Cloud Vehicle Incident Detection Using Two-Phase Data Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle-incident detection systems face challenges in accurately verifying vehicle-related events, often relying on incomplete data and prone to false notifications, which can lead to unnecessary emergency dispatches.
Innovation Solution
A cloud-based vehicle-incident detection method that combines initial sensor data with subsequent vehicle operation data, using a broader dataset including vehicle speed, location, and other parameters to classify events, and notifies authorities only when a verified incident occurs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional vehicle data is collected and analyzed, then detection accuracy is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The detection system is divided into multiple independent components: initial event detection module, additional data collection module, and analysis module. The system segments data collection into two distinct phases (initial vehicle data and subsequent additional vehicle data) that can be processed independently, reducing overall system complexity while maintaining high detection accuracy through comprehensive analysis.
2Reliability
If additional vehicle data is collected and analyzed, then false alarm reduction is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary data collection by gathering initial vehicle data immediately upon detecting a potential event, and simultaneously begins collecting additional subsequent vehicle data in parallel. This preliminary action approach allows both datasets to be prepared in advance, enabling rapid comprehensive analysis that reduces false alarms without significantly increasing processing time.
Data Source
AI summary
A vehicle-incident detection method is disclosed herein. Vehicle data is received at a cloud computing system from a vehicle, where the vehicle data is generated by the vehicle in response to an initial detection of a vehicle-related event. After receiving the data, the cloud computing system requests additional vehicle data from the vehicle. The additional vehicle data is generated by the vehicle at a time subsequent to the initial detection of the vehicle-related event. The additional vehicle data is received from the vehicle, and an application resident in the cloud computing system analyzes the vehicle data and the additional vehicle data to determine that the vehicle-related event occurred. The application includes computer readable code embedded on a non-transitory, tangible computer readable medium for performing the analyzing. Also disclosed herein is a vehicle-incident detection system.