Vehicle Occupant Detection via Accelerometer and Neural Network Analysis
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Solution Overview
Problem
Current occupant detection systems in vehicles are inadequate in detecting an occupant who is hiding or very still, as they rely on conventional alarm systems and lack remote detection capabilities, posing safety risks to car owners approaching their vehicles.
Innovation Solution
An occupant detection system utilizing a sensitive accelerometer to sense vehicle movement, combined with artificial neural networks and Fast Fourier transform algorithms to determine the presence of an occupant, providing a certainty rating and generating alerts through a remote user interface, such as a key fob, when an occupant is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional alarm systems are used for occupant detection, then the system structure is simple, but the detection capability is insufficient and cannot detect hidden or still occupants
Solution Approach 1:
The patent combines multiple detection algorithms (neural networks, Fast Fourier transform, statistical methods) into a unified occupant detection system that processes accelerometer data through multiple analytical pathways, thereby improving detection reliability while managing system complexity through integrated architecture
Solution Approach 2:
The system introduces an accelerometer as an intermediary sensing device that indirectly detects occupant presence through vehicle vibration and movement patterns, enabling detection of hidden occupants without direct visual contact or complex camera systems
2Measurement precision
If multiple processing algorithms are used to improve detection accuracy, then the detection precision is improved, but the processing time and computational load increase
Solution Approach 1:
The system employs periodic sampling of accelerometer data and processes it through multiple algorithms at intervals, allowing computational tasks to be distributed over time rather than executed simultaneously, thus maintaining high detection accuracy while managing processing time constraints
Solution Approach 2:
The patent applies multiple processing algorithms selectively based on detection confidence levels, using simpler methods when sufficient and more complex algorithms only when needed to achieve required precision, thereby optimizing the balance between accuracy and processing time
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
Effectively detects an occupant, even when they are very still, by analyzing vehicle vibrations and biometric characteristics like heartbeat, providing timely alerts to ensure user safety and security.
Implementation Method 1
A sensor, such as an accelerometer or the like, that senses movement of the vehicle
Implementation Method 2
analyzing vehicle vibrations and biometric characteristics like heartbeat
Data Source
AI summary
An occupant detection system for detecting an occupant within a vehicle includes a sensor for sensing movement or acceleration of the vehicle, first and second processors and a decider. The sensor generates a sensor output. The first processor processes the sensor output in a first manner and generates a first output indicative of the possibility of the presence of an occupant within the vehicle. The second processor processes the sensor output in a second manner and generates a second output indicative of the possibility of the presence of an occupant within the vehicle. The decider processes the first and second outputs and determines whether the combination of the first and second outputs is indicative of an occupant in the vehicle.