Contextual Fire Detection System with Override Panels
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Solution Overview
Problem
Fire sensors, such as smoke detectors and heat detectors, often generate false alarms due to dirt, dust, aging sensors, and environmental factors like high humidity, leading to resource wastage, safety risks, and declining adoption rates as users become desensitized to legitimate alarms.
Innovation Solution
Implementing a fire detection system with override panels and non-fire detecting devices that provide contextual information to the monitoring system, allowing for verification of alarms and adjusting alarm generation based on occupancy, environmental conditions, and other contextual factors to minimize false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fire sensors are installed to provide early warning of fire, then fire detection capability is improved, but false alarm rate increases
Solution Approach 1:
The patent introduces an event context system as an intermediary between fire sensors and the alarm generation process. This system collects contextual information from multiple sources (surveillance cameras, motion detectors, appliance sensors, environmental sensors) and uses it to verify whether detected smoke or heat conditions represent actual fire threats or benign situations like cooking. The intermediary filters out false alarms while maintaining detection sensitivity.
Solution Approach 2:
The monitoring system is enhanced with multi-functionality by integrating not only fire detection capabilities but also contextual information gathering from various non-fire detecting devices. The system performs both traditional fire alarm monitoring and contextual verification functions, allowing it to distinguish between genuine fire threats and false alarm conditions through multiple data sources.
2Measurement precision
If traditional smoke detection algorithms are used, then detection accuracy is improved, but false alarms from cooking and environmental factors increase
Solution Approach 1:
The system implements feedback mechanisms where contextual information from surveillance cameras, motion detectors, and appliance sensors continuously feeds back to the monitoring system. This feedback loop allows the system to adjust alarm generation decisions based on real-time contextual conditions, such as detecting whether a person is present in the kitchen or whether cooking appliances are active, thereby reducing false alarms from cooking activities.
Solution Approach 2:
The event context system performs preliminary verification of alarm conditions before triggering fire alarms. By gathering contextual information in advance and analyzing it through dependency rules, the system determines whether detected conditions warrant alarm generation, preventing false alarms from benign cooking activities while maintaining response to genuine fire threats.
3Area of stationary object
If fire sensors are placed in high-traffic areas like train stations, then fire detection coverage is improved, but false alarms from environmental contamination increase
Solution Approach 1:
The event context system serves as an intermediary that verifies alarm conditions before triggering alerts. In high-traffic areas like train stations, the system uses contextual information from environmental sensors, surveillance cameras, and motion detectors to distinguish between genuine fire conditions and false alarm sources such as dirt, dust, or steam from trains, thereby maintaining detection coverage while reducing false alarms.
4Object-generated harmful factors
If override panels are added to verify alarms, then false alarm reduction is improved, but system complexity increases
Solution Approach 1:
The system implements self-service verification through automated contextual information gathering and analysis. The event context system automatically collects data from multiple sensors, applies dependency rules to verify alarm conditions, and makes intelligent decisions about alarm generation without requiring manual override panel intervention. This automation reduces false alarms while keeping the system relatively simple by eliminating the need for complex manual verification interfaces.
Data Source
AI summary
A number of different approaches are described for minimizing or preventing false alarms. In one case, override panels are used such as locally near or in the protected space or remotely at a security desk, for example. These override panels are used to deactivate or block the generation of a fire alarm signal in the case where the occupants or a management personnel recognizes that the fire alarm signal should not be generated. In this way, an alarm verification step is included. In another aspect, additional, contextual information is used to characterize or adjust when fire alarm signals are generated. This contextual information can be generated from sources that are not typically used in the generation of the fire alarm signal but instead are based on other sources of the information concerning the protected space.