Wireless Presence Detection Using Signal Parameter Analysis
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Solution Overview
Problem
Existing methods for determining presence based on wireless device connection or disconnection are often inaccurate due to false predictions, as connections can be disrupted by factors unrelated to presence.
Innovation Solution
Implementing multiple point sampling and analysis of communication parameters such as signal strength and RF band switching to determine presence, reducing false detections by considering patterns and rates of change in these parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If presence is determined based on wireless device connection or disconnection status, then the detection method is simple, but the accuracy of presence detection deteriorates due to false predictions
Solution Approach 1:
The patent changes from using a single binary parameter (connection status) to using multiple continuous parameters (signal strength, data rate, channel quality) that vary continuously as the device moves. This allows for more nuanced detection of presence events by analyzing patterns of parameter changes rather than simple connection states.
Solution Approach 2:
The patent adds temporal and spatial dimensions to the detection process by analyzing rates of change and patterns over time. Instead of looking at a single snapshot of connection status, the system examines how parameters evolve over time sequences, adding a temporal dimension that helps distinguish true presence events from false predictions.
2Measurement precision
If multiple communication parameters are analyzed to improve presence detection accuracy, then false detections are reduced, but the system complexity increases
Solution Approach 1:
The patent segments the detection process into distinct stages: collecting multiple communication parameters, analyzing their rates of change, identifying patterns, and making presence determinations. This segmentation allows the complex task to be broken down into manageable components that can be processed systematically.
Solution Approach 2:
The system uses feedback from multiple communication parameters and their rates of change to continuously refine presence detection. By monitoring how parameters evolve over time and using this feedback to update detection decisions, the system achieves higher accuracy without requiring overly complex hardware, as the complexity is managed through software-based analysis of existing communication data.
Data Source
AI summary
Systems, apparatuses, and methods are described for presence detection of a wireless device in a sensing region. Communication parameters determined by a computing device over one or more periods may be used to generate criteria for determining the occurrence of enter events or leave events. The criteria may comprise, for values of one or more communication parameters, rates of change associated with movement into or out of the sensing region. The criteria may be compared against subsequent data associated with the communication parameters to determine if an enter event or a leave event has occurred.