Occupancy tracking using user device detection
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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 environmental information, such as audio signals, user device detection, and wireless signal strength, to predict the number of people in a space and adjust HVAC settings accordingly.
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 applies multi-functionality by using a single sensor system (camera or display sensor) to perform multiple functions: detecting occupancy, determining the number of people, and identifying who is present. This replaces the need for separate sensors for each function, allowing the HVAC system to gain comprehensive occupancy information without proportionally increasing system complexity
Solution Approach 2:
The patent uses an intermediary processing system that analyzes sensor data (camera images or display sensor readings) to extract occupancy information. This intermediary layer processes the raw sensor data to determine both the number of people and their identities, bridging the gap between simple presence detection and detailed occupancy analysis
2Ease of operation
If existing HVAC systems use binary occupancy detection, then the system operation is simple, but the system cannot provide personalized HVAC settings for different occupants
Solution Approach 1:
The patent applies dynamics by making the HVAC system adaptive and flexible in its operation. Instead of fixed binary control, the system dynamically adjusts HVAC settings based on real-time occupancy information, including the number of people and their identities. This allows the system to transition between simple and complex modes as needed, maintaining ease of operation while enabling personalized control when occupants are present
3Measurement precision
If the system uses audio signals to detect occupancy, then it can determine the number of people by detecting voices, but it may incorrectly identify voices from electronic devices as human voices
Solution Approach 1:
The patent applies partial action by using audio detection as one of multiple occupancy detection methods rather than relying on it exclusively. The system performs audio analysis to detect voices but combines this with other sensor data (camera, display sensors, proximity sensors) to verify occupancy. This partial use of audio detection maintains its benefits while mitigating its limitations through sensor fusion
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
Enables more accurate occupancy detection, allowing for personalized temperature control and improved energy management by distinguishing between people and electronic devices, leading to enhanced comfort and efficiency.
Implementation Method 1
a signal strength of a network connection between a thermostat and an access point. The occupancy tracking system monitors the signal strength of the network connection over time to determine the number of people that are present within the space based on the measured signal strength
Data Source
AI summary
An occupancy tracking device configured to identify devices connected to an access point over a predetermined time period. The device is further configured to populate entries in a device log for the identified devices. The device is further configured to determine a presence value for each device that indicates an amount of time that a device was present during the predetermined time period. The device is further configured to identify entries that are associated with a presence value that is less than a presence threshold value and to associate the entries with a user device classification. The device is further configured to identify clusters for the entries that are associated with a user device classification, 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.