Distributed Surveillance Metadata Processing for Bandwidth Reduction
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Solution Overview
Problem
Large-scale surveillance systems face inefficiencies in data analysis due to the cumbersome and time-consuming process of collecting and processing data from multiple locations, leading to delays in identifying potentially relevant information for law enforcement.
Innovation Solution
A distributed surveillance system architecture that includes Data Collection Nodes (DCNs) and Network Metadata Processing Servers (NMPS), where metadata is generated and analyzed locally at DCNs, reducing the need for centralized processing and enabling quicker identification of relevant data across a wide geographic area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is collected and processed at a central location, then comprehensive surveillance coverage is achieved, but data analysis becomes cumbersome and time-consuming
Solution Approach 1:
The patent divides the centralized surveillance system into distributed Data Collection Nodes (DCNs) that autonomously process data locally. Each DCN segments the data processing task by generating metadata from video feeds and transmitting only this compressed metadata to central servers, thereby maintaining comprehensive surveillance coverage while dramatically reducing central processing time and computational burden.
2Loss of information
If all video data is transmitted to central location for analysis, then complete data availability is ensured, but network bandwidth is excessively consumed
Solution Approach 1:
The patent extracts only the essential metadata from complete video data at the distributed DCNs. This metadata contains the critical information needed for surveillance analysis (such as detected objects, events, or anomalies) without requiring transmission of the entire video feed. This extraction approach ensures complete data availability for analysis while minimizing network bandwidth consumption by transmitting only the necessary information.
3Device complexity
If centralized processing is used, then system simplicity is maintained, but processing speed decreases
Solution Approach 1:
The patent implements a dynamic hybrid architecture where DCNs operate autonomously in the field, performing real-time video analysis and metadata generation. This dynamic distribution of processing tasks to edge devices enables rapid local processing while the central servers coordinate and aggregate results, thereby increasing overall processing speed without significantly complicating the system architecture.
Data Source
AI summary
Operation of a data collection node in a network of data collection nodes includes acquiring data using at least one sensing device of the data collection node. The acquired data is stored in a memory of the data collection node and metadata is generated at the data collection node based on the acquired data. The metadata is analyzed at the data collection node and at least one of the metadata, the acquired data, and an alert is sent from the data collection node to another device on the network based on the analysis of the metadata.