Occupancy Detection System with Adaptive Timeout
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional occupancy sensors often experience false triggering events due to ambient noise and limitations in detecting human presence, particularly at distances beyond their reliable range, leading to inefficient energy management and lighting control.
Innovation Solution
An occupancy detection system utilizing statistical algorithms, specifically second-order statistical equations, to adjust sensor parameters, including a motion detector and sound detectors, which automatically adapt timeout periods based on Gaussian probability distribution analysis, ensuring accurate detection and minimizing false triggers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional occupancy sensors are used with fixed sensitivity parameters, then the device complexity is low, but false triggering events increase due to ambient noise and distance variations
Solution Approach 1:
The patent implements dynamic sensitivity adjustment where the occupancy sensor automatically adapts its detection parameters based on environmental conditions. The system monitors ambient noise levels and distance variations, then dynamically modifies sensitivity thresholds to maintain optimal detection accuracy without requiring manual intervention or complex fixed-parameter configurations.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor detection events and environmental conditions. Based on this feedback, the sensor automatically adjusts its sensitivity parameters to reduce false triggering. The feedback loop analyzes patterns in detected occupancy events and ambient conditions, then fine-tunes detection thresholds to improve reliability while maintaining system simplicity.
2Area of stationary object
If the timeout period is extended to accommodate distant occupants, then detection coverage is improved, but energy consumption increases due to prolonged lighting operation
Solution Approach 1:
The patent applies different timeout periods for different zones within the detection area. Occupants detected in zones closer to the sensor trigger shorter timeout periods, while those in more distant zones trigger extended timeouts. This spatially differentiated approach ensures adequate lighting for distant occupants while minimizing energy consumption for areas where occupants are present for brief periods.
Solution Approach 2:
The system dynamically changes the timeout parameter based on the detected occupancy pattern and environmental conditions. When occupancy is detected at greater distances or in areas historically associated with longer停留 times, the timeout period is automatically extended. Conversely, for close-range detections or areas with typical brief occupancy, the timeout is reduced, optimizing energy consumption while maintaining detection effectiveness.
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 triggering by dynamically adjusting sensor sensitivity and timeout periods, enhancing the accuracy of detecting human presence and managing lighting control more efficiently, thereby improving energy conservation and user experience.
Implementation Method 1
Passive infrared (PIR) sensors are considered to be the most common type of occupancy sensor. They are able to 'see' heat emitted by occupants
Implementation Method 2
Both methods rely on processing Doppler shifts between the frequency of the transmitted and reflected signals
Implementation Method 3
Both methods rely on processing Doppler shifts between the frequency of the transmitted and reflected signals
Implementation Method 4
The Fresnel lenses focus a projection of the defined area on the PIR element
Data Source
AI summary
An occupancy detection system includes a motion detector, one or more sound detectors and a lighting controller configured to turn on and off one or more lighting devices in a defined area based on detected occupancy states. Lighting control circuitry determines occupancy states based on motion detector output signals and sound detector output signals, and further controls associated lighting devices to be turned ON or OFF in accordance with determined occupancy states and an automatically adaptable timeout period. The timeout period is automatically adjusted in accordance with newly recorded time stamps for lighting status changes, based on a second order occupancy distribution analysis such as a Gaussian probability distribution function, with an occupancy curve adjusted for each newly recorded set of time stamps and the timeout period being adjusted according to the mean and variance of the occupancy curve.