (BLOBs) from first processed image and contours of objects from the second processed image; analyse the BLOB for smoke and the contours of objects for fire; and determine smoke in response to analysing smoke from the BLOBs and fire in response to analysing fire from the contours of objects.