Environmental control device, environmental control method, and environmental control program
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Solution Overview
Problem
Existing environmental control systems do not effectively manage energy consumption while maintaining happiness during a person's active periods, as they primarily focus on sleep environments and do not account for time-series changes in physiological states when the person is awake and active.
Innovation Solution
An environmental control device with a learning processing unit that creates a control model by analyzing past relationships between environmental indicators and happiness, allowing for targeted environmental adjustments to enhance happiness while minimizing energy usage during active periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If environmental control systems focus on sleep environments only, then energy saving during sleep is improved, but energy consumption during active periods is not optimized
Solution Approach 1:
The environmental control system is designed to handle both sleep and active periods through a unified control model. The learning processing unit creates a comprehensive model that adapts to different states (sleep and active), allowing the system to optimize energy consumption across multiple scenarios rather than requiring separate specialized systems.
Solution Approach 2:
The system dynamically adjusts environmental indicators based on the person's state. The control model learns from time-series changes in physiological states and happiness, enabling the system to adapt its control strategy in real-time according to whether the person is sleeping or active, thus optimizing energy consumption for each state appropriately.
2Device complexity
If environmental control ignores time-series changes in physiological states, then system complexity is reduced, but happiness maintenance during active periods deteriorates
Solution Approach 1:
The system incorporates feedback mechanisms by continuously monitoring time-series changes in physiological states and happiness levels. The learning processing unit uses this feedback to refine the control model, creating a closed-loop system that adapts to individual preferences and maintains happiness while managing energy consumption during active periods.
Solution Approach 2:
The learning processing unit performs preliminary learning by analyzing past relationships between environmental indicators and happiness. This preliminary action builds a control model that anticipates future needs, allowing the system to maintain happiness during active periods without requiring complex real-time adjustments for every change in physiological state.
3Reliability
If environmental control adjusts environmental indicators aggressively to boost happiness, then happiness improvement is enhanced, but energy consumption increases
Solution Approach 1:
The control model determines appropriate environmental indicator adjustments by learning from past examples. It applies partial actions - making just enough adjustments to boost happiness without over-adjusting. The system identifies the minimum necessary changes to environmental indicators to achieve happiness improvement while avoiding excessive energy consumption.
Solution Approach 2:
The system optimizes energy consumption by learning the relationships between environmental indicator parameters and happiness. The control model identifies which parameter changes yield the best happiness improvement per unit of energy consumed, allowing it to select the most energy-efficient parameter adjustments during active periods.
Data Source
AI summary
An environmental control device of the invention includes a learning processing unit configured to create a control model by collecting relationships between past examples of changes in temporal or spatial happiness of a person who is subjected to environmental control and past examples of changes in a temporal or spatial environmental indicator regarding the person, and an environmental control unit configured to, based on the created control model, determine a temporal or spatial environmental indicator for boosting happiness of a person who is newly subjected to the environmental control and perform the environmental control while targeting the determined environmental indicator.