Alarm Monitoring System Using Sensor Cross-Validation to Reduce False Alarms
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Solution Overview
Problem
Existing alarm monitoring systems often generate false alarms due to user error or non-urgent events, leading to unnecessary burdens on first responders and increased costs, as they lack effective methods to verify the authenticity of alarm events before dispatching services.
Innovation Solution
A method and system that analyze event data in conjunction with verification data using a processor and memory to generate a probability indication of an alarm event, applying rules and predefined values to determine the likelihood of an alarm, and initiate appropriate actions such as notifications or home automation adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video verification methods are used to verify alarm events, then the reliability of alarm event indicators is improved, but the response time increases and human resource costs increase
Solution Approach 1:
The system performs preliminary verification by analyzing additional event data from multiple sensors before dispatching first responders. This preliminary action filters out false alarms early in the process, ensuring that only verified alarm events trigger emergency responses, thereby maintaining high reliability without delaying critical responses.
Solution Approach 2:
The system introduces an intermediary verification layer that processes event data from multiple sources (motion detectors, glass break detectors, door contacts, environmental sensors) before confirming an alarm event. This intermediary analysis acts as a mediator between raw sensor data and emergency dispatch decisions, improving reliability while maintaining rapid response times through automated processing.
2Reliability
If video verification methods are used to verify alarm events, then the reliability of alarm event indicators is improved, but the cost associated with human resources increases
Solution Approach 1:
The system performs self-service verification by automatically analyzing event data from multiple sensors and determining whether an alarm event is genuine. This automated self-verification eliminates the need for human operators to review every alarm event, significantly reducing human resource costs while maintaining high reliability through comprehensive sensor data analysis.
Solution Approach 2:
The system introduces an intermediary automated verification layer that processes event data from multiple sources before confirming an alarm event. This intermediary analysis reduces the burden on human resources by filtering out false alarms automatically, allowing human operators to focus only on verified critical events, thereby reducing overall human resource costs while maintaining reliability.
3Reliability
If additional hardware is used to verify alarm events, then the reliability of alarm event indicators is improved, but the cost of the alarm monitoring system increases
Solution Approach 1:
The system achieves multi-functionality by using existing alarm monitoring sensors (motion detectors, glass break detectors, door contacts, environmental sensors) for both their primary alarm detection function and secondary verification function. This universal use of existing hardware improves reliability through cross-validation without requiring additional specialized verification equipment, thereby avoiding increased system costs.
Solution Approach 2:
The system merges the verification function with the existing alarm detection infrastructure by combining data from multiple sensor types already present in the system. This consolidation allows the system to verify alarm events using existing hardware resources, improving reliability without the need for separate verification equipment and avoiding additional system costs.
4Reliability
If follow up contact with system owner is required for verification, then the reliability of alarm event indicators is improved, but the response time increases
Solution Approach 1:
The system performs preliminary verification by automatically analyzing event data from multiple sensors before contacting the system owner. This preliminary automated verification filters out many false alarms before human contact is needed, ensuring that follow-up contacts occur only for genuinely suspicious events, thereby improving reliability while minimizing response time delays.
Solution Approach 2:
The system implements automated feedback processing by analyzing event data from multiple sensors and using this feedback to determine whether alarm event verification is needed. This feedback mechanism allows the system to make intelligent decisions about when to contact the system owner, improving reliability by reducing unnecessary contacts while maintaining rapid response times for genuine alarms.
Data Source
AI summary
A device and method for analyzing an event at a premises is provided. In one embodiment the device includes a processor and a memory configured to store executable instructions, which when executed by the processor, cause the processor to receive first event data related to the event at the premises, receive verification data related to the event at the premises, analyze the first event data in conjunction with the verification data, generate, based on the analysis, an indication of a probability that the event is an alarm event, and initiate at least one action based on the indication.