Indoor Asset Location Sensing with Environment Tags
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Solution Overview
Problem
Existing location-sensing technologies, such as GPS, RADAR, and Cricket Location Support System, are limited in accuracy and functionality for indoor asset tracking, often requiring extensive manual intervention and failing to account for signal strength variations among tags, leading to inaccurate location prediction of assets.
Innovation Solution
Implementing multiple reader devices and environment tags in fixed geographical locations and storage units, utilizing signal strength comparisons to predict the location of assets with redundancy checks and data cleaning to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS triangulation or typical location-sensing technologies are used, then location detection is enabled, but measurement precision is insufficient for indoor asset tracking
Solution Approach 1:
The facility is divided into multiple storage units, each equipped with environment tags at specific locations. Reader devices are strategically placed to cover different areas. This segmentation enables precise location determination by comparing signal strengths from multiple tags within specific storage units, achieving granular location sensing without requiring a single complex centralized system.
Solution Approach 2:
Environment tags are introduced as intermediary elements placed throughout the facility and coupled to storage units. These tags serve as reference points that mediate between the reader devices and the target asset tags. By comparing signal strengths from multiple environment tags, the system accurately determines asset locations within storage units without requiring direct line-of-sight or complex triangulation mathematics.
2Measurement precision
If static location-sensing components are deployed, then infrastructure is simplified, but location prediction accuracy deteriorates
Solution Approach 1:
The system employs multiple reader devices that can dynamically query different environment tags and asset tags based on current location needs. The reader devices adaptively select which tags to read and compare signal strengths from multiple tags to determine precise locations. This dynamic querying and signal comparison approach enables accurate location tracking while maintaining a relatively simple static infrastructure of tags and readers.
Solution Approach 2:
Environment tags serve multiple functions: they act as location markers, signal strength references, and identifiers for storage units. Reader devices perform multiple tasks including reading tag data, comparing signal strengths, and determining asset locations within storage units. This multi-functionality increases system versatility without requiring specialized components for each function.
3Measurement precision
If signal strength variations among tags are not accounted for, then system complexity is reduced, but measurement precision of asset location deteriorates
Solution Approach 1:
The system implements feedback by comparing signal strengths from multiple environment tags relative to a target asset tag. Reader devices collect signal strength data from multiple tags, compare these values to determine which storage unit contains the asset, and use the relative signal strength differences to pinpoint the asset's specific location within the storage unit. This feedback mechanism accounts for signal variations and converts them into useful location information.
Solution Approach 2:
The system changes the parameter being measured from simple tag presence detection to signal strength comparison. By measuring and comparing the strength of signals from multiple environment tags against the target asset tag, the system transforms signal variations from potential errors into useful data for determining precise asset locations within storage units.
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
Achieves granular and redundant location sensing with minimal human intervention, improving the precision of asset location prediction within storage units and reducing interference noise.
Implementation Method 1
comparing one or more indications of signal strength values between the at least one reader device and each tag of the first set of environment tags with one or more other indications of signal strength values between the at least one reader device and the target tag
Data Source
AI summary
Various embodiments employ multiple readers and tags in fixed locations in different geographical areas and/or along different storage units. This allows for more granular or precise location sensing. Particular embodiments employ multiple environment tags in various geographical locations and within multiple storage units. Using this new infrastructure setup, some embodiments can perform new functionality by predicting whether a target asset is in a particular geographical location, predict whether the asset is within a particular storage unit based on the proportion of readers mapped to that shelf which are actually reading the tag on the asset, and/or can predict where an asset's exact location in the located storage unit is based on comparing indications of signal strength values between each reader and tag in the storage unit with other indications of signal strength values between each reader and the tag that is attached to the asset.