Context-Aware Vehicle Event Detection With Dynamic Thresholds
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Solution Overview
Problem
Existing vehicle event detection systems rely on single-sensor data and post-accident analysis, lacking real-time detection capabilities and integration of environmental conditions, which limits their effectiveness in preventing and responding to vehicle events.
Innovation Solution
A system that integrates multiple sensors and external data sources to detect vehicle events in real-time by comparing current operating conditions with thresholds adjusted by contextual information, including environmental conditions, and provides immediate notifications and record-keeping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If single-sensor data and post-accident analysis are used, then system complexity is reduced, but real-time detection capability and event response effectiveness deteriorate
Solution Approach 1:
The patent combines multiple sensors (accelerometers, gyroscopes, GPS, temperature sensors, humidity sensors) into an integrated vehicle monitoring system. This merging of sensing capabilities enables comprehensive real-time detection of vehicle events and environmental conditions, resolving the contradiction by achieving reliable event detection through systematic integration rather than single-sensor approaches
Solution Approach 2:
The system performs preliminary actions by continuously monitoring vehicle parameters and environmental conditions before actual events occur. The dynamic threshold adjustment mechanism prepares the system in advance by establishing context-aware detection criteria based on pre-collected environmental data, enabling faster and more accurate real-time event detection without requiring complex post-accident analysis
2Measurement precision
If environmental conditions are integrated into event detection, then event identification accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent implements dynamic threshold adjustment based on environmental conditions. Instead of using fixed detection thresholds, the system continuously adapts thresholds according to real-time environmental data (temperature, humidity, location). This dynamic approach improves event identification accuracy by accounting for environmental variability while managing data processing complexity through adaptive rather than statically complex algorithms
Solution Approach 2:
The system changes detection parameters (thresholds) based on environmental parameters. By linking detection thresholds to environmental conditions such as temperature, humidity, and geographic location, the system achieves more accurate event identification. The parameter changes are driven by environmental measurements, creating a responsive detection system that adapts to varying operating conditions without requiring overly complex processing architectures
3Loss of time
If real-time detection is implemented, then response time is reduced, but computational resource requirements increase
Solution Approach 1:
The patent applies partial action by implementing real-time detection for critical vehicle events while using asynchronous processing for less time-sensitive environmental data monitoring. The system prioritizes processing of safety-critical sensor data (accelerometer, gyroscope) over environmental sensor data, achieving fast response times for important events while managing computational resource requirements through selective real-time processing
Solution Approach 2:
The system uses self-service mechanisms through event-triggered processing. Instead of continuously processing all sensor data at maximum computational intensity, the system activates intensive processing only when events are detected or environmental thresholds are exceeded. Normal operation uses lightweight monitoring, and computational resources are engaged on-demand, reducing overall energy consumption while maintaining real-time detection capabilities for critical events
Data Source
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AI summary
This disclosure relates to a system and method for detecting vehicle events. Some or all of the system may be installed in a vehicle, operate at the vehicle, and/or be otherwise coupled with a vehicle. The system includes one or more sensors configured to generate output signals conveying information related to the vehicle. The system receives contextual information from a source external to the vehicle. The system detects a vehicle event based on the information conveyed by the output signals from the sensors and the received contextual information.