Child Safety Seat Motion Sensing for Adaptive Protection Activation
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Solution Overview
Problem
Existing safety seats lack the ability to detect child-related events and adjust protection mechanisms according to vehicle driving patterns, leading to inadequate protection and potential dangers for children during vehicle travel.
Innovation Solution
A machine learning model that uses motion sensors to detect child-related events and adjust protection mechanisms, such as activating alerts or adjusting airbags, based on vehicle driving conditions and child activity levels, while learning from a dataset of measurements associated with child safety seats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional passive restraints are used in safety seats, then the device complexity is low, but the protection effectiveness is insufficient for detecting child-related events and adapting to driving conditions
Solution Approach 1:
The patent replaces traditional mechanical passive restraint systems with an intelligent system that uses motion sensors, machine learning models, and electronic processors to detect child events and driving conditions, enabling adaptive protection that responds to actual situations rather than relying solely on fixed mechanical structures
Solution Approach 2:
The safety seat system performs self-diagnosis and self-adjustment by using onboard sensors to detect child presence, activity level, and driving conditions, then automatically adjusts protection mechanisms without requiring external intervention or complex manual configuration
2Measurement precision
If motion sensors and machine learning models are added to detect child events, then the detection capability is improved, but the manufacturing cost and device complexity increase
Solution Approach 1:
The motion sensor system is designed to perform multiple functions: detecting child presence, determining activity level, identifying driving conditions, and triggering appropriate protection mechanisms, thereby reducing the need for separate specialized sensors and systems for each function
Solution Approach 2:
The system uses machine learning models that analyze changes in motion parameters and patterns to detect different child events and driving conditions, transforming raw sensor data into meaningful classifications through parameter analysis rather than requiring complex hardware for each detection type
3Adaptability or versatility
If the safety seat adapts to vehicle-specific driving patterns, then the adaptability is improved, but the loss of time for data collection and model training increases
Solution Approach 1:
The system collects and processes driving pattern data in the background during normal vehicle operation, preparing adaptive models in advance so that when specific child events occur, the system can immediately apply pre-trained vehicle-specific parameters without requiring real-time data collection or delay
4Reliability
If protection mechanisms are activated based on detected events, then the protection effectiveness is improved, but the false alarm rate may increase
Solution Approach 1:
The machine learning model continuously analyzes sensor data with feedback loops that evaluate multiple parameters and patterns over time, adjusting detection thresholds and criteria based on learned patterns to distinguish true events from normal variations, thereby reducing false alarms while maintaining high detection accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The model effectively detects child-related events and adjusts protection mechanisms to enhance child safety, providing solutions for undefined situations and adapting to vehicle-specific conditions, thus improving protection and reducing the risk of accidents.
Implementation Method 1
a motion sensor mounted on a child safety seat or a base of a child safety seat installed in a vehicle
Data Source
AI summary
There is provided a computer implemented method for executing a model, for detecting safety seat events, comprising: receiving a plurality of records, each represents measurements taken by a motion sensor mounted on a child safety seat or a base of a child safety seat installed in a vehicle while the vehicle is static or in motion; executing at least one model to classify each of the plurality of records; detecting an occurrence of a child related event based on outputs of the execution of the at least one model; and activating a protection mechanism by a protection mechanism unit according to the detected occurrence of child related event.