Computing Device Location-Based Setting Adjustment
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Solution Overview
Problem
Portable computing devices, such as notebooks, tablets, and smartphones, face challenges in automatically adjusting settings based on their environment, leading to potential privacy issues and reduced user productivity, as users must manually change settings for different locations.
Innovation Solution
Equipping computing devices with sensors, such as RGB or IR cameras and microphones, to detect environmental objects and sounds, allowing the device to determine its location and adjust settings like privacy filters, audio output, screen brightness, and Bluetooth pairing automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual setting adjustment is required for different locations, then user control over device settings is maintained, but user productivity decreases and time is lost
Solution Approach 1:
The computing device automatically detects environmental context through sensors (camera, microphone, GPS) and autonomously adjusts settings without requiring user intervention. The system serves itself by monitoring location, identifying environment type, and applying appropriate settings profiles, thereby eliminating manual adjustment while maintaining optimal performance
Solution Approach 2:
The device pre-configures multiple setting profiles corresponding to different environments (office, cafe, library, outdoor) and automatically selects and applies the appropriate profile based on detected location. This preliminary preparation of multiple scenarios enables instant adaptation without manual intervention when the user moves between locations
2Object-affected harmful factors
If settings are manually adjusted for different environments, then privacy can be maintained in public places, but user convenience is reduced
Solution Approach 1:
The system continuously monitors environmental context through sensors (detecting presence of other people via audio, analyzing visual context via camera, tracking location via GPS) and provides feedback to automatically adjust privacy-sensitive settings. This closed-loop feedback mechanism ensures privacy protection is dynamically maintained based on real-time environmental conditions without requiring user awareness or action
Solution Approach 2:
The computing device autonomously manages privacy settings by detecting public versus private environments and automatically applying appropriate privacy profiles (such as disabling microphone, adjusting display orientation, or limiting camera access in public spaces). The system protects user privacy through self-monitoring and self-adjustment without manual intervention
3Extent of automation
If sensors and automatic detection systems are added to computing devices, then automatic setting adjustment is enabled, but device complexity increases
Solution Approach 1:
The patent leverages existing multi-functional sensors already present in modern computing devices (camera for photos and video, microphone for audio input, GPS for location tracking, ambient light sensors) and applies them to environment detection. By utilizing sensors that already serve multiple purposes, the system achieves automatic setting adjustment without adding dedicated single-purpose sensors, thereby minimizing the increase in device complexity
Solution Approach 2:
The system combines data from multiple existing sensors (camera, microphone, GPS, accelerometer) to collectively determine environmental context. Rather than relying on a single complex sensor, the patent merges information from several simpler, existing sensors to achieve accurate environment detection, reducing overall system complexity while maintaining high automation capability
Data Source
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AI summary
Examples disclosed herein provide the ability for a computing device to adjust settings on a computing device. In one example method, the computing device captures, via a first sensor of a computing device, images of an environment that the computing device is currently in, and detects objects in the environment as captured by the images. As an example, the computing device determines a location of the environment based on contextual data gathered from the detected objects and adjusts a setting on the computing device based on the determined location.