Mobile Device Automatic Mode Determination via Visual Context Recognition
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Solution Overview
Problem
Users face challenges in configuring mobile devices to operate in specific modes for controlling electronic appliances, as current methods require manual intervention and are time-consuming, especially when switching between different modes or environments.
Innovation Solution
A mobile device that automatically determines its operating mode by visually sensing its environment using a camera and processor-implemented methods, associating images with user interface configurations and communication protocols to automatically configure itself for controlling electronic appliances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration methods are used to set up mobile device for controlling electronic appliances, then user can control the appliance, but the process is time-consuming and burdensome
Solution Approach 1:
The mobile device automatically captures images of the electronic appliance, processes these images to identify the appliance type and characteristics, and configures the user interface and communication protocol without requiring manual user input. This self-service approach eliminates the time-consuming manual configuration process while maintaining accurate appliance control capabilities.
Solution Approach 2:
The system performs preliminary actions by capturing and storing reference images of electronic appliances during a setup phase. These pre-processed images and associated control information are stored in memory, enabling the device to automatically recognize and configure for previously encountered appliances without requiring manual setup each time.
2Extent of automation
If the mobile device automatically captures and processes images to identify electronic appliances, then configuration is automated and time is saved, but device complexity increases
Solution Approach 1:
Instead of analyzing the physical structure of the appliance in complex detail, the system creates a simplified visual copy (image) of the appliance and stores it as a reference pattern. During operation, the device captures a new image and compares it against the stored reference images to identify the appliance type, using a simpler image matching approach rather than complex physical analysis.
Solution Approach 2:
The system introduces an intermediary representation (processed image data) between the physical appliance and the control system. By converting the physical appliance into a digital image representation and storing this as a reference, the complex task of appliance identification is simplified to a pattern matching problem, reducing the computational complexity required for real-time identification.
3Measurement precision
If the mobile device stores reference images and compares them to identify appliances, then automatic recognition is achieved, but memory requirements and processing load increase
Solution Approach 1:
The system extracts only the essential visual characteristics of the appliance by capturing an image and processing it to identify key features. Rather than storing complete high-resolution images and all associated metadata, the system extracts and stores only the necessary reference image data and associated control information, reducing the quantity of stored data while maintaining recognition accuracy.
Solution Approach 2:
The system performs partial image processing by capturing images at specific moments (during setup or when appliance is detected) rather than continuously processing all visual data. It stores only the necessary reference images and compares new captures against these references, using selective processing to achieve accurate recognition without requiring continuous analysis of all possible appliance types.
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 seamless and automatic mode switching for mobile devices when interacting with electronic appliances, reducing user burden and simplifying the configuration process by using visual context recognition and image processing algorithms.
Implementation Method 1
captures a first image of the electronic appliance using the image sensor
Data Source
AI summary
A mobile device such as a cell phone is used to remotely control an electronic appliance such as a television or personal computer. In a setup phase, the mobile device captures an image of the electronic appliance and identifies and stores scale-invariant features of the image. A user interface configuration such as a virtual keypad configuration, and a communication protocol, can be associated with the stored data. Subsequently, in an implementation phase, another image of the electronic appliance is captured and compared to the stored features in a library to identify a match. In response, the associated user interface configuration and communication protocol are implemented to control the electronic appliance. In a polling and reply process, the mobile device captures a picture of a display of the electronic device and compares it to image data which is transmitted by the electronic appliance.