Image Recognition for Automated User Interface Generation
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Solution Overview
Problem
Software development for user interfaces is complex, time-consuming, and resource-intensive, especially when custom interfaces are created for systems with standardized devices, leading to inconsistent designs and increased development effort due to differences in device configurations and environments.
Innovation Solution
The use of machine learning techniques to automatically recognize devices in images, associate them with device profiles, and generate user interfaces with standardized command schemas, allowing for the creation of user interfaces that can control devices with common user interface controls and reduce the need for manual customization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If custom user interfaces are created for each system or environment, then the user interface can be tailored to specific device configurations, but the development time and resources increase significantly
Solution Approach 1:
The patent uses image recognition to capture visual representations of physical systems and automatically generates digital user interfaces by copying the spatial relationships and device configurations from the images. This eliminates manual interface design while preserving system-specific customization, resolving the contradiction between adaptability and development time.
Solution Approach 2:
The system performs self-configuration by automatically recognizing devices in images, identifying their types and positions, and generating appropriate user interface controls without human intervention. This automated self-service approach creates customized interfaces rapidly, addressing both the need for adaptability and the reduction of development time.
2Adaptability or versatility
If custom user interfaces are created for each system or environment, then the interface can accommodate specific device configurations, but development resources and complexity increase
Solution Approach 1:
The patent replaces the mechanical process of manual interface design and configuration with an automated image recognition and processing system. The machine learning model automatically analyzes images, identifies devices, and generates interfaces, substituting complex human-driven development processes with automated computational methods, thereby reducing development complexity while maintaining customization capability.
3Loss of time
If standardized device profiles are used, then development time is reduced, but the ability to handle unique or non-standard devices is limited
Solution Approach 1:
The patent applies local quality by using standardized device profiles for common devices to enable rapid interface generation, while simultaneously allowing for custom profile creation and image-based recognition of non-standard devices. This layered approach ensures that standard devices benefit from fast standardized processing, while unique devices receive customized attention, balancing development speed with device compatibility.
Solution Approach 2:
The system dynamically adapts its approach based on device recognition results. When a standardized device profile matches the recognized device, the system applies the standardized profile for rapid processing. When no match is found or the device is non-standard, the system dynamically switches to creating custom profiles, thereby optimizing the balance between development time and device compatibility.
4Adaptability or versatility
If manual customization is performed for each environment, then specific requirements are met, but consistency across different interfaces is lost
Solution Approach 1:
The patent implements a universal standardized command schema that serves multiple device types and environments. By mapping diverse device-specific commands to a common standardized schema, the system ensures that user interfaces maintain consistent interaction patterns across different environments while still accommodating environment-specific requirements through image-based customization.
Data Source
AI summary
Techniques and solutions are described for improving automated user interface generation. Devices can automatically be recognized in one or more images of a system or environment. At least certain devices can be identified as standard devices, and associated with device profiles. The device profiles can include information useable to identify user interface controls that should be rendered on a user interface for the system or environment. The user interface controls can be rendered over an image or schematic diagram of the system or environment, including at locations that correspond to a geospatial location of the corresponding device, or a controllable element thereof. The user interface controls can be associated with commands of a standardized command schema, which in turn are mapped to specific commands that can be sent to control the devices or controllable elements thereof.