Motorized Camera Object Recognition for IoT Control
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Solution Overview
Problem
In IoT networks, users face difficulties in distinguishing between multiple objects of similar type or function, leading to incorrect control when issuing voice commands, as existing systems struggle to accurately identify the intended device among a group of connected devices.
Innovation Solution
An electronic device equipped with a camera module and motor system that uses vision-based recognition to identify user motion and reposition itself to focus on the intended object, allowing for precise control by analyzing images and adjusting its orientation to center on the desired device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vision-based recognition with motor-driven camera adjustment is implemented, then object identification accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the object identification process into distinct functional modules: camera module for image capture, processor for image analysis and motion detection, and motor system for positioning adjustment. This modular segmentation allows each component to specialize in its function, improving overall identification accuracy while making the complex system more manageable and maintainable
Solution Approach 2:
The system transitions from static image capture to dynamic multi-dimensional observation by adding motor-driven camera adjustment capabilities. This allows the camera to move in multiple dimensions (pan, tilt, zoom) to track user motion and focus on target objects, significantly improving identification accuracy in environments with multiple similar objects
2Measurement precision
If the camera is repositioned to follow user motion, then control precision is improved, but response time increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring user motion and pre-positioning the camera to anticipate the user's intended target. The processor detects user motion in real-time and adjusts the camera position proactively before the user completes their gesture, reducing the perceived response time while maintaining high control precision
Solution Approach 2:
The system implements a closed-loop feedback mechanism where the processor continuously analyzes user motion, determines the intended target, and adjusts camera positioning accordingly. This real-time feedback loop ensures the camera remains aligned with the user's focus, improving control precision without significant delay
Data Source
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AI summary
Embodiments of the present disclosure relate to vision-based object recognition devices and methods for controlling the same. According to an embodiment of the present disclosure, an electronic device may comprise a camera, at least one motor, a communication interface, at least one processor, and a memory electrically connected with the processor, wherein the memory may store commands that, when executed by the processor, cause the processor to identify a motion of an external object using a first image obtained by controlling the camera, obtain first direction information based on the identified motion of the external object, drive the at least one motor so that the camera faces a direction determined according to the first direction information, and identify a second electronic device from a second image obtained by controlling the camera facing the determined direction.