PIR Sensor Self-Learning False Trigger Reduction
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Solution Overview
Problem
Passive infrared (PIR) sensors are prone to false triggers, leading to unnecessary energy consumption due to false positive and false negative detections, which are difficult to predict and often occur in specific environmental conditions.
Innovation Solution
A method of controlling PIR sensors using multiple sensor elements with processing units and memory to correlate presence detection events, adjust detection thresholds, and implement time delays to differentiate between true and false triggers, allowing the system to self-learn and adapt to its environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor elements are used to increase detection range and sensitivity, then the detection capability is improved, but false positive triggers increase due to detecting IR movement from unintended objects like moving trees
Solution Approach 1:
The detection area is divided into multiple sectors, each monitored by a separate sensor element. This segmentation allows the system to analyze the spatial distribution of detected objects and distinguish between genuine targets and false triggers based on their location within specific sectors.
Solution Approach 2:
The system uses feedback from multiple sensor elements to continuously adjust detection thresholds and parameters. By analyzing patterns across all sensor elements over time, the system learns from actual events and adapts to environmental conditions, reducing false positives while maintaining detection accuracy.
2Loss of energy
If PIR sensors are used for presence detection, then energy savings are achieved by controlling electrical devices, but false triggers cause unnecessary energy consumption and equipment operation
Solution Approach 1:
The PIR sensor system performs self-learning and auto-commissioning by automatically analyzing detection patterns from multiple sensor elements and adjusting its own parameters. The system learns from actual events over time, adapting to the specific environment without manual intervention, thereby reducing false triggers and optimizing energy savings automatically.
3Measurement precision
If detection thresholds are lowered to improve sensitivity, then more presence events are detected, but false positive triggers from environmental factors increase
Solution Approach 1:
The detection thresholds are made dynamic rather than static. The system continuously adjusts thresholds based on patterns detected across multiple sensor elements and environmental conditions. This dynamic adjustment allows the system to maintain high sensitivity while adapting to environmental factors that cause false triggers.
Solution Approach 2:
The system performs preliminary learning during an auto-commissioning phase, establishing baseline detection parameters before normal operation. This preliminary action allows the system to pre-adapt to the specific environment, reducing the likelihood of false positives from environmental factors like moving trees or weather conditions.
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
This approach significantly reduces false triggers, conserves energy by optimizing the operation of connected electrical devices, and enhances the robustness of PIR sensors over time by self-learning from actual events.
Implementation Method 1
A false positive trigger scenario is shown in FIG. 2. A nearby object, e.g. a tree is moved by some means, e.g. by the wind. The sensor detects IR movement
Implementation Method 2
A typical PIR sensor consists of lens to focus infrared (IR) energy onto the sensor element
Data Source
AI summary
The invention relates to a method of controlling a passive infrared (PIR) sensor, said sensor controlling if an electrical device is on or off, wherein said PIR sensor has at least two sensor elements, each having a lens focusing IR onto them, control electronics comprising of at least one processing unit and one memory, wherein the at least two sensors cover adjacent cover areas, wherein information of detected presence from said at least two sensor elements are used to decrease false triggers by using the time period between subsequent presence detections, and identification of each of said at least two PIR sensor elements. The invention further relates to a method of controlling a passive infrared (PIR) sensor, said sensor controlling if an electrical device is on or off, wherein said PIR sensor has two or more sensor elements, each having a lens focusing IR onto them, control electronics comprising of at least one processing unit and one memory, wherein two or more sensors cover different sequentially adjacent cover areas, wherein the sensor elements have a threshold for IR detection above which threshold a positive signal of presence is provided from the sensor element, said method comprising the step of provide a signal (Pan) if all sensor elements provide a positive signal of presence during a time period shorter than a predetermined time period (T3), and if (Pall) is detected a predetermined number of times within a second predetermined time period (T4), increase said threshold by a predetermined amount.