Smart Device Conflict Processing for Non-Directional Commands
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Solution Overview
Problem
Existing smart device control systems struggle to determine the appropriate execution device when a user's instruction is non-directional, leading to ambiguity among multiple capable devices.
Innovation Solution
A device control method that acquires user, environmental, and device information to determine the optimal execution device through multi-modal fusion feature representation and attention-weighting processing, utilizing a feature fusion network to select the appropriate device based on user intent and device characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple smart devices are deployed to provide comprehensive functionality, then the system's adaptability and versatility improve, but device selection ambiguity increases when users issue non-directional instructions
Solution Approach 1:
The system implements feedback mechanisms by analyzing device states, user profiles, and environmental contexts to determine the most appropriate execution device. The system continuously monitors device availability, operational states, and user preferences, using this feedback to resolve ambiguity in device selection without requiring explicit user specification.
Solution Approach 2:
The system introduces an intermediary device selection mechanism that acts as a mediator between the user's non-directional instruction and the multiple capable devices. This intermediary analyzes various factors including device states, user profiles, and environmental contexts to determine the most appropriate device, thereby resolving the information loss about device selection clarity.
2Measurement precision
If the system considers multiple factors (user information, environmental information, device information) to accurately select execution devices, then device selection precision improves, but system complexity increases
Solution Approach 1:
The system segments the complex device selection process into distinct functional modules: a module for acquiring user information, another for environmental information, and a third for device information. Each module independently processes its specific data type, and their results are integrated to determine the execution device. This segmentation reduces overall system complexity by making each component's function clear and manageable.
Solution Approach 2:
The system implements a universal device selection mechanism that handles multiple types of information (user profiles, environmental contexts, device states) through a single integrated framework. This multi-functional approach improves device selection accuracy by considering diverse factors while avoiding the need for separate specialized systems for each information type, thereby controlling complexity.
3Reliability
If the system performs conflict detection and processing among multiple execution devices, then operational reliability improves, but processing time increases
Solution Approach 1:
The system performs preliminary conflict detection and resolution before executing device operations. By proactively identifying potential conflicts among multiple execution devices and resolving them in advance, the system ensures operational reliability without requiring time-consuming conflict resolution during execution, thereby reducing overall processing time.
Solution Approach 2:
The system dynamically adjusts processing parameters based on the detected conflict severity and device priorities. When conflicts are detected, the system modifies execution parameters such as processing depth, resolution strategies, and device priority weights to resolve conflicts efficiently. This adaptive parameter adjustment maintains operational reliability while minimizing the time spent on conflict processing.
Data Source
AI summary
The application provides a device control method, a conflict processing method, a corresponding apparatus, and an electronic device. The method includes: acquiring an input instruction of user; acquiring at least one of the following information: user information, environmental information, device information; determining at least one execution device of the input instruction based on the acquired information and the input instruction; controlling the at least one execution device to perform a corresponding operation. The present application can determine at least one optimal execution device by using at least one of the obtained input instruction and the user information, the environment information, and the device information when the user does not specify the specific execution device, thereby better responding to the user.