Multi-Sensor Fire Alarm Validation for False Alarm Prevention
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Solution Overview
Problem
Fire alarm apparatuses often malfunction by mistaking non-fire conditions such as smoke from cooking or cigarette smoke for actual fire, leading to user distrust and increased risk of fire due to frequent false alarms.
Innovation Solution
A fire alarm system utilizing multiple sensing units to detect smoke, temperature, humidity, and gas, with a non-fire alarm prevention function that employs big data and wireless communication to validate fire detection signals, using a server to determine the validity of alarms based on different criteria for various situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single sensing unit is used to detect fire, then the device complexity is low, but the reliability of fire detection is poor due to false alarms from non-fire conditions
Solution Approach 1:
The fire detection system is divided into multiple independent sensing units, each detecting different parameters (smoke, temperature, humidity, gas). This segmentation allows the system to analyze multiple independent data sources to distinguish fire from non-fire conditions, thereby improving detection reliability while managing complexity through modular design.
Solution Approach 2:
Multiple sensing units detecting different physical quantities (smoke concentration, temperature, humidity, gas composition) are merged into a unified detection system. The server integrates data from all sensing units and applies comprehensive analysis algorithms to determine fire situations, achieving high reliability through combined multi-parameter detection.
2Reliability
If multiple sensing units with different detection criteria are used, then the reliability of fire detection is improved, but the device complexity increases due to data integration requirements
Solution Approach 1:
A server acts as an intermediary between multiple sensing units and the user interface. The server receives data from various sensing units, applies different determination criteria for different situations, and generates unified alarm decisions. This intermediary architecture manages the complexity of multi-criteria data integration while maintaining high detection reliability.
Solution Approach 2:
The system employs dynamic determination criteria that adapt to different situations. The server selects and applies different algorithms and thresholds based on the current context (e.g., different criteria for smoke detection versus temperature detection), allowing the system to maintain high reliability across varying environmental conditions without requiring a static complex structure.
3Measurement precision
If different determination criteria are applied for different situations, then the accuracy of fire detection is improved, but the ease of operation decreases due to complex decision-making processes
Solution Approach 1:
The system performs self-service by automatically selecting and applying appropriate determination criteria based on the detected situation. The server autonomously analyzes data from multiple sensing units, compares them against predefined criteria for different scenarios, and makes fire determination decisions without requiring user intervention or manual configuration, thereby maintaining high accuracy while preserving ease of operation.
Solution Approach 2:
The system implements feedback mechanisms where the server continuously monitors data from sensing units, adjusts determination criteria based on detected patterns and historical data, and refines its fire detection decisions. This feedback loop enables the system to maintain high measurement precision through adaptive learning while keeping the operation simple for end users who only need to respond to clear alarm signals.
Data Source
AI summary
A fire alarm apparatus with non-fire alarm prevention function according to an embodiment of the inventive concept includes a plurality of sensing units having different address information and configured to generate a fire detection signal when each sensing unit detects at least one of smoke, temperature, humidity, and gas to determine a fire situation, a repeater configured to perform wireless communication with each of the plurality of sensing units, a receiver configured to perform wireless communication with the repeater, and a first server configured to perform wireless communication with the receiver and determine the fire situation based on the fire detection signal, wherein the first server includes a big data reception unit configured to receive big data from an external second server, and a non-fire alarm determination unit configured to determine validity of the fire detection signal based on the big data and values detected by each of the plurality of sensing units based on different criteria for each situation.