Adaptive Sensor Arming Sequence Based on Historical Activity Patterns
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Solution Overview
Problem
Conventional security systems are vulnerable during the arming phase in AWAY mode, as sensors remain unarmed, allowing potential intrusions to go undetected, and the fixed arming time does not account for historical activity patterns, leading to inefficient security and potential false alarms.
Innovation Solution
A smart security system that captures and analyzes data from network-connected sensors to determine a customized arming order and timing based on historical activity, adjusting sensor arm times dynamically to enhance security and reduce vulnerability during the arming phase.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are armed immediately when security system is switched to AWAY mode, then security response time is improved, but false alarms increase due to not accounting for historical activity patterns
Solution Approach 1:
The system performs preliminary analysis of historical activity data before arming sensors. It calculates predicted arm times based on past patterns of when sensors were last triggered, and uses this information to determine the optimal arming sequence, preventing false alarms while maintaining security readiness.
Solution Approach 2:
The system dynamically adjusts the arming sequence and timing of individual sensors based on historical activity patterns. Instead of a fixed arming order, it calculates customized arm times for each sensor based on when they were last triggered in the past, making the security system adaptive to actual usage patterns.
2Device complexity
If a fixed arming time is used for all sensors, then system complexity is reduced, but security effectiveness deteriorates due to inability to account for varying activity patterns at different locations
Solution Approach 1:
The system applies local quality by assigning different arm times to different sensors based on their specific historical activity patterns. Each sensor's arming time is customized according to its location and usage history, rather than applying a uniform arming time across all sensors, thereby improving security effectiveness without significantly increasing complexity.
Solution Approach 2:
The system changes the parameter of arm time from a fixed value to a dynamically calculated value based on historical data. It computes predicted arm times for each sensor by analyzing when they were last triggered, and uses these calculated parameters to optimize the arming sequence, improving security effectiveness while maintaining manageable system complexity.
3Ease of operation
If sensors are armed in a predetermined fixed order, then ease of operation is improved, but vulnerability during arming phase increases due to not matching actual usage patterns
Solution Approach 1:
The system performs preliminary calculation of optimal arm times for each sensor based on historical activity data before the arming process begins. This preliminary analysis determines the sequence and timing that minimizes vulnerability, while the actual arming operation remains automated and simple to execute.
Solution Approach 2:
The system determines its own arming sequence automatically based on historical patterns without requiring manual configuration or user intervention. It uses its stored historical data to self-optimize the arming order, reducing vulnerability while maintaining ease of operation through automated decision-making.
Data Source
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Figure 5A
AI summary
A security system includes a plurality of sensors installed at a premises to capture data from an environment in or around the premises, a memory configured to store data captured spanning at least a first period of time, and a processor configured to arm the plurality of sensors in an order determined based on a history of detected activity in the premises as indicated by the stored data.