Distributed Video Surveillance Camera Allocation
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Solution Overview
Problem
Current video surveillance systems face challenges in effectively managing and storing large amounts of video data, with appliance-based systems being limited in scalability and capacity, and enterprise server-based systems being costly and complex, with static camera-to-server mappings that lead to inefficiencies and high costs.
Innovation Solution
A distributed video surveillance system with abstracted functional layers that dynamically reconfigure camera-to-node mappings, allowing cameras to be reassigned and processed across multiple nodes based on priority and computational load, using standard web browsers for client access without proprietary software, and abstracted storage for flexible data retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a network video recorder or enterprise server is used to capture and store video data, then video data management capability is improved, but device complexity and cost increase
Solution Approach 1:
The system divides video surveillance functionality into independent camera nodes that can operate autonomously. Each camera node captures, processes, and stores video data locally, eliminating the need for a centralized network video recorder or enterprise server. This segmentation reduces system complexity while maintaining video data management capability.
Solution Approach 2:
Camera nodes are designed to be self-sufficient units that perform video capture, processing, and storage without requiring external centralized control. Each node independently manages its video data streams, reducing the need for complex centralized management infrastructure.
2Adaptability or versatility
If more video cameras are added to increase surveillance coverage, then monitoring capability is improved, but computational load and storage requirements exceed system capacity
Solution Approach 1:
The system segments video processing loads across multiple independent camera nodes rather than concentrating all computational tasks in a single centralized system. This distribution allows the system to handle increased surveillance coverage without overwhelming any single node's computational capacity.
Solution Approach 2:
The camera allocation configuration is dynamically adjustable, allowing the system to adapt computational and storage loads as cameras are added or removed. The master node can reallocate camera assignments to different camera nodes based on current system capacity and demand, maintaining balance even as surveillance coverage expands.
3Power
If cameras are selectively disconnected to reduce computational load, then system capacity is preserved, but surveillance coverage is reduced
Solution Approach 1:
The system employs dynamic camera allocation where the master node continuously monitors system capacity and automatically reconnects or disconnects cameras based on available resources. When capacity is exceeded, low-priority cameras are temporarily disconnected; when capacity becomes available, cameras are automatically reconnected, maintaining optimal surveillance coverage while preserving system capacity.
Solution Approach 2:
The master node implements feedback mechanisms by monitoring computational load and storage capacity at each camera node. Based on this feedback, the system automatically adjusts camera allocations, disconnecting cameras when capacity is exceeded and reconnecting them when capacity is available, creating a self-regulating system that balances capacity utilization with surveillance coverage.
Data Source
AI summary
A distributed video management system that allows for monitoring a camera allocation parameter and dynamic reallocation of video cameras to available camera nodes in response to detecting a change in the allocation parameter including selectively dropping at least one camera from the system based on a priority of the camera. The change in allocation parameter may be due to a number of potential contexts including a change in availability of camera nodes, a change in the nature of the video data captured, a change in computational load, or other change that results in a change in allocation parameter. The disconnection or “dropping” of a camera may be temporary in response to an increase in computational load on the system. The use of priority values of the cameras may allow for sufficient camera coverage to be provided by the system while maintaining processing of video data from higher priority cameras.