Indoor Asset Tracking via Image-Based Map Scaling
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Solution Overview
Problem
Graphical user interfaces for tracking systems often lack granular details, especially in indoor environments, making it difficult to accurately locate assets using satellite-based maps or large-area maps that do not provide fine details of indoor layouts or exact object locations.
Innovation Solution
A user interface and system that includes a mapping interface and a locating interface, which processes images of environmental layouts to generate geographic layouts, allowing for the accurate placement of infrastructure nodes and tracking of assets by determining communication recency with asset nodes and overlaying node graphical elements on the interface based on communication history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If satellite-based maps or large-area maps are used for asset tracking, then coverage area is improved, but measurement precision of indoor locations and fine details deteriorates
Solution Approach 1:
The system segments the mapping approach by combining satellite-based large-area maps with locally captured images of indoor environments. The large map provides broad coverage while local images provide detailed indoor layouts, allowing the system to maintain both wide coverage and high precision simultaneously by dividing the problem into regional and local components.
2Measurement precision
If detailed indoor layout images are captured and processed, then measurement precision is improved, but device complexity and processing requirements worsen
Solution Approach 1:
The system merges multiple data sources including satellite map data, locally captured images, and wireless communication signals into a unified tracking interface. This integration allows the system to leverage the strengths of each data source while managing complexity through coordinated processing of diverse inputs to achieve accurate indoor asset location.
Solution Approach 2:
The system introduces an intermediary processing layer that captures images of indoor environments, processes them to extract layout information, and integrates this data with satellite map coordinates. This intermediary step transforms complex image data into structured location information that can be displayed on the tracking interface without overwhelming system resources.
3Measurement precision
If multiple infrastructure nodes are tracked with communication history, then asset tracking accuracy is improved, but information processing requirements worsen
Solution Approach 1:
The system extracts only the essential communication recency information from infrastructure node interactions, focusing on whether recent communication occurred rather than processing complete communication histories. This extraction approach maintains tracking accuracy by capturing the critical temporal aspect of node-asset interactions while minimizing data volume requirements.
Data Source
AI summary
Systems and methods receive an image of at least part of an environmental layout and at least two geographic feature locations associated with the image. At least two geographic locations are determined, each corresponding to a respective one of the at least two geographic feature locations and a map scale is determined for the images based on the at least two geographic feature locations and the at least two geographic locations. The map scale allows conversion between points on the image and geographic locations. The image and the map scale are used to display a location interface on a client device that allows a user to search the environmental layout for an asset associated with a tracking node, where the location interface graphically displays graphical elements indicative of communication recency between the tracking tag and one or more infrastructure nodes.