Vehicle Event Detection With Sensor-Triggered Data Offloading
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Solution Overview
Problem
Current systems for detecting and recording vehicle events rely on single sensors, which are limited in accuracy and real-time capability, and lack efficient methods for offloading event records from vehicles to external systems.
Innovation Solution
A system comprising sensors, servers, and processors that generate and analyze output signals to detect vehicle events in real-time, select subsets of sensors for specific event types, and transmit event records to external systems for storage and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single sensor is used to detect vehicle events, then the system complexity is reduced, but the measurement precision and reliability of event detection deteriorates
Solution Approach 1:
The system segments the detection task by using multiple sensors (accelerometer, gyroscope, magnetometer, barometer, microphone, camera) to detect different aspects of vehicle events. Each sensor captures specific physical quantities, and the processor integrates these segmented measurements to achieve comprehensive and precise event detection without requiring a single complex sensor.
2Loss of information
If all sensor data is continuously recorded and stored, then the completeness of event information is improved, but the loss of time for data transmission and the energy consumption increase
Solution Approach 1:
The processor performs preliminary analysis of sensor data in real-time to identify events matching predefined criteria (collisions, falls, theft attempts). Only when an event is confirmed does the system capture and store the corresponding sensor data segment. This preliminary filtering action prevents unnecessary continuous recording and transmission, reducing data transmission time while maintaining event information completeness.
3Reliability
If multiple sensors are used to detect vehicle events, then the measurement precision and reliability are improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The system divides the monitoring function across multiple specialized sensors, each optimized for detecting specific physical quantities (acceleration, rotation, magnetic field, pressure, sound, visual). This segmentation improves reliability by using appropriate sensors for specific detection tasks while keeping each sensor component relatively simple and well-understood.
Solution Approach 2:
The central processor serves as a universal component that handles data from all sensor types, performs event detection algorithms, and manages data storage and transmission. This multi-functional processor consolidates the complexity into a single coordinating unit rather than requiring separate processing circuits for each sensor.
4Loss of time
If event data is stored locally in the vehicle, then the data availability for immediate analysis is improved, but the loss of time for data retrieval and the energy consumption increase
Solution Approach 1:
The system extracts and transmits only the essential event data (sensor readings during the event window, event type, timestamp, location) to external servers or authorized devices. By taking out only the critical information needed for analysis rather than continuously accessing local storage, the system reduces data retrieval time and minimizes energy consumption from the vehicle's electrical system.
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.