Image-Based Personal Thermal Comfort Detection for HVAC Control
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Solution Overview
Problem
Traditional thermal sensors and detection processes are unable to accurately assess individual thermal comfort levels, leading to inconsistent temperature experiences in shared spaces, as different individuals react differently to the same temperature conditions.
Innovation Solution
A system that uses image processing to identify individuals, estimate their thermal comfort by analyzing clothing, skin exposure, and behavioral cues, and adjusts air-conditioning or heating units based on these assessments to maintain personal comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional thermal sensors are used to detect temperature, then temperature data can be obtained, but individual thermal comfort levels cannot be accurately assessed
Solution Approach 1:
The patent replaces traditional thermal sensors with an image processing system that uses cameras to capture visual data. The system processes images to detect clothing types, skin exposure levels, and behavioral cues (such as fanning or wrapping arms) to infer individual thermal comfort states. This substitution enables personalized comfort assessment without requiring direct thermal contact with individuals.
2Adaptability or versatility
If a single ambient temperature is maintained for all individuals, then energy consumption is reduced, but different individuals experience different thermal comfort levels
Solution Approach 1:
The patent implements local quality by providing personalized thermal comfort control for different individuals within the same space. The image processing system identifies each individual's thermal comfort state and sends targeted recommendations to specific users via mobile devices. This allows each person to adjust their local environment (personal heater, fan, or clothing) without requiring the entire space to be conditioned, thereby reducing overall energy consumption while maintaining individual comfort.
Solution Approach 2:
The system enables self-service by empowering individuals to make their own thermal comfort adjustments based on AI-generated recommendations. Users receive personalized suggestions (e.g., 'put on a jacket' or 'turn on your personal heater') and independently implement changes using their own devices or actions, eliminating the need for centralized control of the entire environment.
3Measurement precision
If image processing is used to identify individuals and assess thermal comfort, then personalized comfort levels can be determined, but system complexity increases
Solution Approach 1:
The patent leverages the universality of mobile devices by using smartphones that users already possess for communication and notification purposes. The system sends thermal comfort recommendations through existing mobile messaging infrastructure, eliminating the need for specialized display devices or complex user interfaces. This multi-functional approach reduces overall system complexity while maintaining personalized comfort assessment capabilities.
Data Source
AI summary
A method for temperature control includes acquiring image data, and analyzing the image data to identify one or more individuals within the image data. A level of thermal comfort is estimated for each of the identified individuals based on the image data. The determined level of thermal comfort indicates whether each individual appears to be feeling too hot, appears to be feeling too cold or appears to be feeling satisfied with an ambient temperature. An air-conditioning unit or a heating unit is controlled based on the estimation of the level of thermal comfort for each of the identified individuals.