Context-Aware IR Sensor System for False Alarm Reduction
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Solution Overview
Problem
Existing presence detection and localization systems using infrared (IR) sensors face challenges in distinguishing between known and unknown IR sources, leading to false positives and inefficient alarm management in indoor environments.
Innovation Solution
A context-aware IR sensing system employing multiple IR sensors with overlapping fields of view and a controller that generates alarms based on IR source identification, using a look-up table to differentiate between known and unknown sources by analyzing IR source location, intensity, and temporal characteristics, thereby reducing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional IR sensors are used for presence detection, then detection capability is provided, but false positives occur due to inability to distinguish known and unknown IR sources
Solution Approach 1:
The system performs preliminary learning during an initial period to build a database of known IR sources (appliances, furniture, people) before normal detection begins. This preliminary action enables the system to distinguish between familiar and unfamiliar sources, eliminating false positives from known objects while maintaining reliable detection of actual intruders.
Solution Approach 2:
The system continuously compares detected IR sources against the learned database and provides feedback by either confirming safe conditions or triggering alarms. This feedback mechanism allows the system to adapt and improve its discrimination capability over time, maintaining high reliability while reducing false positives through iterative learning and comparison.
2Reliability
If multiple IR sensors are deployed to improve detection coverage, then detection capability increases, but system complexity increases
Solution Approach 1:
The system divides the detection space into multiple zones covered by different IR sensors, with each sensor independently monitoring its own field of view. This segmentation allows comprehensive coverage while keeping individual sensor processing simple, as each sensor only needs to detect presence in its own zone rather than processing data from all sensors.
Solution Approach 2:
The system merges the detection results from multiple IR sensors into a unified decision-making process. By combining the simple detection outputs from multiple sensors with the learned database comparison, the system achieves comprehensive coverage without requiring complex individual sensor processing, thus managing overall system complexity effectively.
3Reliability
If the system learns and adapts to environment changes, then false positives are reduced, but processing time and computational load increase
Solution Approach 1:
The system performs the computationally intensive learning process during an initial setup period before normal operation begins. This preliminary action builds the database of known IR sources in advance, so that during normal detection only simple pattern matching against the pre-built database is required, minimizing real-time processing time and computational load while maintaining high reliability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively reduces false positives by learning the indoor environment context and adapting to changes, ensuring accurate detection of foreign IR sources while ignoring known sources, thus improving presence detection accuracy and reducing unnecessary alarms.
Implementation Method 1
receiving IR radiation with a plurality of IR sensors having a plurality of respective field-of-views; producing a plurality of output signals with the plurality of IR sensors based on the received IR radiation
Implementation Method 2
Thermal-based sensors include pyroelectric infrared (PIR) sensors
Implementation Method 3
Thermopiles may be implemented with series-connected thermocouples and generate a voltage based on the difference between the IR radiation of objects in its FoV and IR radiation from the ambient
Data Source
AI summary
A method includes: receiving IR radiation with a plurality of IR sensors; producing a plurality of output signals with the plurality of IR sensors based on the received IR radiation, where each of the plurality of output signals is indicative of an intensity of the IR radiation received by a respective IR sensor of the plurality of IR sensors; detecting an IR source based on the plurality of output signals; generating a candidate alarm in response to detecting the IR source; determining whether the detected IR source matches any reference IR source of a set of reference IR sources; when the detected IR source matches one reference IR source of the set of reference IR sources, issuing a user alarm, and when the detected IR source does not match any reference IR source of the set of reference IR sources, canceling the candidate alarm without issuing the user alarm.