Remote Control Location Through Multimodal Sensing Signatures
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Solution Overview
Problem
Remote controls are often lost or misplaced, and existing methods for locating them, such as sounding them, are ineffective in environments where sounds are not easily perceivable, making it difficult for users to find them.
Innovation Solution
Devices are equipped with functions to emit sounds, vibrations, or lights, and the feedback from these activations is used to generate sensing signatures that help determine their location, utilizing sensors and machine learning algorithms to analyze the environment and output location information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sound is emitted to locate the remote control, then the remote control can be heard in open spaces, but the sound is not easily perceivable when the remote control is in enclosed or soft locations such as under cushions
Solution Approach 1:
The system segments the location detection process into multiple sensing modalities (sound, light, vibration) rather than relying on a single sound-based approach. Each modality is activated based on the detected environment type, allowing the system to overcome the limitations of sound perception in enclosed spaces by switching to alternative sensing methods.
Solution Approach 2:
The system changes the sensing parameters dynamically based on the detected environment. When the environment is identified as enclosed or soft (through initial sound analysis), the system switches from sound-based detection to light-based detection, changing the physical parameter used for location determination to one that is not affected by the environmental constraints.
2Reliability
If multiple sensing functions (sound, light, vibration) are activated to improve location accuracy in various environments, then location detection becomes more reliable, but the device complexity and energy consumption increase
Solution Approach 1:
The system dynamically activates only the sensing functions necessary for the current environment. Rather than having all sensors continuously active or permanently configured, the system adjusts its sensing modalities in real-time based on environmental conditions, reducing complexity while maintaining reliability across different scenarios.
Solution Approach 2:
The system uses a unified multi-modal sensing framework that can operate with different combinations of sensors (sound, light, vibration) depending on the situation. This universal approach allows the same device to handle various environmental conditions without requiring separate specialized systems for each scenario.
3Ease of manufacture
If sound-based location method is used, then the implementation is simple, but it fails in environments where sound is not easily perceivable such as under cushions or in drawers
Solution Approach 1:
The system performs preliminary sound-based detection to characterize the environment before switching to alternative methods. By first attempting simple sound analysis and detecting environmental characteristics (enclosed, soft, absorbent), the system prepares for and transitions to more appropriate sensing modalities, maintaining implementation simplicity while improving reliability.
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
Effectively locates remote controls by analyzing environmental feedback, enabling users to find misplaced devices even in challenging locations like under cushions or drawers.
Implementation Method 1
The generated sensing signature may be indicative of a reflection of sound and/or light from the device's surrounding environment
Implementation Method 2
A high quantity of light may be used to determine that the device is in a sock drawer, for example, a sensor may detect reflected light from the surface of the drawer
Implementation Method 3
a vibration sensing signature may indicate a level of vibration feedback measured by an accelerometer
Data Source
AI summary
Methods, systems, and apparatuses for device location are described herein. Location information of a lost control device may be determined based on sensing signatures according to various modalities. The sensing signatures may be based on responses to activated functions of the lost remote control. The location information may be determined based on an instruction received while the lost remote control is in an active state. Frequently lost remote controls may be in the active state more frequently. An alternative remote control may be selected as a substitute for the lost remote control before the lost remote control is found. The alternative remote control may be configured to control a device previously controlled by the lost remote control.