Mobile Device Surface Detection for Automated Settings
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Solution Overview
Problem
Mobile devices cannot determine precise locations, such as specific surfaces or environments, leading to manual settings adjustments, which is inefficient and lacks automation.
Innovation Solution
Equipping mobile devices with sensors like microphones, noise generators, light-based proximity sensors, and pressure sensors to detect surface types and perform actions based on the detected surfaces, while also using additional data for location determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual process is used to enter device settings, then user can control device settings, but user experience is degraded due to manual input requirement
Solution Approach 1:
The mobile device automatically detects surface type using sensors and autonomously determines and executes appropriate actions or settings adjustments without requiring user intervention. The system serves itself by detecting environmental context and making intelligent decisions about what actions to perform based on the detected surface type.
Solution Approach 2:
The patent replaces manual mechanical input (user physically entering settings) with automated sensor-based detection and electronic processing. Sensors detect surface characteristics and the system electronically determines appropriate actions, substituting the mechanical manual settings adjustment process with an automated sensing and decision-making system.
2Measurement precision
If general location determination is used, then mobile device can determine location, but precise location information is insufficient for specific environment-based actions
Solution Approach 1:
The patent segments location determination into multiple independent sensing modalities: surface type detection sensors (microphone, noise generator, light-based proximity sensor, pressure sensors), vibration analysis, and acoustic reflection detection. Each sensor targets specific physical characteristics of the surface, dividing the complex location determination task into manageable sensing components that can be processed independently.
Solution Approach 2:
The patent makes existing mobile device sensors multi-functional by using them for both their primary purposes and surface type detection. For example, the microphone is used for both audio processing and detecting acoustic reflections from surfaces; the noise generator serves both media playback and active surface characterization; pressure sensors detect both touch input and surface contact characteristics. This universal usage reduces the need for dedicated sensors.
3Measurement precision
If multiple sensors are added to detect surface type, then surface detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent makes existing mobile device sensors multi-functional by using them for both their primary purposes and surface type detection. For example, the microphone is used for both audio processing and detecting acoustic reflections from surfaces; the noise generator serves both media playback and active surface characterization; pressure sensors detect both touch input and surface contact characteristics. This universal usage reduces the need for dedicated sensors.
Solution Approach 2:
The patent combines multiple sensing functions into existing sensor components. The acoustic system merges noise generation and microphone detection capabilities to create an active surface characterization system. The light-based proximity sensor is combined with surface reflectivity analysis for material identification. This merging approach achieves enhanced surface detection without adding separate dedicated sensor systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables automatic adjustment of device settings and actions based on surface type and location, enhancing user experience by eliminating manual input and improving location-specific functionality.
Implementation Method 1
a microphone and noise generator configured to detect pressure waves produced by setting the mobile device down or by the noise generator and reflected by the surface
Implementation Method 2
a light based proximity sensor configured to detect a texture of the surface
Implementation Method 3
pressure sensors, such as dielectric elastomers, configured to detect a texture of the surface, and/or pressure waves produced by setting the mobile device down
Data Source
AI summary
A mobile device uses sensor data related to the type of surface in contact with the mobile device to determine an action to perform. The sensors, by way of example, may be one or more of a microphone and noise generator, a light based proximity sensor, and pressure sensors, such as dielectric elastomers, configured to detect a texture of the surface, and/or pressure waves produced by setting the mobile device down or by a noise generator and reflected by the surface. The mobile device may identify the type of surface and perform the action based on the type of surface. The mobile device may further determine its location based on the sensor data and use that location to identify the action to be performed. The location may be determined using additional data, e.g., data not related to determining the type of surface with which the mobile device is in contact.