Video Data Routing Server for Scalable Multi-Channel Analysis
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Solution Overview
Problem
Current video data processing systems face limitations in handling multiple channels simultaneously, requiring structural modifications for new video channels and lacking efficient search capabilities for analyzed data, which restricts scalability and user participation in deep learning for object recognition.
Innovation Solution
A system that allocates video data to specific video analyzing servers based on characteristics, performs analysis, generates metadata, and stores it in a database for efficient search, allowing multiple users to participate in deep learning through a web interface and utilizing a routing server, video database, metadata database, and search server for efficient video data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a conventional video data processing system is used, then specific information can be analyzed for a single purpose, but the system cannot handle multiple channels simultaneously and requires structural modifications for new video channels
Solution Approach 1:
The system divides video data processing into separate modules: video receiving units for different channels, a central routing server, and multiple video analyzing servers. Each channel's video data is processed independently by allocated analyzing servers, allowing the system to handle multiple channels simultaneously without requiring overall structural modification when adding new channels.
Solution Approach 2:
The routing server and video analyzing servers are designed as universal components that can handle various types of video data from different channels. The routing server universally routes video data based on channel identification information, and the analyzing servers can process video data from any channel, making the system adaptable to multiple channels without channel-specific dedicated infrastructure.
2Productivity
If video data from multiple channels is processed simultaneously, then more comprehensive analysis is achieved, but the system lacks efficient search capabilities for analyzed data
Solution Approach 1:
The system performs preliminary actions by generating and storing metadata for each video data segment before actual search operations. The routing server creates metadata including channel identification information, object recognition results, and time stamps, which are stored in association with the video data. This preliminary metadata generation enables efficient search operations without affecting the video data processing capacity.
3Measurement precision
If a routing server allocates video data to specific analyzing servers based on video characteristics, then recognition efficiency increases, but the system requires sophisticated routing logic
Solution Approach 1:
The routing server implements local quality by allocating video data to analyzing servers based on specific characteristics of the video data such as channel type, object category, and time of day. Different analyzing servers can be optimized for different types of video analysis, and the routing server directs appropriate video data to the most suitable server, improving recognition accuracy without requiring all servers to handle all types of video data.
Data Source
AI summary
A system for integrated analysis and management of video data includes a routing server configured to receive video data from an external input video providing device, a video database configured to store the received video data, a video analyzing server cluster including a plurality of video analyzing servers configured to analyze the video data, a metadata database configured to store metadata of the video data, and a video search server configured to search the metadata database and the video database. As described in various embodiments of the present disclosure, the system can perform integrated analysis of various video data received from a number of channels and provide an analysis result, and can also rapidly provide an accurate search result in response to a user's request for search.