Enclosure Behavior Recognition for Personalized Environment Control
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Solution Overview
Problem
Current systems for controlling environmental conditions within enclosures, such as buildings, rely on manual adjustment of physical interfaces, lacking automation and personalized user interactions based on identity and behavior recognition.
Innovation Solution
Implementing a method that uses imaging systems, like cameras or IR cameras, to capture user behavior data, determine user identity through machine learning, and automatically adjust environmental settings such as temperature, lighting, and window tint based on the user's preferences and actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of physical interfaces is used for controlling environmental conditions, then device complexity is reduced, but ease of operation and user comfort are worsened due to lack of automation and personalization
Solution Approach 1:
The system automatically detects user presence through imaging systems, identifies the user's identity, retrieves their preferences from a database, and adjusts environmental conditions without requiring manual input. The system serves itself by autonomously performing the complete control sequence from detection to environmental adjustment.
Solution Approach 2:
The patent replaces manual mechanical interaction with physical interfaces (switches, knobs, buttons) with an automated optical system using cameras and image processing. The mechanical act of manually adjusting environmental controls is substituted by an optical detection and automated control system that processes visual data to trigger environmental changes.
2Productivity
If automated behavior recognition systems are implemented, then productivity and energy efficiency are improved through automatic environmental control, but device complexity and initial energy consumption increase
Solution Approach 1:
The imaging system serves multiple functions: it detects user presence, captures behavioral data, and provides visual information for identity recognition. The system integrates these diverse functions into a single multi-functional platform, reducing the need for separate sensors and devices for each function.
Solution Approach 2:
The system continuously monitors the environment through imaging, compares detected behavior patterns against stored user preferences, and automatically adjusts environmental conditions accordingly. This closed-loop feedback mechanism enables automated optimization of environmental settings based on real-time user behavior observation.
3Measurement precision
If imaging systems are used to capture user behavior data, then measurement precision and personalization are improved, but loss of information and privacy concerns increase
Solution Approach 1:
The system extracts only the specific behavioral features necessary for identification and preference matching from the captured images, such as gait patterns, posture, and movement characteristics. Irrelevant visual information is discarded, retaining only the essential data needed for the system's function while minimizing information storage requirements.
Data Source
AI summary
An imaging system in an enclosure can capture a plurality of successive images of a user to determine an external behavior (e.g., a gait) of the user. The user can be identified based on the external behavior, and an environment may be controlled according to preferences and/or requests of the user.