Vehicle Video Upload via Anomalous Event Detection
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Solution Overview
Problem
Uploading full video footage from vehicles to a storage server consumes excessive network and storage resources, as users are typically interested only in specific moments around events like tire punctures or accidents, necessitating a method to detect and upload relevant video snippets efficiently.
Innovation Solution
A computer-implemented method that monitors video and vehicle data to detect anomalous events, determining the relevant cameras that captured the event and uploading video snippets from these cameras within a specific time window to a video storage server, thereby preserving network and storage resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full video footage from all cameras is uploaded to the storage server, then complete video coverage is achieved, but network and storage resources are excessively consumed
Solution Approach 1:
The system extracts and uploads only the relevant video snippets containing anomalous events rather than uploading complete video footage from all cameras. This is achieved by detecting events such as tire punctures, impacts, or aggressive driving behaviors and uploading only the video segments that capture these specific events, thereby significantly reducing network and storage resource consumption while maintaining the reliability of video coverage for analysis purposes
Solution Approach 2:
The video footage is segmented into specific time windows around detected events rather than uploading continuous video streams. The system divides the video data into relevant segments that contain the anomalous events and their context, uploading only these segmented portions to the storage server, which reduces overall data transmission and storage requirements while preserving essential event information
2Loss of information
If video from all cameras is uploaded, then comprehensive event documentation is achieved, but upload time and network bandwidth are increased
Solution Approach 1:
The system extracts only the necessary video information related to detected events and uploads selectively. By identifying which cameras captured relevant events and uploading only those specific video segments within defined time windows, the system maintains comprehensive event documentation while significantly reducing upload time and network bandwidth consumption compared to uploading from all cameras
Solution Approach 2:
The system applies partial action by uploading video from a subset of cameras that captured relevant events rather than all cameras. This selective approach ensures sufficient event documentation is achieved without the excessive resource consumption of uploading from every camera, optimizing the balance between documentation completeness and upload efficiency
Data Source
AI summary
A computer-implemented method includes: storing, by a computing device, pixel-based classification rules in a memory of a computing device; storing, by the computing device, video uploading rules that identify a subset of a plurality of cameras implemented within a vehicle for which video should be uploaded in the memory of the computing device; detecting, by the computing device, satisfaction of video upload event criteria based on video or image data from at least one of the plurality of cameras and vehicle information comprising one of vehicle sensor information and vehicle diagnostic information; determining, by the computing device, a subset of the plurality of cameras based on the detecting the satisfaction of the video upload event criteria; and uploading, by the computing device, video captured by only the subset of the plurality of cameras to a video storage server.