Proximate Beacon Identification via Signal Deviation Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current global positioning systems (GPS) and location identification services on mobile devices often lack the necessary fidelity for precise user experiences, particularly when users need to be immediately proximate to a specific location, and lose reliability indoors or in areas with obstructions, failing to accurately determine the user's location within a building or specific store.
Innovation Solution
The method involves using local beacons to identify the proximity of a mobile device by analyzing and filtering signal transmissions from beacons placed in various locations, determining the average received signal strength and deviation over an observation period to identify the closest beacon, even when the user is non-stationary, thereby providing rich content relevant to the user's location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS satellite triangulation is used to identify user location, then approximate position can be determined, but location fidelity and precision deteriorate with error ranges of thirty to fifty feet
Solution Approach 1:
The patent segments the location identification system into multiple independent components: GPS for outdoor macro-location, Wi-Fi access points for mid-range positioning, and Bluetooth beacons for precise indoor localization. Each component operates independently and contributes to the overall location determination, achieving high fidelity through hierarchical segmentation of the positioning system.
Solution Approach 2:
The patent introduces local beacons as intermediary devices that relay location information between the mobile device and the central server. These beacons transmit unique identifiers that the mobile device uses to determine proximity to specific physical locations, serving as intermediaries that bridge the gap between coarse GPS data and precise indoor positioning requirements.
2Reliability
If GPS signal triangulation is used for location identification, then outdoor position can be determined, but reliability deteriorates when mobile device is inside a building or under cover
Solution Approach 1:
The patent replaces the GPS satellite-based electromagnetic triangulation system with a ground-based infrastructure of Wi-Fi access points and Bluetooth beacons for indoor location tracking. This substitution eliminates dependence on satellite signals that are blocked by building structures, using instead local transmitted signals that penetrate indoor environments effectively, thereby maintaining reliability under cover.
Solution Approach 2:
The patent creates a universal location tracking system that functions across multiple environments using the same mobile device application. The system automatically selects appropriate positioning methods (GPS for outdoor, Wi-Fi/Bluetooth for indoor) based on availability, providing reliable location tracking universally whether the device is outside or inside buildings, thus overcoming environment-specific limitations.
3Measurement precision
If local beacons are used to identify proximate location, then location fidelity improves for indoor positioning, but device complexity increases due to multiple signal sources
Solution Approach 1:
The patent extracts the complex signal processing and location calculation algorithms from the mobile device and places them on the central server. The mobile device only needs to detect beacon identifiers and transmit raw data, while the server performs the computationally intensive tasks of signal strength analysis, triangulation calculations, and location determination, thereby reducing device complexity while maintaining high indoor positioning fidelity.
Solution Approach 2:
The patent changes the operational parameters of the beacon system by using standardized Bluetooth Low Energy (BLE) transmissions with fixed power levels and periodic intervals. This standardization simplifies the signal detection and analysis process on mobile devices, reducing complexity while achieving precise indoor location fidelity through consistent, predictable signal characteristics that are easier to process.
4Measurement precision
If signal transmissions from multiple beacons are analyzed to identify proximate beacon, then location precision improves, but time consumption increases for signal processing
Solution Approach 1:
The patent implements a partial action approach by initially analyzing only the strongest beacon signals and progressively considering additional beacons only when needed for disambiguation. The system processes a limited subset of beacon data first to achieve quick location identification, then incorporates additional beacon information only when the initial analysis is insufficient, thereby reducing overall processing time while maintaining high proximity identification accuracy.
Solution Approach 2:
The patent performs preliminary actions by pre-calculating and storing beacon locations, signal propagation characteristics, and expected signal strength patterns in databases before actual location tracking begins. When a mobile device needs location identification, the system retrieves pre-processed data and performs minimal real-time calculations, significantly reducing the time required for beacon proximity identification while maintaining high precision through advance preparation.
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
This approach enhances location awareness on mobile devices, enabling accurate identification of the user's location relative to known beacons, even in dynamic conditions, and provides on-the-fly, location-specific information to users.
Implementation Method 1
a first average received signal strength (RSS) can be determined for a first beacon; and a first average RSS deviation can be determined for the first beacon
Data Source
AI summary
Among other things, one or more techniques and/or systems are disclosed for identifying a proximate beacon to a mobile device. One or more first received signal strengths (RSSs), relative to the mobile device, may be received and used to determine a first average signal strength (RSS) and a first average RSS deviation for a first beacon during an observation period. An average RSS deviation for the observation period can be determined using the first average RSS deviation (e.g., and other average RSS deviations). If the average RSS deviation meets a desired deviation threshold, the first beacon may be identified as the proximate beacon. In this manner, if the user of the mobile device consents to the same, the user may be provided with relevant information (e.g., advertisements) on the mobile device while in a locale (e.g., store) corresponding to the (known) location of the beacon, for example.