Interactive Digital Maps Using Multi-Tiered Location Identification
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Solution Overview
Problem
Current digital mapping technologies face challenges in accurately generating and updating maps for indoor venues due to unreliable GPS signals and the inability to capture precise geographical information, leading to poor user experience and ineffective navigation tools.
Innovation Solution
A system that uses multi-tiered location identification processes, combining user-collected data, WiFi records, Bluetooth Low Energy data, and accelerometer data to generate and modify interactive digital maps, allowing for precise location determination and dynamic GUI adjustments based on user location and confidence levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS signals and satellite imaging are used for digital mapping, then map data can be collected for outdoor venues, but GPS signals are unreliable indoors and satellite imaging cannot capture indoor geographical information
Solution Approach 1:
The patent introduces WiFi access points and Bluetooth Low Energy (BLE) beacons as intermediary devices that emit signals detectable by mobile devices. These intermediaries serve the same purpose as GPS satellites but operate indoors, enabling location determination in environments where traditional satellite-based systems fail.
Solution Approach 2:
The patent replaces the satellite-based electromagnetic signal system with a local network of WiFi and BLE signal emitters. This substitution transitions from a centralized satellite system to a distributed local system, allowing indoor location services without relying on external satellite infrastructure.
2Measurement precision
If standard GPS resolution (5-30 meters) is used for navigation, then general location identification is possible, but precision is insufficient for identifying specific seating spots or workspaces
Solution Approach 1:
The patent transitions from coarse GPS coordinates to fine-grained location identification by introducing a multi-dimensional approach: combining signal strength measurements, signal triangulation data, and confidence levels. This enables precision down to specific seating spots or workspaces rather than general area identification.
Solution Approach 2:
The patent changes the parameters used for location determination from simple satellite coordinates to multiple measurable parameters including WiFi signal strength, BLE signal strength, signal arrival times, and confidence scores. These parameter changes enable much finer location resolution.
3Productivity
If digital maps are updated frequently to reflect changing venue layouts, then current topologies can be captured, but data collection and verification become time-consuming and complex
Solution Approach 1:
The patent implements a self-service update mechanism where mobile device users automatically contribute location data and spot information as they move through venues. The system passively collects data from multiple users and uses confidence level calculations to automatically verify and update maps without requiring manual data collection or verification teams.
Solution Approach 2:
The patent incorporates feedback loops where user-reported spots and location data are continuously evaluated against confidence thresholds. When confidence levels are sufficient, maps are automatically updated; when thresholds are not met, additional verification is triggered. This feedback-driven approach enables frequent updates while maintaining accuracy.
Data Source
AI summary
A system for generating a map with spots. The system includes processors and storage devices storing instructions that, when executed, configure the processors to perform operations. The operations may include receiving a map request of a venue, the map request comprising first location data associated with the venue, and transmitting a map data file for the venue, the map data file comprising a presentation of a plurality of spots in the venue and the spots being associated with confidence levels. The operations may also include receiving an add-spot request, the add-spot including data of an additional spot to be added, second location data associated with the additional spot, and verification data. The operations may also include determining a confidence level for the additional spot, modifying the map data file to include a representation of the additional spot, and transmitting the modified map data file.