Motion Sensor Configuration Using Device-Type Classification
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Solution Overview
Problem
Existing motion-detecting devices in media devices face challenges such as high computational and resource intensity, particularly when transmitting large amounts of motion data, which can quickly drain battery power, and manual configuration can be complex and require technical proficiency.
Innovation Solution
A classifier-based configuration technique is employed to identify the device type of a media device using motion data, allowing the motion-detecting device to process data on-device and transmit only relevant information, reducing the need for extensive data transmission and battery drain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion data is transmitted to a central server for processing, then accurate user activity detection can be achieved, but battery power is drained quickly due to high computational and resource intensity
Solution Approach 1:
The system segments the data processing task by performing initial motion data processing locally at the media device before transmission to the central server. The motion-detecting device processes and filters motion data locally to identify and transmit only relevant information, reducing the amount of data transmitted and thus lowering battery power consumption while maintaining detection accuracy.
Solution Approach 2:
The invention extracts and transmits only the essential motion data and processed information to the central server, rather than transmitting all raw motion data. The motion-detecting device extracts relevant patterns and summarizes motion information, reducing data volume and energy consumption while preserving the accuracy of user activity detection.
2Adaptability or versatility
If manual configuration of motion-detecting device is performed, then device can be customized for specific needs, but configuration process is complex and requires technical proficiency
Solution Approach 1:
The system implements self-service configuration where the motion-detecting device automatically identifies the media device type and configures itself without manual intervention. The device autonomously determines appropriate motion detection parameters and settings based on the detected media device type, eliminating the need for users to perform complex manual configuration while maintaining full customization capability.
Solution Approach 2:
The invention automatically changes configuration parameters based on the detected media device type. The system modifies motion detection sensitivity, data processing thresholds, and transmission parameters dynamically according to the specific media device, providing customized configuration through automated parameter adjustment rather than manual user input.
3Loss of energy
If motion data is processed on-device, then data transmission volume is reduced and battery life is conserved, but device complexity increases due to need for classifier and processing capabilities
Solution Approach 1:
The system performs preliminary action by pre-training and storing motion detection classifiers and processing algorithms within the motion-detecting device before actual operation. The device contains pre-configured machine learning models and processing rules that enable local motion data analysis without requiring complex real-time computation, thus reducing energy consumption while limiting the increase in operational device complexity.
Data Source
AI summary
An example method is for use in connection with a media device and a motion-detecting device mounted to the media device, and includes: obtaining motion data associated with the motion-detecting device; providing the obtained motion data to a trained classifier, wherein the trained classifier is configured to use at least motion data as runtime input data to generate at least device type data as runtime output data; responsive to providing the obtained motion data to the trained classifier, receiving from the trained classifier corresponding device type data generated by the trained classifier; using at least the received device type data to identify a device type of the media device; using at least the identified device type of the media device as a basis to select a set of configuration parameters for the motion-detecting device; and causing the motion-detecting device to be configured according to the selected set of configuration parameters.