Vehicle Biometric Sensor Control for Thermal Comfort
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Solution Overview
Problem
Automobile users often overcompensate in adjusting vehicle system inputs to correct their autonomic functions, leading to uncomfortable conditions, and there is a need for a system that automatically monitors user biometrics to provide personalized and dynamic adjustments to vehicle settings.
Innovation Solution
A system comprising biometric sensors, controllers, and machine learning algorithms that monitor and adjust interior environmental conditions based on occupant biometrics, external conditions, and vehicle settings to create a personalized experience, reducing subjective errors and enabling dynamic user profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the user manually adjusts the vehicle cabin temperature setting to correct perceived discomfort, then the user attempts to improve their thermal comfort, but the user overcompensates resulting in the opposite effect and requiring further adjustments
Solution Approach 1:
The system uses biometric sensors to automatically detect the occupant's autonomic physiological responses and autonomously adjusts vehicle systems without requiring manual user input. The occupant's body itself provides the control signals through biometric data, eliminating overcompensation errors inherent in manual adjustment.
Solution Approach 2:
The system continuously monitors biometric parameters and uses this feedback to dynamically adjust vehicle environmental controls. The closed-loop feedback mechanism compares actual biometric states with target states and automatically corrects deviations, preventing the oscillating overcompensation behavior seen in manual adjustment.
2Measurement precision
If the system automatically monitors user biometrics and adjusts vehicle conditions, then the system provides personalized and accurate control, but the system complexity increases
Solution Approach 1:
The controller serves multiple functions: it processes biometric data from various sensors, determines optimal vehicle settings based on biometric feedback, stores learned occupant profiles, and coordinates multiple vehicle systems (HVAC, seating, lighting). This multi-functionality reduces the need for separate dedicated systems for each function.
Solution Approach 2:
The controller acts as an intermediary that integrates biometric sensor data with vehicle system controls. It translates complex biometric measurements into appropriate vehicle setting adjustments, and manages the machine learning algorithms that bridge the gap between raw biometric data and actionable control commands.
3Adaptability or versatility
If the system uses machine learning algorithms to learn from occupant biometrics, then the system creates dynamic personalized profiles, but the data processing requirements increase
Solution Approach 1:
The system performs preliminary learning and profile creation during periods when the vehicle is stationary or during initial occupancy periods. By pre-learning occupant preferences and biometric patterns before critical driving situations arise, the system reduces real-time computational demands during active vehicle operation.
Solution Approach 2:
The machine learning algorithms process biometric data by transforming it into standardized parameter representations and using dimensionality reduction techniques. The system changes the parameter space from raw complex biometric signals to simplified occupancy profiles, reducing computational energy requirements while maintaining adaptability.
Data Source
AI summary
A system and method are described for controlling a vehicle interior environmental condition. A biometric sensor senses a biometric condition of a vehicle seat occupant and generates a sensed biometric condition value. A controller receives the sensed biometric condition value, a sensed interior environmental condition value, and a sensed exterior environmental condition value. Each of multiple exterior environmental condition values has an associated biometric condition value defined as optimal for the vehicle occupant. The controller determines the optimal biometric condition value associated with the sensed exterior environmental condition value, compares the optimal biometric condition value to the sensed biometric condition value, and in response to a difference between the optimal biometric condition value and the sensed biometric condition value, generates a control signal to control an actuator to control the controllable interior environmental condition to reduce the difference between sensed biometric condition value and the optimal biometric condition value.