Vehicle Event Detection Using Trigger-Based Sensor Offloading
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Solution Overview
Problem
Current systems for detecting and recording vehicle events rely on single sensors and post-accident analysis, lacking real-time capability and comprehensive data capture from multiple sources, which limits their effectiveness in identifying and documenting vehicle maneuvers and environmental conditions.
Innovation Solution
A system comprising sensors, servers, and processors that generate and analyze output signals from various sensors, including video and audio data, to detect vehicle events in real-time, select relevant subsets of sensors, and record and transmit event data for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data from multiple sensors is captured and transmitted, then measurement precision and event detection capability improve, but device complexity and data transmission requirements increase
Solution Approach 1:
The system segments sensor data processing by creating separate processing paths for different event types. The server divides incoming data streams from multiple sensors into event-specific processing queues, allowing each event type to be analyzed by specialized algorithms rather than processing all sensor data uniformly.
Solution Approach 2:
The system performs preliminary action by pre-configuring event detection thresholds and processing rules before events occur. The server maintains pre-compiled event templates and sensor correlation matrices that are prepared in advance, enabling rapid event detection without complex real-time computation.
2Loss of time
If real-time event detection is implemented, then response time improves, but energy consumption and processing requirements increase
Solution Approach 1:
The system implements periodic action by sampling sensor data at optimized intervals rather than continuously processing all data streams. The server adjusts sampling frequencies based on event likelihood and current vehicle conditions, performing intensive processing only when events are detected while using lighter periodic checks during normal operation.
Solution Approach 2:
The system applies partial action by selectively processing only the subset of sensor data relevant to detected events. When an event is triggered, the server activates only the specific processing pipelines needed for that event type rather than running all processing routines, reducing overall energy consumption while maintaining real-time detection capability.
3Loss of information
If comprehensive sensor data is recorded and transmitted, then information completeness improves, but data transmission time and bandwidth requirements increase
Solution Approach 1:
The system extracts only the essential event-related data from the comprehensive sensor dataset for transmission. The server identifies and extracts key parameters relevant to each event type, filtering out redundant information while maintaining complete event documentation. This extraction approach preserves information completeness for analysis while dramatically reducing transmission bandwidth requirements.
Solution Approach 2:
The system applies local quality by transmitting different data quality levels for different event types based on their importance and analysis requirements. Critical safety events trigger high-fidelity data transmission from all sensors, while minor events use reduced data sets, optimizing the balance between information completeness and transmission efficiency for each specific case.
Data Source
AI summary
This disclosure relates to a system and method for detecting vehicle events. The system includes sensors configured to generate output signals conveying information related to the vehicle. The system detects a vehicle event based on the information conveyed by the output signals. The system selects a subset of sensors based on the detected vehicle event. The system captures and records information from the selected subset of sensors. The system transfers the recorded information to a remote server or provider.