Hierarchical Distributed Architecture for Container Security Monitoring
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Solution Overview
Problem
Current container security systems face challenges in efficiently monitoring and tracking the contents of shipping containers due to high false alarm rates, network congestion, and increased costs as the number of monitored containers grows, with most systems relying on centralized processing and human intervention.
Innovation Solution
A hierarchical distributed processing architecture is implemented, where information and decision support processing are distributed across discrete layers, including sensor, container, collection, and data fusion center elements, allowing for localized data processing and reduced data transmission, thereby enhancing computational capacity and reducing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If centralized processing architecture is used, then system simplicity is maintained, but processing speed and information handling capacity deteriorate
Solution Approach 1:
The patent divides the container security system into hierarchical layers: sensor level (individual sensors), container level (container processors), collection level (relay processors), and data fusion center. Each layer processes information locally before passing to the next level, distributing the processing burden and enabling parallel operation across multiple containers and sensors simultaneously.
Solution Approach 2:
The patent introduces a hierarchical dimension to the system architecture, organizing processors across multiple levels (sensor→container→collection→fusion) rather than a single centralized level. This dimensional organization allows information to flow upward through the hierarchy while enabling local processing at each level, thus increasing overall processing capacity without linearly increasing central complexity.
2Loss of information
If all sensor data is transmitted to central monitoring station, then complete information is available, but network congestion and communication costs increase
Solution Approach 1:
The patent extracts and processes information locally at container-level processors and collection-level relay processors before transmission to the central data fusion center. Container processors filter sensor data and extract relevant security events, while relay processors aggregate data from multiple containers, removing redundant information before network transmission and reducing communication bandwidth requirements.
Solution Approach 2:
The patent performs preliminary information processing and filtering at lower hierarchical levels before data reaches the central monitoring station. Container processors pre-process sensor readings and identify anomalies, while relay processors further aggregate and validate data, ensuring that only essential information consumes network bandwidth and that the central station receives pre-processed, high-value data.
3Reliability
If human operators monitor all container events, then comprehensive security oversight is achieved, but false alarm rates and operational costs increase
Solution Approach 1:
The patent implements self-service through automated decision support processors at multiple hierarchical levels that independently analyze sensor data, identify security events, and generate alerts without requiring constant human intervention. The system autonomously filters false alarms through multi-level validation, with container processors and relay processors performing automated anomaly detection and correlation before presenting refined alerts to human operators.
Data Source
AI summary
A hierarchical and distributed system architecture for a container monitoring and security system is provided. The architecture may be a hierarchical chain of separate, related processing elements. The partitioning of functions and distribution of processing among these or other similar hierarchical elements in the network is provided. The elements may further be described in successive layers, each have a greater level of network intelligence than the former.