Alarm Panel Classification via Pareto Optimization
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Solution Overview
Problem
Building security systems face a significant challenge with false alarms, which account for approximately 98% of all alarms, primarily due to user error, faulty equipment, and improper installation, leading to financial burdens on customers, police departments, and alarm system providers.
Innovation Solution
A system that analyzes alarm panels by receiving and classifying alarm events, generating data points, identifying statistical dividers, and assigning rankings to alarm panels based on their performance, allowing for the construction of a monitoring dashboard to prioritize servicing of alarm panels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If alarm panels are monitored and classified using traditional methods, then the system can identify false alarms, but the process is manual and time-consuming, reducing productivity
Solution Approach 1:
The patent replaces manual mechanical analysis methods with an automated computer-based system that receives alarm events, generates data points, computes Pareto frontiers, and assigns rankings automatically. This substitution of mechanical human analysis with computational algorithms dramatically improves productivity while eliminating time loss associated with manual processing.
Solution Approach 2:
The system enables alarm panels to be self-evaluated through automated data collection and analysis. The computer automatically monitors alarm events, classifies them by type, generates performance data points, and assigns rankings without requiring external manual intervention, allowing the system to serve itself in the analysis process.
2Measurement precision
If comprehensive alarm event data is collected and analyzed for each alarm panel, then classification accuracy improves, but the device complexity increases
Solution Approach 1:
The patent segments the complex analysis task into distinct modular components: receiving alarm events, identifying alarm types, generating data points for each alarm panel, computing Pareto frontiers, determining statistical dividers, and assigning rankings. This segmentation of the data processing workflow into discrete steps manages complexity while maintaining high classification accuracy through systematic analysis.
Solution Approach 2:
The patent introduces intermediate data structures including data points that represent alarm panel performance, Pareto frontiers that capture optimal performance boundaries, and statistical dividers that partition the data space. These intermediaries serve as mediators between raw alarm events and final classifications, simplifying the overall processing complexity while preserving measurement precision.
Data Source
AI summary
Systems and methods for alarm panel analysis include receiving a plurality of alarm events from the respective alarm panels monitoring corresponding buildings. An alarm analysis system may classify the alarm panels by identifying an alarm type for the alarm events. The alarm analysis system may determine a number of occurrences of each alarm type for the alarm panels, and generate a data point for a dataset for the alarm panels. The alarm analysis system may identify statistical dividers in the data points for the data set, which may be used for assigning a ranking for the alarm panels based on their location in relation to the statistical dividers. The alarm analysis system may construct and a monitoring dashboard which includes the rankings of the alarm panels, which may be rendered on a display to an end user.