Gesture Load Control With Regional Mapping for Precise Device Selection
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Solution Overview
Problem
Current load control systems require users to manage multiple devices and have limited control due to predefined interfaces and limited instructions, making them inconvenient and not commercially viable, especially with the experimental nature of gesture-based systems that lack essential features.
Innovation Solution
A gesture-based load control system that uses motion capture devices to identify user gestures and send control instructions to load control devices, allowing users to control electrical loads without remote controls by analyzing images or videos and associating gestures with specific devices or scenes within a regional mapping configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional load control systems use multiple devices and predefined interfaces, then control functionality is provided, but user convenience deteriorates and system complexity increases
Solution Approach 1:
The patent extracts the control interface from physical devices and transforms it into gesture-based commands captured by imaging devices. Users perform natural gestures in space that are captured and translated into control instructions, eliminating the need for remote controls, wall switches, and other intermediary devices. This extraction of the interface layer simplifies the system while maintaining full control functionality.
Solution Approach 2:
The patent introduces an imaging device and gesture recognition system as a new intermediary between the user and the load control device. Instead of directly manipulating physical controls, users perform gestures in the field of view of the imaging device, which then translates these gestures into control commands. This intermediary layer provides a more natural and convenient interface while consolidating multiple control functions into a single system.
2Measurement precision
If gesture-based control is implemented without regional mapping, then gesture recognition is simplified, but control precision and device identification deteriorate
Solution Approach 1:
The patent segments the field of view into multiple predefined regions, each associated with specific control devices or functions. When a user performs a gesture within a particular region, the system identifies the relevant device based on the regional mapping. This segmentation provides precise control and device identification without requiring complex real-time device detection algorithms.
Solution Approach 2:
The patent establishes regional mappings in advance before actual control operations occur. Each region is pre-configured to correspond to specific devices or control functions, creating a lookup table that enables rapid and accurate device identification during gesture recognition. This preliminary configuration eliminates the need for complex real-time spatial analysis while maintaining high precision in control.
3Adaptability or versatility
If predefined interfaces and instructions are used, then control functionality is established, but adaptability to different user needs deteriorates
Solution Approach 1:
The patent transforms the static, predefined interface into a dynamic gesture-based system that adapts to user needs in real-time. Users can perform various gestures in different regions to control different devices and functions, allowing the system to adapt to different control scenarios without requiring reconfiguration of the interface itself. The flexibility comes from the variety of possible gestures and regional mappings rather than complex interface options.
Data Source
AI summary
A load control system may include load control devices for controlling an amount of power provided to an electrical load. The load control devices may be capable of controlling the amount of power provided to the electrical load based on control instructions received from a gesture-based control device. The gesture-based control device may identify gestures performed by a user for controlling a load control device and provide control instructions to the load control device based on the identified gestures. The gestures may be identified based on images received from a motion capture device. A gesture may be associated with a scene that includes a configuration of one or more load control devices in a load control system. The user may perform one or more gestures to program the gesture-based control device to identify a gesture.