Vehicle Video Monitoring Event Labeling and Retrieval
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Solution Overview
Problem
Current vehicle video monitoring systems do not provide easily usable video files for supervisors to identify and review driver behavior incidents efficiently, requiring extensive review of long recordings for incidents like poor driving habits or violations.
Innovation Solution
A system that captures and buffers video data from vehicles, detects triggering events such as speeding or seatbelt violations, and saves relevant video clips with descriptive labels, allowing for efficient retrieval and analysis of specific incidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire video recording is saved and reviewed to identify driver behavior incidents, then complete coverage of all incidents is achieved, but the time and effort required for review increases significantly
Solution Approach 1:
The system extracts only the relevant portions of video data associated with triggering events rather than reviewing the entire recording. When a triggering event is detected, the system saves a specific time window around that event, isolating the incident from the rest of the footage for efficient review.
Solution Approach 2:
The system performs preliminary processing by automatically detecting triggering events and saving relevant video clips during the driving shift, so that when supervisors need to review incidents, the work is already done. This preliminary detection and segmentation eliminates the need for manual review of entire recordings.
2Productivity
If video data is segmented by manual review to identify violations, then incident identification is achieved, but the process becomes complex and less efficient
Solution Approach 1:
The system performs automatic detection and segmentation of video data without requiring manual intervention. The monitoring system itself identifies triggering events and creates the segmented video clips, eliminating the need for third-party reviewers to manually watch and divide the footage.
Solution Approach 2:
The system replaces manual mechanical review processes with automated electronic detection and processing. Sensors and processors automatically identify triggering events and generate segmented video files, substituting human reviewers with an automated system that is both faster and more consistent.
3Ease of operation
If minimal information is provided on video segments, then file simplicity is maintained, but supervisors cannot easily search or prioritize specific types of violations
Solution Approach 1:
The system applies different levels of information detail to different aspects of the video files. The file names contain specific event type information for searchability, while the video content itself maintains its original quality. This localized enhancement of metadata provides search capability without affecting the core video data.
Data Source
AI summary
System and method for capturing video data, comprising buffering video data captured from a video recording device in a vehicle, detecting a triggering event, saving a portion of the video data occurring within a specified period of time near the event, and naming a saved portion of video data with a label associated with the triggering event.