Location Probability Surfaces for Wireless Proximity Estimation
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Solution Overview
Problem
Existing methods for determining proximity between wireless devices are prone to noise in signal strength measurements, leading to inaccurate location estimation and increased risk of exposure to infectious diseases, such as COVID-19, as they rely on triangulation-based methods that are susceptible to errors.
Innovation Solution
The use of location probability surfaces (LPS) that aggregate probabilities across multiple devices and mitigate noise by calculating expected signal strengths and comparing them to measured signal strengths, allowing for more accurate proximity estimation between wireless devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If triangulation-based methods are used to determine location of wireless devices, then location determination capability is provided, but measurement precision deteriorates due to noise in signal strength measurements
Solution Approach 1:
The patent segments the location determination problem into multiple independent probability surfaces, each corresponding to a different wireless device. Instead of relying on a single triangulation calculation that is sensitive to noise, the system creates multiple location probability surfaces that can be independently evaluated and aggregated, reducing the impact of individual measurement errors on the final exposure risk assessment.
2Ease of operation
If signal strength measurements are used for proximity determination, then wireless location capability is enabled, but measurement precision deteriorates due to noise
Solution Approach 1:
The patent merges multiple signal strength measurements from different wireless devices into a composite location probability surface. By combining information from multiple sources and aggregating the resulting probability surfaces, the system achieves more reliable proximity determination that is less susceptible to noise in individual signal strength measurements.
3Measurement precision
If location probability surfaces aggregate probabilities across multiple devices, then measurement precision improves for proximity estimation, but device complexity increases
Solution Approach 1:
The patent introduces a probability dimension to the location determination process. Instead of working with single-point location estimates in two-dimensional space, the system creates three-dimensional probability surfaces where the vertical dimension represents the likelihood of being at a particular location. This dimensional transformation allows for more accurate proximity estimation while managing complexity through standardized mathematical operations.
Data Source
AI summary
Disclosed are embodiments for estimating risk associated with a user of a wireless device. In some embodiments, the risk relates to a risk of infection by a contagious disease. For example, in some embodiments, the contagious disease is Coronavirus 2019. In some embodiments, locations of multiple wireless devices are estimated based on signal strengths of signals associated with the devices. Neighboring devices are identified based on highest probability regions of the devices that are determined based on associated signals. A measure of proximity to other devices is then determined based on probabilities that each device is located in neighboring regions. The risk is then based on the measure of proximity. In some embodiments, a risk of a first user associated with a first wireless device is based, in part, on a risk of a second user within a proximity of the first user.