Adaptive Vehicle Seat Control for Posture and Strain Reduction
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Solution Overview
Problem
Existing seating systems fail to provide optimal support and comfort for users due to varying individual needs and changing circumstances, leading to discomfort, back strain, and decreased productivity.
Innovation Solution
The Intelligent Seat System (ISS) actively adjusts to improve occupant comfort and safety by measuring pressure surface values, determining posture and physiological state, and responding to driving environment conditions through machine vision, machine learning, and state machine processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If seating systems are made adjustable to accommodate different users and circumstances, then comfort and support are improved, but device complexity increases
Solution Approach 1:
The ISS uses pressure sensors, machine vision cameras, and machine learning algorithms to automatically detect occupant posture, position, and physiological state, then autonomously adjusts seat parameters without requiring manual user input. The system serves itself by making real-time adjustments based on sensor data and AI processing.
Solution Approach 2:
The seating system transitions from static, fixed-position seats to dynamic, continuously adjustable seats that adapt in real-time. The system monitors occupant conditions through sensors and actively modifies seat parameters (position, support, firmness) dynamically to maintain optimal comfort and posture throughout the driving experience.
2Ease of manufacture
If manual adjustment of seating systems is required, then ease of manufacture is improved, but ease of operation deteriorates
Solution Approach 1:
The patent replaces manual mechanical adjustment mechanisms with automated electronic control systems. Machine vision cameras capture images of the occupant, machine learning algorithms process the images to determine optimal seating parameters, and electronic actuators automatically adjust the seat, eliminating the need for manual operation.
Solution Approach 2:
The system introduces an intermediary AI processing layer between the occupant and the seat adjustment mechanism. The machine learning model acts as a mediator that translates visual data from cameras into specific adjustment commands, enabling automatic adaptation without direct user interaction with the seat controls.
3Device complexity
If seating systems remain static, then device complexity is reduced, but adaptability to different users and circumstances deteriorates
Solution Approach 1:
The ISS integrates multiple functions into a single unified system: pressure sensors detect body contact points, machine vision cameras capture posture information, machine learning algorithms process data from multiple sources, and actuators execute adjustments. This multi-functional integration enables the system to serve diverse user needs while maintaining a cohesive architectural structure.
Data Source
AI summary
An ISS is a seating system that actively adjusts to improve an occupant's comfort, performance, and safety in a specific driving environment. The ISS determines the occupant's posture, position on the seat surface, and/or physiological state, for example, by applying a machine vision process. The ISS can further determine a driving environment. The ISS adjusts its settings and settings of the vehicle according to one or more factors such as an occupant's posture, the occupant's physiological state, the occupant's preferences, and/or the driving environment. The ISS can include a state machine that determines a current state and determines if a change has occurred such that the system should shift to another state that best suits this change. The ISS makes adjustment according to system settings associated with the best suitable state.