Real-Time Vehicle Event Detection With Selective Data Streaming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing event data recorders (EDRs) lack the capability to efficiently detect and monitor events and precursors to events in real-time, and do not provide interfaces for users to manage and view recorded data effectively.
Innovation Solution
An event detection system comprising a plurality of sensor devices, including cameras, accelerometers, and a neural network, to generate and analyze sensor data, detect events or precursors, and stream data to a server system for further analysis, using object models and machine learning to identify specific events and precursors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing EDRs continuously record data, then data availability is improved, but data management complexity and user accessibility worsen
Solution Approach 1:
The patent extracts and separates event detection functionality from continuous data recording. The system records only specific data related to detected events rather than continuously managing all vehicle data, thereby reducing data management complexity while maintaining data availability for relevant events.
Solution Approach 2:
The patent introduces an intermediary event detection system that acts as a mediator between continuous data collection and user access. This intermediary process automatically identifies, filters, and prepares event data for user access, reducing the complexity of data management while ensuring data availability.
2Reliability
If real-time event detection is implemented, then safety and responsiveness are improved, but processing time and computational resources worsen
Solution Approach 1:
The patent applies preliminary action by pre-defining event criteria, thresholds, and detection parameters before actual event occurrence. The system prepares detection algorithms and parameter sets in advance, enabling rapid real-time processing without computational delays during actual event detection.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting detection sensitivity and processing thresholds based on vehicle state and event context. This allows the system to optimize processing speed for critical safety events while reducing computational overhead for routine monitoring, thereby improving safety without excessive processing time loss.
3Adaptability or versatility
If multiple sensor devices are integrated, then detection capability is improved, but system complexity and data processing burden worsen
Solution Approach 1:
The patent segments the sensor integration architecture into modular detection units, each handling specific sensor types (cameras, accelerometers, GPS). This segmentation allows the system to achieve high detection capability across multiple sensor sources while managing complexity through independent, standardized processing modules that can be activated based on detected event types.
Data Source
AI summary
Example embodiments described herein therefore relate to an event detection system that comprises a plurality of sensor devices, to perform operations that include: generating sensor data at the plurality of sensor devices; accessing the sensor data generated by the plurality of sensor devices; detecting an event, or precursor to an event, based on the sensor data, wherein the detected event corresponds to an event category; accessing an object model associated with the event type in response to detecting the event, wherein the object model defines a procedure to be applied by the event detection system to the sensor data; and streaming at least a portion of a plurality of data streams generated by the plurality of sensor devices to a server system based on the procedure, wherein the server system may perform further analysis or visualization based on the portion of the plurality of data streams.