Remote Control Location Detection Using Multi-Modal Sensing
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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 emit sounds, vibrations, or lights in response to commands, and the resulting sensing signatures are analyzed to determine their location using sensors and machine learning algorithms, allowing for precise location determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a remote control emits sound to indicate its location, then users can locate the remote control in open environments, but the method becomes ineffective when the remote control is in locations where sounds are not easily perceivable (e.g., under cushion)
Solution Approach 1:
The patent segments the location detection function into multiple independent sensing modalities: sound emission, vibration sensing, and light sensing. Each modality operates independently to detect different environmental characteristics, allowing the system to adapt to various locations by selecting or combining appropriate sensing methods based on the detected environment.
Solution Approach 2:
The remote control device is equipped with multiple sensors (microphone, accelerometer, light sensor) that enable it to perform multiple sensing functions. This multi-functionality allows the device to operate effectively across diverse environments by using the most appropriate sensing modality for each specific location scenario.
2Measurement precision
If multiple sensing functions are added to determine device location, then location accuracy in various environments improves, but device complexity increases
Solution Approach 1:
The system uses feedback from multiple sensors to continuously monitor the device's environment. Based on this feedback, the machine learning model dynamically determines the most appropriate sensing modality or combination of modalities to use, optimizing location detection accuracy while avoiding unnecessary activation of all sensors in every situation.
Solution Approach 2:
The patent changes the operational parameters of the sensing system by using a machine learning model to dynamically select which sensors to activate and how to interpret their readings. This parameter-based approach allows the system to adapt its complexity level based on the specific detection scenario, using only the necessary sensing capabilities for each situation.
3Measurement precision
If the remote control emits light or vibration to indicate location, then location can be determined in sound-insensitive environments, but energy consumption increases
Solution Approach 1:
The system employs periodic sensing and emission actions rather than continuous operation. The machine learning model determines when to activate each sensing modality based on the detected environment, allowing the device to remain in a low-power state until location detection is needed, and even then, only activating the necessary sensors for the specific situation.
Solution Approach 2:
The patent applies partial action by activating only the necessary sensing modalities required for the current detection scenario. Instead of continuously using all sensors, the system selectively activates sound, vibration, or light emission based on what is needed for the specific environment, thereby reducing overall energy consumption while maintaining detection effectiveness.
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 accurate identification of a remote control's location, even in challenging environments, by analyzing feedback from emitted sounds, vibrations, or light patterns, facilitating easy retrieval.
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
The generated sensing signature may be indicative of a reflection of sound and/or light from the device's surrounding environment
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.