Thermal Image Data Compression for IoT Fire Detection
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Solution Overview
Problem
Current fire detection systems in large structures have limited detection range, are prone to malfunctions, and lack integrated monitoring capabilities, especially in IoT-based networks, and fail to distinguish between electric and common fires, leading to inefficient data transmission and frequent false alarms.
Innovation Solution
A system that uses thermal image data compression to predict and detect fire outbreaks, enabling rapid identification and transmission of fire danger points over IoT networks, with a management server, state detection units, and thermal image cameras that calibrate and compress data for efficient communication, allowing for real-time monitoring and visual identification of fire risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a spark detector is used for fast fire alarm response, then the response speed is improved, but the detection range is limited to maximum 50m and malfunction risk increases
Solution Approach 1:
The patent combines multiple detection methods (spark detection, thermal image detection, and sensor-based detection) into a single integrated fire detection system. This merging allows the system to achieve both fast response speed through spark detection and extended detection range through thermal imaging and sensor networks, eliminating the limitation of using only spark detectors with 50m range.
Solution Approach 2:
The detection device is designed with multi-functionality, incorporating not only spark detection but also thermal image capture, sensor-based temperature and smoke detection, and communication capabilities. This universal design enables the single device to perform multiple detection functions, extending the effective detection range beyond the 50m limitation of traditional spark detectors while maintaining fast response capability.
2Device complexity
If conventional fire detectors are used with simple sensor-based detection, then the system structure is simple, but false alarms increase requiring frequent fire station dispatches
Solution Approach 1:
The patent merges multiple detection functions (spark detection, thermal imaging, sensor-based temperature and smoke detection) into an integrated system. This combination allows cross-validation of detection signals, reducing false alarms while maintaining manageable system complexity through unified processing and communication architecture.
Solution Approach 2:
The system incorporates feedback mechanisms where detection signals from multiple sensors and thermal images are continuously monitored and validated. The abnormal state determination unit analyzes patterns and provides feedback to filter out false alarms, improving detection reliability while maintaining system manageability through automated decision-making.
3Speed
If thermal image camera data is transmitted using Wi-Fi or Ethernet for high-speed transmission, then data transmission speed is improved, but the method is impossible for small amount of low-speed camera data in IoT-based sensor networks
Solution Approach 1:
The patent applies parameter changes by compressing thermal image data to reduce its size and adapt it for transmission over IoT-based sensor networks with limited bandwidth. The data compression transforms the thermal image data from a format suitable for high-speed Wi-Fi/Ethernet transmission into a compact format compatible with low-speed IoT networks, maintaining transmission effectiveness across different network types.
4Device complexity
If conventional fire detection systems are used, then the system is simple, but it cannot distinguish between electric fire and common fire leading to inefficient data transmission
Solution Approach 1:
The patent segments the fire detection analysis into distinct functional components: spark detection for electric fire identification, thermal image analysis for fire location and type determination, and sensor-based detection for general fire monitoring. This segmentation allows the system to distinguish between electric and common fires by analyzing specific characteristics from different detection sources, preventing information loss while maintaining manageable 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
Enables smooth data transmission over IoT networks, allowing for rapid fire detection and prevention, reducing false alarms and enabling managers to visually identify fire dangers, thereby facilitating timely measures.
Implementation Method 1
a detection space photographing unit configured to photograph the detection space... thermal image data measured through the second screen
Data Source
AI summary
The present disclosure relates to a system and method for predicting and detecting the outbreak of a fire. In particular, the present disclosure includes a management server configured to store and output data, a state detection unit disposed in a given space (hereinafter referred to as a “detection space”) becoming a target of detection and configured to transmit, to the management server, a detected value of a normal state or an abnormal state within the detection space, a detection space photographing unit configured to transmit, to the management server, a first screen obtained by photographing the detection space in the normal state in which a detected value detected by the state detection unit is less than a set value and a second screen obtained by photographing the detection space in the abnormal state in which a detected value detected by the state detection unit is the set value or more, an abnormal state determination unit configured to determine a dangerous situation when a detected value transmitted by the state detection unit is the set value or more and to transmit, to a management terminal, thermal image data measured through the second screen, and the manager terminal configured to communicate with the management server. Accordingly, the present disclosure provides an advantage in that a manager can predict and identify a fire outbreak danger point in advance.