On-Premise Cloud Agent for Industrial Data Ingestion
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Solution Overview
Problem
Industrial automation systems generate vast amounts of data that are typically limited to local networks, restricting access and utilization for analytics and reporting across geographically diverse industrial enterprises.
Innovation Solution
An on-premise cloud agent architecture that collects industrial data from various sources, compresses it, and uploads it to a cloud platform with priority message queuing and blob storage, enabling intelligent sorting and organization based on contextual parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If industrial data is stored locally on private networks, then data security and control are maintained, but data accessibility and utilization across geographically diverse facilities are restricted
Solution Approach 1:
The patent introduces an on-premise cloud agent as an intermediary component that bridges local industrial data sources and remote cloud storage. The agent collects data locally, compresses it, and transmits it to cloud repositories, enabling centralized data accessibility without requiring complex private network infrastructure across all facilities. This mediator approach resolves the contradiction by providing cloud-level accessibility through a simple local agent rather than complex network connections.
2Productivity
If industrial data is transmitted to cloud platform, then data aggregation and analytics capability are enhanced, but data transmission time and network bandwidth consumption increase
Solution Approach 1:
The patent applies preliminary action by performing data compression at the source (on-premise cloud agent) before transmission to the cloud platform. The compression process reduces the volume of data that needs to be transmitted, thereby decreasing transmission time and network bandwidth consumption while still achieving comprehensive data aggregation. This pre-processing step resolves the contradiction by preparing data in advance to minimize transmission overhead.
3Quantity of substance
If data compression is applied to industrial data, then storage efficiency and transmission bandwidth are improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies local quality by performing compression operations at the distributed on-premise cloud agents rather than centralizing all processing at the cloud platform. Each agent compresses data locally using computational resources available at that location, distributing the processing load across multiple nodes. This approach improves storage efficiency and reduces transmission bandwidth while avoiding concentration of computational resource consumption at a single point, resolving the contradiction through distributed processing.
Data Source
AI summary
A cloud agent facilitates collection of industrial data from one or more data sources on the plant floor and migration of the collected data to a cloud platform for storage and processing. Collection services associated with the cloud agent perform on-premise data collection of historical, live, and/or alarm data directly from industrial devices networked to the agent or from intermediate data concentrators that gather the data from the devices. Queue processing services executed by the cloud agent package the data into a data packet comprising header information that identifies a customer associated with the industrial enterprise, processing priority information, and other information that informs data processing services on the cloud platform how to process and/or direct the incoming data. The cloud agent then establishes a communication channel to the cloud platform and sends the data via the channel.