Occupancy Sensing with Dynamic Thresholds and Motion Analysis
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Solution Overview
Problem
Existing occupancy sensing systems, such as passive infrared (PIR) sensors, often inaccurately detect motion, leading to unnecessary light activation or deactivation, and are not suitable for advanced workspaces requiring precise occupancy determination.
Innovation Solution
A motion sensor system that operates in high and low threshold modes, adjusts thresholds based on motion signals, uses human-like motion analysis, and incorporates multiple sensors with calibration tools to enhance accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional PIR sensors are used for occupancy sensing, then the system is simple and low cost, but the occupancy detection accuracy is insufficient leading to false positives and negatives
Solution Approach 1:
The patent divides the occupancy sensing function into multiple independent sensor components (motion sensor, presence sensor, occupancy sensor) that work together. Each sensor type detects different aspects of occupancy, and their combined output provides accurate occupancy determination while maintaining individual sensor simplicity and low cost.
2Adaptability or versatility
If a single threshold is used for motion detection, then the system is simple to operate, but it cannot adapt to varying motion conditions leading to inaccurate occupancy determination
Solution Approach 1:
The patent implements dynamic threshold adjustment where the motion detection threshold automatically adapts based on environmental conditions and sensor inputs. The system transitions from static to dynamic threshold operation, allowing it to respond appropriately to varying motion conditions without requiring manual reconfiguration or complex user intervention.
3Measurement precision
If motion threshold is lowered to detect subtle movements, then sensitivity increases, but false positives increase due to environmental noise
Solution Approach 1:
The patent combines multiple sensor types (motion sensor, presence sensor, occupancy sensor) to detect occupancy conditions. By merging the outputs of these sensors, the system achieves high sensitivity to subtle human movements while maintaining reliability through cross-validation among multiple sensor inputs, filtering out environmental noise that would trigger false positives in a single-sensor system.
Data Source
AI summary
The present disclosure provides systems and methods for improved occupancy sensing. The methods and systems can deploy various signal threshold adjustments and/or signal analysis algorithms in response to sensed signals having a given quality, such as exceeding a threshold. In some cases, signal thresholds are lowered following an initial generated signal exceeding a first, higher threshold. In some cases, time-dependent signals are monitored using algorithms that analyze the signals for variations that are characteristic of human usage. Methods are disclosed for determining if two motion sensors are observing the same or overlapping spaces. Systems and methods for calibrating motion sensing systems are also disclosed.