Voice-Based Occupancy Tracking for Personalized HVAC Control
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Solution Overview
Problem
Existing HVAC systems cannot determine the number of people present in a space, limiting their ability to provide personalized temperature settings and efficient energy management.
Innovation Solution
An occupancy tracking system that uses audio signal processing, device detection, and wireless signal strength analysis to predict the number of people in a space, allowing for personalized HVAC control based on individual preferences and occupancy levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If proximity sensors or motion detection sensors are used to determine occupancy, then the system can detect whether a space is occupied, but it cannot determine the number of people present or identify who is present
Solution Approach 1:
The patent replaces mechanical/proximity sensors with acoustic field-based detection. The system uses microphones to capture audio signals and processes these signals to identify voices, determine occupancy count, and recognize occupants based on voice characteristics. This substitution enables the system to obtain detailed occupancy information (number of people, identity) that proximity sensors cannot provide.
2Adaptability or versatility
If existing HVAC systems use binary occupancy detection, then the system structure remains simple, but it cannot provide personalized HVAC settings for different numbers of occupants or individual occupants
Solution Approach 1:
The patent makes the HVAC system multi-functional by integrating voice-based occupancy detection, occupancy counting, and occupant identification capabilities into the existing HVAC control architecture. The system processes audio signals to simultaneously determine whether space is occupied, how many people are present, and who they are, enabling personalized HVAC settings without requiring entirely separate detection systems.
Solution Approach 2:
The system changes the detection parameter from binary presence/absence to continuous audio signal analysis. By analyzing voice characteristics, frequency ranges, and acoustic patterns in the audio signals, the system derives multiple occupancy parameters (occupancy status, count, identity) from a single audio input channel, enabling personalized control without proportionally increasing hardware complexity.
3Measurement precision
If the system captures audio signals to determine occupancy, then it can identify voices and count people, but it may incorrectly identify voices from electronic devices as human voices
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors audio signals and adjusts its detection algorithms based on learned patterns. By analyzing voice characteristics over time and comparing against known human voice profiles, the system refines its ability to distinguish human voices from electronic device sounds, improving both accuracy and reliability through iterative learning and adaptation.
Data Source
AI summary
An occupancy tracking device configured to receive a plurality of sound samples over a predetermined time period. The device is further configured to compute an audio signature for each sound sample. The device is further configured to populate entries in the voice data log for the sound samples, to identify one or more clusters based on an audio signature that is associated with the populated entries, and to determine a number of clusters that are identified. The device is further configured to determine a predicted occupancy level based on the number of clusters that are identified and to control a Heating, Ventilation, and Air Conditioning (HVAC) system based on the predicted occupancy level.