Indoor Mobile Device Location via Semantic Image Analysis
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Solution Overview
Problem
Existing location-based systems for mobile devices, such as GPS, struggle in indoor environments with weak satellite signals, making it difficult to accurately determine the device's location, especially in high-density commercial areas with many internal locations.
Innovation Solution
A computer-implemented method using semantic indicators from captured images, including visual features, audio data, logos, textures, and sensor data, to compare with stored location features and select the most likely location from candidate locations, allowing for accurate indoor navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS satellite signals are used for location detection, then outdoor location accuracy is improved, but indoor location detection capability deteriorates due to weak satellite signals
Solution Approach 1:
The patent introduces semantic indicators (visual features, audio data, logos, textures) as intermediary elements to bridge the gap between captured images and location identification. These indicators serve as mediators that enable indoor location detection without requiring direct satellite signal access, resolving the contradiction between GPS accuracy and indoor adaptability
Solution Approach 2:
The patent replaces the mechanical/electromagnetic GPS satellite signal system with a semantic analysis system that processes visual and auditory data. This substitution eliminates dependency on satellite signals for indoor environments, maintaining location detection capability where GPS fails
2Measurement precision
If multiple sensors and data types are collected for location detection, then location accuracy is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple data types (images, audio, logos, textures, sensor data) into a unified semantic indicator framework. By combining these diverse data sources and processing them through a single comparison mechanism against stored location features, the system achieves high accuracy without proportionally increasing complexity
Solution Approach 2:
The semantic indicator system serves multiple functions simultaneously: it identifies visual features, processes audio data, recognizes logos, analyzes textures, and integrates sensor information. This multi-functionality allows the system to maintain accuracy across different detection modalities while using a single unified processing approach
Data Source
AI summary
A system and computer implemented method for detecting the location of a mobile device using semantic indicators is provided. The method includes receiving, using one or more processors, a plurality of images captured by a mobile device at an area. The area is associated with a set of candidate locations. Using the one or more processors, one or more feature indicators associated with the plurality of images are detected. These feature indicators include semantic features related to the area. The semantic features are compared with a plurality of stored location features for the set of candidate locations. In accordance with the comparison, a location from the set of candidate locations is selected to identify an estimated position of the mobile device.