Customer Flow Counting Using Video and WiFi Segmentation
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Solution Overview
Problem
Existing methods for monitoring customer flow volume inaccurately count personnel entering and exiting a site, leading to distorted statistical results due to inability to differentiate between customers and non-customer personnel, such as store clerks, resulting in incorrect decision-making.
Innovation Solution
A method and device that utilize video analysis and WiFi terminal identifiers to determine the movement direction of individuals within a monitoring area, adjusting customer flow volume statistics by subtracting or adding counts based on the presence of non-customer personnel, ensuring accurate tracking of customer flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If video analysis is used to count all persons entering/exiting, then the detection coverage is improved, but the measurement precision deteriorates due to inability to differentiate customers from non-customer personnel
Solution Approach 1:
The patent segments the detected personnel into different categories (customers vs. non-customer personnel) by extracting and comparing terminal identifiers. This segmentation allows the system to count only relevant personnel (customers) while excluding others (clerks, delivery personnel), thereby improving measurement precision without reducing detection coverage.
Solution Approach 2:
The patent introduces terminal identifiers (WiFi/MAC addresses) as an intermediary to differentiate between customers and non-customer personnel. By using this intermediary information, the system can accurately identify and filter personnel types, resolving the contradiction between comprehensive detection and precise measurement.
2Measurement precision
If terminal identifier detection is added to differentiate personnel types, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent makes the monitoring system multi-functional by integrating both video analysis and terminal identifier detection capabilities into a single system. The terminal detection module serves multiple purposes: identifying personnel types, tracking customer flow, and providing data for analysis, thereby managing complexity through functional integration rather than adding separate independent systems.
Solution Approach 2:
The system uses existing terminal identifiers (WiFi MAC addresses) that are already present in the environment, eliminating the need for additional specialized identification hardware. By leveraging these pre-existing identifiers, the system achieves precise personnel differentiation without significantly increasing device complexity.
Data Source
AI summary
A statistical method and device for customer flow volume. The method comprises: obtaining video image information in a preset monitoring area; performing video analysis on the video image information and determining a movement direction of a first target person appearing in the preset monitoring area according to an analysis result; obtaining, through statistics, incoming or outgoing customer flow volume of the actual detection area according to the determined movement direction of the first target person; reading a first terminal identifier, detected by a WiFi detector, of a WiFi terminal apparatus carried by the first target person; judging whether the first terminal identifier is present in a preset terminal identifier database for non-customer personnel; if so, decreasing the incoming or outgoing customer flow volume by 1; otherwise, making no change to the incoming or outgoing customer flow volume.