Hybrid Location Identification Using Sensor Fusion
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Solution Overview
Problem
Existing electronic devices face challenges in accurately identifying location changes and adjusting settings automatically, as they often rely on camera-based systems that are sensitive to environmental changes and user movements, leading to potential misidentification and frequent re-registration.
Innovation Solution
The use of sensors such as position/orientation sensors, long-range motion sensors, and proximity sensors to assist in location identification, allowing for feedback and verification of registration conditions without relying solely on camera-based programs, and integrating these sensor data with camera images to determine location changes and trigger registration processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera-based systems are used for location identification, then the system can identify locations, but the accuracy deteriorates due to sensitivity to environmental changes and user movements
Solution Approach 1:
The patent combines camera-based image recognition with sensor-based detection (accelerometer, gyroscope, magnetometer) to create a hybrid location identification system. The processor integrates data from multiple sensors and camera images to determine location changes, leveraging the strengths of both approaches while mitigating their individual weaknesses. This merging resolves the contradiction by maintaining camera-based identification capability while adding sensor-based reliability to reduce misidentification.
Solution Approach 2:
The system implements feedback mechanisms where sensor data continuously monitors device movement and orientation, providing real-time information to the processor. This feedback loop allows the system to verify whether detected location changes are actual transitions or merely device movements, thereby improving both accuracy and reliability of location identification and reducing false registrations.
2Productivity
If camera-based place recognition is used, then location identification can be performed, but frequent re-registration occurs due to sensitivity to viewpoint and environmental changes
Solution Approach 1:
The system performs preliminary actions by continuously monitoring sensor data (acceleration, orientation, magnetic field) even before camera-based re-recognition is triggered. This preliminary detection allows the system to anticipate whether a true location change has occurred, preparing to confirm or reject re-registration attempts before they fully unfold, thereby reducing unnecessary re-registrations while maintaining quick response to actual location changes.
Solution Approach 2:
Sensor-based feedback mechanisms provide continuous verification during the location identification process. The processor uses sensor data to validate camera-based recognition results, confirming whether detected changes represent actual location transitions. This feedback prevents premature or incorrect re-registrations, reducing the frequency of time-consuming re-registration cycles while preserving automatic setting adjustment capability.
3Reliability
If sensor data is integrated with camera images, then location identification reliability improves, but device complexity increases
Solution Approach 1:
The processor serves multiple functions: it processes camera images for location recognition, integrates sensor data for movement detection, validates registration conditions, and triggers appropriate responses. By making the processor multi-functional, the system avoids adding separate dedicated hardware for each function, thereby improving reliability through integrated processing while minimizing the increase in overall device complexity.
Data Source
AI summary
In some examples, an electronic device includes a processor to identify a first location based on an image captured by a camera. In some examples, the processor detects a movement of the electronic device based on sensor data generated by a sensor. In some examples, the processor identifies a second location when the movement satisfies a registration condition.