Air Conditioner User Detection to Prevent False Airflow Targeting
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Solution Overview
Problem
Existing air conditioners struggle with inaccurate detection of human presence due to confusion between actual users and user-like objects such as pictures or displays, leading to inefficient airflow control and user inconvenience.
Innovation Solution
A home appliance system that includes a camera, processor, and operation unit to distinguish between users and user-like objects by analyzing image differences and pixel values, allowing separate operations based on user presence and absence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the air conditioner uses a camera to detect human presence and automatically control airflow, then user convenience is improved, but detection accuracy deteriorates due to confusion between actual users and user-like objects such as pictures or displays
Solution Approach 1:
The system dynamically adjusts detection parameters and operational modes based on the detected object type. When a user is detected, the system performs concentrated airflow control; when a user-like object is detected, it switches to non-concentrated mode. This dynamic adaptation allows the system to optimize both convenience and accuracy by responding differently to different object types.
Solution Approach 2:
The system changes operational parameters based on detection results. It distinguishes between actual users and user-like objects by analyzing multiple parameters including object position, shape characteristics, and temporal patterns. Based on these parameter analyses, the system adjusts airflow concentration, temperature settings, and operational intensity to match the actual detection scenario, thereby resolving the contradiction between convenience and accuracy.
2Productivity
If the air conditioner performs concentrated airflow control based on detected human presence, then cooling/heating efficiency is improved, but energy consumption increases when detecting user-like objects
Solution Approach 1:
The system implements a feedback mechanism where the camera continuously monitors the indoor space and the processor analyzes detected objects in real-time. Based on the analysis results, the system provides feedback to the operation control unit to adjust airflow patterns. This closed-loop feedback ensures that concentrated airflow is only applied when actual users are present, optimizing efficiency while avoiding unnecessary energy consumption from misdetecting user-like objects.
Solution Approach 2:
The system applies partial concentrated airflow control based on the confidence level of detection. When user-like objects are detected, the system performs partial or reduced concentrated control rather than full concentrated control, thereby maintaining some efficiency benefit while avoiding excessive energy consumption associated with complete misidentification of non-user objects.
3Device complexity
If the air conditioner uses simple human-body shape recognition, then device complexity is reduced, but detection reliability deteriorates due to false identification of pictures and displays
Solution Approach 1:
The detection system is segmented into multiple functional modules: a camera module for image capture, a processor module for analyzing object characteristics including shape, position, and temporal patterns, and an operation control module for executing differentiated actions. This segmentation allows the system to maintain relatively simple individual components while achieving high overall reliability through the coordinated work of multiple specialized modules.
Solution Approach 2:
The system transitions from two-dimensional image analysis to multi-dimensional detection by incorporating temporal dimension (continuous monitoring over time), spatial dimension (position and movement trajectory), and characteristic dimension (shape, size, and pattern analysis). This multi-dimensional approach significantly improves detection reliability while keeping individual sensing components simple, as the complexity is distributed across multiple detection dimensions rather than requiring a single complex sensor.
Data Source
AI summary
Disclosed are a home appliance and a control method thereof. The disclosed home appliance performs a first home appliance operation for objects corresponding to shapes of a human body in a space, and thereafter, excludes an object other than a user from among the objects and performs a second home appliance operation for the user only. In this case, the first home appliance operation and the second home appliance operation are not simultaneously performed and are different from each other.