Premises Security System Health Monitoring via Predictive Analysis
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Solution Overview
Problem
Conventional security systems lack health monitoring capabilities, leading to unexpected failures that can go unnoticed until critical, potentially allowing intrusions when users are away from the premises.
Innovation Solution
A system and method for determining operational conditions of premises-based systems, including predictive analysis to modify settings and alert users or monitoring centers before failures occur, using a control unit that manages power, communication, and diagnostic processes to monitor battery levels, signal strengths, and behavioral characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional security systems use simple threshold-based health monitoring, then the system structure remains simple, but the system fails to provide early warnings before critical failures occur
Solution Approach 1:
The system performs preliminary diagnostic procedures and predictive analysis to identify potential failures before they occur. By analyzing operational data trends and predicting future system states, the system provides early warnings allowing proactive maintenance, thus improving reliability without requiring complex real-time intervention mechanisms.
Solution Approach 2:
The monitoring system is segmented into distinct functional modules: operational data collection, diagnostic procedure execution, predictive analysis, and alert generation. This modular segmentation allows the complex monitoring task to be divided into manageable components, each handling specific aspects of system health assessment, thereby improving overall system reliability while maintaining manageable complexity.
2Loss of information
If the system continuously monitors all operational parameters, then early failures can be detected, but the energy consumption and processing load increase
Solution Approach 1:
The system applies partial monitoring by selectively collecting operational data based on diagnostic needs rather than continuously monitoring all parameters at maximum detail. Diagnostic procedures are triggered based on system state and risk assessment, collecting sufficient information to detect potential failures while avoiding the excessive energy consumption of continuous full-scale monitoring.
Solution Approach 2:
The system implements periodic diagnostic procedures instead of continuous monitoring. Operational data is collected and analyzed at scheduled intervals or based on trigger events, allowing the system to maintain adequate situational awareness while consuming less energy compared to continuous real-time analysis of all parameters.
3Reliability
If health monitoring thresholds are set to trigger early alerts, then proactive maintenance is enabled, but false alarms may increase
Solution Approach 1:
The system incorporates feedback mechanisms where alert generation is based on multiple data points and trend analysis rather than simple threshold crossing. Predictive analysis evaluates the likelihood of actual failure based on historical data and current operational patterns, providing feedback that helps distinguish between genuine threats requiring attention and normal variations that would trigger false alarms.
Solution Approach 2:
The system dynamically adjusts monitoring parameters and alert thresholds based on system state, environmental conditions, and historical performance data. By changing parameters adaptively rather than using fixed thresholds, the system can maintain high sensitivity for detecting real issues while reducing false alarms caused by normal operational variations under different conditions.
Data Source
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AI summary
An apparatus and method for determining at least one operational condition of a premises based system including at least one premises device. The apparatus includes a processor configured to perform a diagnostic procedure. The diagnostic procedure includes determining operational data of the premises based system, the operational data indicating at least one of a premises device and the apparatus is operating outside a failure range and performing predictive analysis based at least in part on the received operational data. The predictive analysis indicates whether the at least one of premises device and apparatus is likely to operate within the failure range within a predefined period of time. The diagnostic procedure includes causing a notification alert to be transmitted to at least one of a user interface device and remote monitoring center based on the predictive analysis.