Occupancy Sensor Network Acoustic Signal Processing
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Solution Overview
Problem
Existing electrical control systems for lighting, particularly occupancy sensors, face challenges in accurately detecting occupancy and efficiently controlling lighting systems due to noise interference and variability in acoustic signals, leading to false positives and negatives.
Innovation Solution
An occupancy sensor system incorporating an acoustic transmitter, receiver, variable band-pass filter, and controller that transmits and processes acoustic signals to determine occupancy by sweeping the band-pass filter across frequencies, time-averaging amplitudes, and comparing variations to distinguish between occupancy and noise, while preventing signal clipping and adjusting filter settings for optimal performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the occupancy sensor uses acoustic signals to detect occupancy, then the detection range and coverage are improved, but noise interference increases causing false positives and negatives
Solution Approach 1:
The acoustic spectrum is segmented into multiple frequency bands using a bank of bandpass filters. Each filter processes a specific frequency range, allowing the system to analyze different spectral components separately. This segmentation enables the system to identify occupancy-related acoustic patterns while filtering out noise in specific frequency ranges, thereby improving detection accuracy despite noise interference.
Solution Approach 2:
A network of multiple occupancy sensors acts as intermediaries to cross-validate occupancy detections. When one sensor detects potential occupancy, other sensors in the network verify the detection by analyzing the same acoustic environment from different positions. This intermediary verification mechanism reduces false positives and negatives caused by localized noise interference.
2Measurement precision
If the sensor processes acoustic signals across multiple frequencies, then the ability to distinguish occupancy from noise improves, but the processing complexity and computational load increase
Solution Approach 1:
The complex task of analyzing the entire acoustic spectrum is segmented into multiple simpler parallel tasks, each handling a specific frequency band. This segmentation allows the system to process frequencies in parallel rather than sequentially, reducing the computational complexity of each individual processing task while maintaining comprehensive spectral analysis for accurate occupancy discrimination.
Solution Approach 2:
The system employs periodic sweeping of the bandpass filter across the acoustic frequency spectrum rather than continuously processing all frequencies simultaneously. The filter sweeps through different frequency bands in a periodic manner, analyzing each band for a predetermined time period. This periodic action reduces the instantaneous processing load while still providing comprehensive spectral coverage over time, thereby distinguishing occupancy from noise without excessive computational complexity.
3Adaptability or versatility
If the band-pass filter sweeps across all frequencies, then the detection of varying signal conditions improves, but the response time to detect occupancy increases
Solution Approach 1:
The frequency spectrum is segmented into multiple bands that can be processed in parallel. Instead of sweeping through all frequencies sequentially, the system divides the spectrum into concurrent processing channels, each handling a specific frequency range. This segmentation enables simultaneous analysis of multiple frequency bands, maintaining comprehensive spectral coverage for adapting to varying signal conditions while significantly reducing the time required to detect occupancy across the full frequency range.
4Reliability
If the system uses multiple occupancy sensors in a network, then the reliability and accuracy of occupancy detection improve, but the system cost and installation complexity increase
Solution Approach 1:
Multiple occupancy sensors are merged into a unified networked system that shares processing resources and data. The sensors communicate with each other and a central controller, combining their detection capabilities to achieve higher reliability through cross-validation. This merging approach allows the system to maintain high detection reliability while managing installation and configuration complexity through standardized communication protocols and centralized management.
Solution Approach 2:
The occupancy sensor network implements feedback mechanisms where each sensor's detection results are communicated to other sensors and the central controller. The system uses this feedback to verify detections, eliminate false positives, and adapt to changing environmental conditions. This feedback loop enhances reliability by allowing the network to collectively validate occupancy detections while providing a structured framework that simplifies the overall system configuration and management.
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 readings and improves accuracy in detecting occupancy, enabling efficient control of lighting systems by filtering out noise and adapting to varying signal conditions, thus enhancing energy management and user comfort.
Implementation Method 1
transmit acoustic signals using an acoustic transmitter
Implementation Method 2
receive acoustic signals using an acoustic receiver
Implementation Method 3
filter the acoustic signals using a variable band-pass filter
Data Source
AI summary
An occupancy sensor includes an acoustic transmitter and an acoustic receiver each operably coupled to a controller. The sensor further includes a communication interface operably coupled to the controller and capable of transmitting and receiving communication signals to and from a communication network through the communication interface. The sensor also includes memory for storing operation aspects, such as a network address associated with the sensor, information representative of data corresponding to the defined region monitored by the sensor, an office plan location for the sensor, and an operating schedule for the sensor. One or more operational aspects of the occupancy sensor may be adjusted through the use of a remote control or a local control at the sensor. The occupancy sensor processes acoustic and/or infrared signals to determine the presence or absence of an occupant within a defined region.