Distributed Tracking System with Graph Database for Scalability
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Solution Overview
Problem
Existing tracking systems lack scalability and efficiency in managing and retrieving tracking information across multiple cameras, with processing loads concentrated on the server device, making it difficult to track individuals across wide ranges and retrieve specific data effectively.
Innovation Solution
A distributed tracking system comprising multiple tracking devices and a server device, where each tracking device captures images, transmits tracking information, and determines object coincidence, while the server stores this information in a graph structure, distributing processing load and enabling high-speed retrieval using unique identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all processing is performed by the server device, then tracking information can be centralized managed, but scalability deteriorates and processing load becomes concentrated
Solution Approach 1:
The patent divides the tracking system into multiple tracking devices (100A, 100B, 100C) that independently perform tracking processing locally. Each device manages its own tracked objects and communicates only necessary information to the server device, segmenting the processing load and enabling scalability while maintaining centralized coordination through the server.
Solution Approach 2:
The server device acts as an intermediary that receives tracking information from multiple tracking devices, stores it in a graph database, and facilitates coordination between devices. This intermediary role allows decentralized tracking while maintaining centralized management capabilities through standardized data exchange protocols.
2Quantity of substance
If tracking information is stored in traditional database structures, then data can be stored efficiently, but retrieval speed deteriorates for specific data across large datasets
Solution Approach 1:
The patent transitions from traditional tabular database structures to a graph database structure where tracking information is represented as nodes and edges. This dimensional change in data organization enables efficient retrieval by traversing relationships through the graph, significantly improving query speed even as data quantity increases across multiple tracking devices.
3Productivity
If multiple tracking devices operate independently, then processing load is distributed, but maintaining database consistency becomes difficult
Solution Approach 1:
The patent implements a feedback mechanism where tracking devices transmit coincidence information to the server device when objects are identified across multiple devices. The server device uses this feedback to update the graph database, ensuring consistency across all tracking devices while allowing independent local processing.
Solution Approach 2:
The patent merges the tracking information from multiple independent tracking devices into a unified graph database structure at the server device. This merging process combines the benefits of distributed processing with centralized data consistency management, as all tracking information is consolidated in a single coherent graph structure that maintains relationships across devices.
Data Source
AI summary
A tracking system that includes a plurality of tracking devices and a server device. Each of the tracking devices: tracks an object; transmits tracking information, which includes at least features and an identifier of the object, to nearby tracking devices and the server device; determines whether an object coincided with an object specified by the transmitted tracking information is included in the currently tracked objects; replaces the identifier of the object with the identifier included in the tracking information; and transmits the coincidence information.