Indoor Subject Tracking With Hybrid VLC Positioning
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Solution Overview
Problem
Existing Visual Light Communication (VLC) systems for indoor tracking, such as self-scanners, often fail to provide accurate positioning data due to factors like the self-scanner being left behind or occlusion, leading to inefficiencies in shopping and data analysis in commercial spaces.
Innovation Solution
A system and method utilizing a scanning device and a mobile device connected via VLC, with a processor that dynamically switches between tracking via the scanning device and mobile device based on predetermined conditions, ensuring accurate positioning by leveraging both devices' data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If VLC-based self-scanner is used for tracking, then positioning capability is provided, but positioning accuracy deteriorates when self-scanner is left behind or occluded
Solution Approach 1:
The patent combines VLC-based self-scanner positioning with mobile device positioning systems into a hybrid tracking system. The processor integrates position information from the self-scanner with position data from the mobile device, allowing the system to maintain accurate tracking even when one device becomes unavailable due to occlusion or being left behind.
Solution Approach 2:
The system dynamically switches between relying on self-scanner position information and mobile device position information based on predetermined conditions. The processor monitors the reliability of each source and adapts the positioning strategy in real-time, transitioning from self-scanner-only to mobile device supplementation when accuracy deteriorates.
2Measurement precision
If mobile device is continuously used for positioning, then positioning accuracy is maintained, but battery consumption increases
Solution Approach 1:
The mobile device's positioning capabilities are activated partially rather than continuously. The system uses the mobile device only when predetermined conditions indicate that the self-scanner positioning is insufficient or unavailable, reducing overall energy consumption while maintaining positioning accuracy when needed.
Solution Approach 2:
The system primarily relies on the self-scanner for positioning, which does not consume the user's mobile device battery. The mobile device serves as a supplementary resource that activates only when necessary, allowing the main positioning function to be self-sufficient without continuous external power consumption.
3Productivity
If self-scanner is used for tracking, then shopping efficiency is improved, but tracking reliability deteriorates when device is left in shopping cart
Solution Approach 1:
The mobile device acts as an intermediary backup when the self-scanner is left in the shopping cart. The processor detects when the self-scanner is stationary for extended periods and transitions to using the mobile device's positioning data, ensuring continuous tracking reliability without interrupting the shopping workflow.
Solution Approach 2:
The system prepares for potential self-scanner unavailability by having the mobile device positioning capability ready as a pre-arranged backup. This cushioning approach ensures that if the self-scanner is left behind, the tracking function seamlessly transitions to the mobile device without loss of reliability.
4Measurement precision
If hybrid positioning system is implemented, then positioning accuracy is improved, but system complexity increases
Solution Approach 1:
The processor is designed to handle multiple positioning functions universally, managing both self-scanner VLC positioning and mobile device positioning through a single integrated component. This multi-functionality reduces the need for separate dedicated systems and simplifies the overall architecture despite the hybrid nature of the positioning approach.
Solution Approach 2:
The system changes operational parameters based on conditions, switching between different positioning modes rather than maintaining a permanently complex hybrid system. The processor adjusts which positioning source is active based on predetermined conditions, effectively simplifying the system state at any given moment while maintaining the capability for high accuracy when needed.
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
Enhances positioning accuracy by adapting tracking to the device in use, conserving battery life, and minimizing privacy concerns while improving data analysis for customer behavior and staff scheduling.
Implementation Method 1
a plurality of light sources, wherein each light source of the plurality of light sources is configured to emit modulated illumination
Data Source
AI summary
A system (100) and method (500) for tracking a position of a subject (110) in an indoor space (120) are provided. The system comprises light sources (130) configured to emit modulated illumination, a scanning device (140) configured to receive the modulated illumination and obtain position information of the scanning device, a wireless communication system (160), a mobile device (170) arranged to be portable by the subject and connectable to the wireless communication system, wherein the mobile device is configured to generate its position data (180) via the wireless communication system, wherein a processor (200) of the system, as a function of at least one predetermined condition (230a-e), is configured to, register a position of the subject based on a position of the scanning device, or obtain position data of the mobile device, and/or register a position of the subject based on the position data of the mobile device.