AI Device Behavior Pattern Association for Non-AI IoT Integration
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Solution Overview
Problem
Many devices without AI functionality lack integration with AI systems, necessitating a method to associate them using IoT technology, as existing devices with AI functions are expensive and time-consuming to acquire.
Innovation Solution
A method involving a camera that senses user behavior patterns and transmits these patterns to an AI device, which receives voice commands and sends control instructions to devices without AI functionality via an IoT network, allowing for operation based on predefined patterns without the need for a wake-up word.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If devices without AI functionality are integrated with AI systems using existing methods, then AI functionality is added to devices, but the cost and time required increase significantly
Solution Approach 1:
The system performs preliminary actions by having the camera continuously capture user behavior data and pre-process this data to recognize behavior patterns before voice commands are needed. The AI device maintains a ready state with pre-recognized patterns, so when a user speaks, the system can immediately match the voice command against pre-processed behavior data, eliminating the need for real-time analysis and reducing integration time.
Solution Approach 2:
The patent introduces an intermediary mechanism - a server - that mediates between the camera, AI device, and target devices. The server receives behavior data from the camera, processes it to recognize patterns, and stores these patterns for quick retrieval by the AI device. This intermediary handles the complex processing tasks, allowing the AI device to focus on voice recognition and command execution, thereby reducing overall integration time and complexity.
2Reliability
If AI devices are equipped with wake-up word functionality, then they can accurately identify user intent, but the system complexity and number of required components increase
Solution Approach 1:
The patent merges the wake-up word recognition function with the existing voice command processing system. Instead of adding a separate wake-up word detection module, the system combines behavior pattern recognition with voice command analysis. The camera-captured behavior data serves as contextual information that enhances voice intent identification, allowing the system to achieve reliable user intent recognition without increasing component count or system complexity.
Solution Approach 2:
The system uses self-service by leveraging the behavior data already being collected by the camera for other purposes. This existing behavior data is repurposed to enhance voice command recognition, eliminating the need for separate sensors or additional data collection mechanisms. The system serves multiple functions using the same hardware components, thereby maintaining simplicity while improving reliability.
3Ease of operation
If behavior pattern recognition is implemented using camera data, then user convenience is enhanced, but the data processing requirements and computational load increase
Solution Approach 1:
The patent segments the data processing task into distinct stages: the camera captures raw behavior data, the server performs pattern recognition and processing, and the AI device executes voice command matching. This segmentation allows computationally intensive operations to be performed on the server with adequate processing power, while the AI device maintains lower energy consumption by handling only the final matching and execution tasks. The division of labor reduces the computational burden on energy-constrained devices.
Solution Approach 2:
The server acts as an intermediary that handles the heavy computational workload of behavior pattern recognition. By offloading this energy-intensive processing to the server, the AI device and camera can operate with lower power consumption. The server processes behavior data, recognizes patterns, and returns simplified results to the AI device, thereby reducing the overall energy requirements of the system while maintaining enhanced user convenience.
Data Source
AI summary
Provided are a method of associating an AI device with a device based on a behavior pattern of a user and a device therefor. The method of associating the AI device with the device according to an embodiment of the invention receives a preset behavior pattern of the user sensed by a first camera from the first camera, receives a voice command for controlling an operation of the device from the user, and transmits the voice command to the device, thus allowing devices having no AI function to be used in conjunction with the AI device. The AI device and the dive of the invention may be associated with artificial intelligence modules, drones (unmanned aerial vehicles (UAVs)), robots, augmented reality (AR) devices, virtual reality (VR) devices, devices related to 5G service, etc.