Multi-Sensor Intrusion Detection with Normalized Threat Aggregation
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Solution Overview
Problem
Existing security systems generate false alarms due to environmental changes, human error, and pets moving within protected areas, leading to resource wastage and potential penalties, as they rely on binary decision processes that do not account for raw data below detector thresholds.
Innovation Solution
A security apparatus comprising multiple sensing elements, a signal processing section, a computing section, and an alarm generating section that translates sensing signals into normalized threat values, adjusts them with weighting coefficients, and generates an alarm enable signal based on an aggregate threat value compared to a master threshold, while incorporating aging factors and scaling factors to reduce false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a binary decision process is used for alarm detection, then the system is simple to operate, but false alarms increase due to environmental changes and pets
Solution Approach 1:
The patent transforms the binary alarm detection into a continuous threat level assessment by introducing normalized threat values that range from 0 to 1. Instead of simple on/off sensor states, the system uses scaled and weighted threat values that can take any value within the range, allowing for nuanced differentiation between benign environmental events and actual intrusions. This parameter transformation enables the system to reduce false alarms while maintaining operational simplicity.
Solution Approach 2:
The patent adds a dimensional transformation by converting sensor outputs into normalized threat values that exist on a continuous scale rather than binary states. This dimensional change from discrete (0/1) to continuous (0-1) space allows the system to capture the intensity and probability of threat events, providing a more sophisticated basis for alarm generation that accounts for environmental variations and reduces false positives.
2Measurement precision
If sensor sensitivity is increased to detect all potential intrusions, then detection capability improves, but false alarms increase due to environmental changes
Solution Approach 1:
The patent implements dynamic threat level assessment by continuously monitoring and comparing sensor outputs against adaptive thresholds. The system dynamically adjusts the alarm generation decision based on the cumulative normalized threat values and their rates of change, allowing high sensitivity to actual intrusions while dynamically filtering out false alarms from environmental changes through adaptive threshold comparison.
Solution Approach 2:
The system employs feedback mechanisms where the normalized threat values and their changes are continuously fed back into the alarm generation decision process. This feedback loop allows the system to learn from patterns and adjust its sensitivity dynamically, maintaining high detection capability for actual intrusions while reducing false alarms through continuous adaptive threshold comparison.
3Reliability
If multiple sensors are used to improve detection accuracy, then the system becomes more complex, but the complexity management becomes difficult
Solution Approach 1:
The patent segments the complex multi-sensor system into independent sensor modules, each producing its own normalized threat value. This segmentation allows each sensor to be processed independently through standardized normalization and weighting procedures, reducing the complexity of integrating multiple sensor types while maintaining high detection accuracy through the aggregation of individual sensor assessments.
Solution Approach 2:
The patent creates a universal processing framework that handles multiple sensor types through a common normalization and weighting mechanism. This universal approach allows different sensor modalities (motion, acoustic, visual) to be processed using the same mathematical operations and decision criteria, simplifying system complexity management while improving detection accuracy through multi-sensor fusion.
Data Source
AI summary
A security apparatus comprising a plurality of sensing elements, each adapted to detect intrusion into protected premises, each sensing element outputs a sensing signal representing a detected event, a signal processing section for examining each sensing signal and outputting a signature for each sensing signal, a computing section for translating each signature into a normalized threat value, ranging from “0” to “1”, modifying each normalized threat values by multiplying a weighting coefficient corresponding to a type of sensing element, storing for a temporary period of time, each modified normalized threat value, and an alarm generating section for adding each of the stored modified normalized threat values, outputting an aggregate threat value and generating an alarm enable signal based upon an analysis of the aggregate threat value.