Vehicle Occupant Validation Using Seat and Steering Pressure
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Solution Overview
Problem
Current transportation systems lack efficient methods to monitor and respond to changes in passenger weight distribution, seat position, and steering wheel pressure, which can indicate unsafe driving conditions, potentially leading to accidents.
Innovation Solution
Integration of sensors and machine learning algorithms within vehicles to validate weight distribution, seat position, and steering wheel pressure, triggering alerts or altering vehicle use when thresholds are exceeded, utilizing blockchain for secure data storage and smart contracts for authorization and service management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors and machine learning algorithms are integrated to monitor weight distribution, seat position, and steering wheel pressure, then safety monitoring capability is improved, but device complexity increases
Solution Approach 1:
The monitoring system is divided into separate functional modules: weight sensors on the seat bottom, position sensors detecting seat back angle, and pressure sensors on the steering wheel. Each sensor type independently measures a specific parameter, and the processor evaluates each parameter separately against predefined thresholds before triggering safety alerts.
Solution Approach 2:
The processor performs multiple functions using a single computational unit: it processes data from different sensor types (weight, position, pressure), compares each against thresholds, determines unsafe conditions, and triggers alerts. This multi-functional approach reduces the need for separate dedicated systems for each monitoring task.
2Loss of time
If real-time monitoring and alerting systems are implemented, then response time to unsafe conditions is improved, but energy consumption increases
Solution Approach 1:
The system continuously monitors parameters by periodically comparing sensor readings against predefined thresholds. The processor evaluates weight distribution, seat position, and steering wheel pressure at regular intervals, triggering alerts only when threshold violations occur. This periodic evaluation approach enables timely detection of unsafe conditions while avoiding continuous high-energy processing.
3Reliability
If blockchain technology is used for secure data storage and smart contracts for service management, then data security and decentralization are improved, but system complexity increases
Solution Approach 1:
Blockchain technology serves as an intermediary layer for secure data storage and verification. Instead of implementing complex cryptographic protocols directly in the vehicle's monitoring system, the patent leverages blockchain's inherent security features to store sensor data, validation results, and service transaction records. This intermediary approach provides robust security without requiring the vehicle system to manage cryptographic complexity.
Solution Approach 2:
The system uses smart contracts to create digital copies of service authorization and data access permissions. Rather than managing complex access control lists and permission hierarchies, the patent implements permissionless access models where blockchain validators can verify and access data through predefined smart contract rules. This copying approach simplifies service management by replacing complex authorization logic with transparent, automated contract execution.
Data Source
AI summary
An example operation includes one or more of validating, by a transport, a weight distribution of an individual on a bottom of a seat, a position of the individual against a back of the seat and a pressure exerted by the individual on a steering wheel of the transport, and when the weight distribution, the position and the pressure are above a threshold, altering, by the transport, a use of the transport.