People Counting Camera with BLE Receiver for Employee Exclusion
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Solution Overview
Problem
Conventional people counting and tracking systems inaccurately differentiate between employees and customers, leading to skewed analytical results in retail and similar environments, as they fail to effectively exclude employee traffic from customer analytics.
Innovation Solution
A system utilizing a people counting camera equipped with a wireless signal receiver, such as a Bluetooth Low Energy (BLE) receiver, to identify and track wireless devices associated with employee identification tags, allowing for the separation of employee and customer counts by predicting wireless signal strengths and characteristics based on tag location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional people counting systems are used to track all people in a facility, then the system provides basic people flow data, but the accuracy of customer analytics deteriorates due to mixing employees and customers
Solution Approach 1:
The patent introduces wireless communication devices as an intermediary layer between the camera system and employee identification. These devices receive wireless signals (Bluetooth, Wi-Fi) from employee mobile devices and provide this information to the surveillance system, enabling differentiation without requiring direct camera recognition of employees versus customers
Solution Approach 2:
The surveillance system is enhanced with multi-functionality by integrating wireless signal reception capabilities alongside traditional video surveillance. This allows the same system to perform both visual monitoring and wireless device detection, enabling employee identification through multiple channels simultaneously
2Measurement precision
If wireless signal receivers are added to differentiate employees from customers, then customer analytics accuracy improves, but device complexity increases
Solution Approach 1:
The patent merges the wireless signal reception functionality directly into the existing surveillance camera system. By combining video surveillance and wireless signal detection in a single integrated device, the system avoids the need for separate wireless receivers positioned throughout the facility, thereby reducing overall system complexity while maintaining differentiation accuracy
Solution Approach 2:
The surveillance system is enhanced with multi-functionality by integrating wireless signal reception capabilities alongside traditional video surveillance. This allows the same system to perform both visual monitoring and wireless device detection, enabling employee identification through multiple channels simultaneously
3Measurement precision
If multiple sensor types are integrated into the surveillance system, then identification accuracy improves, but cost and manufacturing complexity increase
Solution Approach 1:
The surveillance system is enhanced with multi-functionality by integrating wireless signal reception capabilities alongside traditional video surveillance. This allows the same system to perform both visual monitoring and wireless device detection, enabling employee identification through multiple channels simultaneously
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
The system provides more accurate customer analytics by accurately distinguishing between employees and customers, improving the reliability of data used for operational decisions in retail and other environments.
Implementation Method 1
a people counting camera equipped with a wireless signal receiver (e.g., a Bluetooth Low Energy (BLE) signal receiver) operable to receive wireless signals
Data Source
AI summary
Various techniques are provided for counting and/or tracking objects within a field of view of an imaging system, while excluding certain objects from the results. A monitoring system may count or track people identified in captured images while utilizing an employee identification system including a wireless signal receiver to identify and remove the employees from the result. The system includes algorithms for separating employee counts from customer counts, thereby offering enhanced tracking analytics.