Mobile Device Count Estimation via Trajectory Normalization
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Solution Overview
Problem
Existing methods for estimating the number of mobile devices fail to accurately account for dynamic population changes due to biases in probe data from mobile devices that generate data at different rates and change session identifiers frequently, leading to overcounting and inaccurate population estimates.
Innovation Solution
A method that normalizes probe data by grouping it by session identifiers, calculating trajectory durations, and expanding trajectory areas to correct for biases, allowing for a more accurate estimation of mobile device counts and population distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional census methods are used to obtain population data, then comprehensive population information can be obtained, but the cost is significant and the data is static and not real-time
Solution Approach 1:
The patent uses mobile device probe data as a copy or proxy for actual population data. Instead of conducting expensive censuses, the system collects location data from mobile devices that carry information about the people using them, creating a cheaper alternative representation of population distribution that can be updated in real-time
Solution Approach 2:
The patent replaces the mechanical census system (physical counting and data collection) with an electronic data processing system that automatically collects and processes mobile device location data. This substitution eliminates the need for manual census operations while providing continuous real-time population information
2Productivity
If mobile device probe data is used to estimate population, then real-time population dynamics can be captured, but biases in probe data generation rates and session identifier changes lead to overcounting
Solution Approach 1:
The patent segments the population estimation problem into distinct analytical components: trajectory identification, duration calculation, and normalization. By dividing the probe data analysis into these segments and applying specific correction factors to each, the system eliminates overcounting biases while maintaining real-time monitoring capabilities
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors probe data patterns, identifies biases in data generation rates and session identifier changes, and applies corrective normalization factors. This closed-loop approach ensures that the population estimates remain accurate despite variations in mobile device behavior
3Productivity
If simple counting of probe data points is used, then the process is simple and fast, but the results are inaccurate due to different data generation rates among mobile devices
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing trajectory information, including duration and normalized values, before final population estimation is needed. This preparation work allows the system to quickly generate accurate population estimates in real-time without performing complex calculations during the actual estimation process
Data Source
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AI summary
A method, system, and apparatus for estimation of a number of mobile devices include receiving one or more probe data points including a location, a session identifier, and a timestamp, constructing a trajectory including the one or more probe data points having a same session identifier, calculating a trajectory duration for the trajectory based on the timestamps of the one or more probe data points, calculating a normalized trajectory from the trajectory duration and a predetermined observation duration, and estimating the number of mobile devices from at least the normalized trajectory. A path of the trajectory is based on the location of the one or more probe data points.