Central Monitoring Station Alarm Triage with Probability Scoring
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Solution Overview
Problem
False alarms in security systems lead to unnecessary dispatching of emergency services, consumption of resources, and delayed response times for actual alarm situations due to the inability to verify alarm events in real-time.
Innovation Solution
A central monitoring station uses an alarm probability measure determined by end user feedback and heuristics based on sensor data, historical data, weather data, crime data, and locale data to prioritize responses to potential alarm events, reducing false alarms and improving response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If alarm systems generate alerts for all detected security breaches, then detection coverage is improved, but false alarm rate increases
Solution Approach 1:
The system implements feedback loops where alarm events are monitored, verified through multiple sensors and heuristics, and used to refine future alarm probability assessments. The monitoring service receives alarm data, analyzes it through multiple verification steps, and feeds back probability scores that improve system accuracy over time.
Solution Approach 2:
An alarm probability score acts as an intermediary between raw sensor detection and emergency service dispatch. This intermediate assessment layer filters alarm events by calculating probability scores based on multiple factors, allowing the system to distinguish between genuine threats and false alarms before triggering emergency responses.
2Reliability
If emergency services are dispatched for all alarm events, then response coverage is improved, but resource consumption increases
Solution Approach 1:
The system applies partial action by dispatching emergency services only for alarm events that exceed a threshold probability score, rather than for all detected alarms. This selective approach ensures adequate response coverage for genuine threats while avoiding unnecessary resource consumption on false alarms.
Solution Approach 2:
The system changes the parameter of emergency service dispatch from a binary on/off decision to a probability-based threshold decision. By calculating alarm probability scores and comparing them against configurable thresholds, the system optimizes resource allocation based on the actual risk level of each alarm event.
3Object-generated harmful factors
If alarm verification processes are implemented, then false alarm reduction is improved, but response time increases
Solution Approach 1:
The system performs preliminary verification actions automatically as alarm events occur, using pre-configured heuristics and multiple sensors to assess alarm probability before emergency services are dispatched. This preliminary assessment reduces false alarms without significantly delaying response time for genuine threats.
Solution Approach 2:
For alarm events with high probability scores indicating genuine threats, the system skips extended verification processes and rushes through to immediate emergency service dispatch. This selective skipping ensures that critical alarms receive rapid response while lower-priority alarms undergo more thorough verification.
Data Source
AI summary
Alarm system technology, in which an alarm event is detected at a property monitored by an alarm system when the alarm system was set in an armed state. Based on detection of the alarm event, an alarm probability score that indicates a likelihood of the alarm event being an emergency situation is determined and the alarm event is handled based on the determined alarm probability score.