Context-Aware Gesture Command Execution for Multi-Device Control
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Solution Overview
Problem
In environments with multiple gesture-controlled devices, it is challenging to determine which device a detected gesture is intended for and whether the gesture is meant to control a device at all.
Innovation Solution
The system interprets gestures by considering the context in which the gesture is performed, using data from various sources like cameras, motion sensors, and controllable devices to determine the intended device and action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple gesture-controlled devices are deployed in a premises, then device functionality and control options are improved, but it becomes challenging to determine which device a detected gesture is intended for
Solution Approach 1:
The system continuously monitors contextual data from multiple sources (cameras, motion sensors, device states) and uses this feedback to dynamically determine which device a gesture is intended for. The contextual information feedback loop allows the system to resolve ambiguity by considering the current state of all devices and the user's behavior patterns.
Solution Approach 2:
Contextual information acts as an intermediary between the gesture detection and device selection. Rather than directly mapping gestures to devices, the system uses contextual data (user location, device states, environmental conditions) as a mediator to determine the most likely intended target device.
2Ease of operation
If a single gesture is used to control multiple devices, then ease of operation is improved, but ambiguity arises about which device the gesture is intended for
Solution Approach 1:
The system changes the parameters used to interpret gestures based on contextual conditions. The same physical gesture can result in different device selections depending on contextual parameters such as which devices are currently active, user location, and recent interaction patterns. This allows a single gesture to control multiple devices without ambiguity.
Solution Approach 2:
The gesture-to-device mapping is dynamic rather than static. The system continuously adapts which device a gesture controls based on the current contextual state, allowing the same gesture to naturally control different devices at different times without requiring the user to learn multiple gestures.
3Measurement precision
If contextual data from multiple sources is collected to determine gesture intent, then accuracy of device selection is improved, but system complexity increases
Solution Approach 1:
The system uses a unified contextual analysis framework that handles multiple data sources (cameras, motion sensors, device states) through a single multi-functional processing architecture. This universal approach allows the same system components to serve multiple purposes: tracking user position, determining device proximity, assessing contextual relevance, and resolving gesture ambiguity.
Data Source
AI summary
Upon detection of a gesture, a current context of an environment in which the gesture is performed may be determined. The current context may be used to interpret the gesture to determine which of potentially a plurality of devices are to be controlled by the gesture and whether the gesture is configured to control the determined device(s) in the current context. The current context may also be used to determine whether to adjust a threshold for determining whether the gesture is intended as a control command. An aspect of the detected gesture may be compared to the threshold to determine whether the gesture is intended as a control command. If the gesture is intended as a control command, the determined device(s) may be controlled accordingly.