Vehicle Data Processing Using Distributed Local Processors
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Solution Overview
Problem
Vehicle data processing systems face significant delays and data lag due to increased data volumes, which can lead to inadequate response times in emergency situations, potentially resulting in accidents or injuries.
Innovation Solution
Implementing local processors in proximity to sensors and control mechanisms within vehicles to rapidly identify and respond to emergency events, distributing processing load and minimizing latency, with the main processor supplementing initial reactions based on additional analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a main processor handles all data processing for vehicle sensors, then centralized control and comprehensive data analysis are achieved, but processing time increases and emergency response is delayed
Solution Approach 1:
The patent divides the centralized processing function into distributed processing units located at different strategic positions within the vehicle. Each processing unit handles data from nearby sensors locally, segmenting the overall processing task to reduce communication overhead and accelerate response time for emergency situations.
Solution Approach 2:
The patent introduces a spatial dimension to the processing architecture by distributing processors throughout the vehicle volume rather than concentrating them in one location. This spatial distribution allows parallel processing of sensor data from different regions simultaneously, reducing overall processing time.
2Reliability
If more sensors are added to detect emergency situations, then detection capability and safety are improved, but data volume increases causing processing delays
Solution Approach 1:
The patent segments the large volume of sensor data by assigning different sensor groups to different distributed processing units. Each unit processes only the data from its associated sensors, dividing the overwhelming total data volume into manageable chunks that can be processed in parallel, thereby maintaining fast response times despite having numerous sensors.
Solution Approach 2:
The distributed processing units act as intermediaries between the sensors and the central main processor. They perform preliminary processing and filtering of sensor data, reducing the burden on the main processor and enabling faster local responses to emergency conditions while maintaining comprehensive monitoring capability.
Data Source
AI summary
A vehicle data processing method includes receiving data points from one or more sensors arranged in or around a vehicle, identifying one or more emergency events based on the received data points from the sensors, determining, with the one or more local processors of a vehicle, an instant reaction in response to the emergency events, and controlling a control mechanism of the vehicle based on the determined instant reaction.