Industrial Plant IoT Edge Monitoring for Secure Low-Latency Analytics
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Solution Overview
Problem
The challenge lies in bridging the gap between highly proprietary industrial manufacturing systems and cloud technologies, particularly in process industries like chemical plants, where high security standards and latency considerations hinder the migration of embedded control systems to cloud computing and data analytics.
Innovation Solution
A system and method are introduced that utilize an IoT Edge unit and hub to preprocess and analyze data from sensors, allowing one-way communication to a cloud-based data sink, reducing data volume through metadata addition and key performance indicator calculation, while maintaining security and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data from industrial plant sensors is transferred to cloud-based data sinks for analysis, then data analytics capability is improved, but data transfer volume and bandwidth requirements increase
Solution Approach 1:
The patent applies preliminary action by performing data preprocessing, filtering, and analysis at the edge device (IoT Edge unit) before data is transmitted to the cloud. This advance processing reduces the volume of data that needs to be transferred while maintaining analytical capabilities, as only relevant processed data and metadata are sent to cloud-based data sinks.
Solution Approach 2:
The patent segments the data processing architecture into multiple layers: edge devices perform local preprocessing and filtering, intermediate servers conduct further analysis, and cloud data sinks receive only essential processed data. This segmentation allows analytics capabilities to be distributed while minimizing the quantity of data transferred across the network.
2Power
If cloud computing systems are used for data analysis, then computational power is improved, but latency and availability concerns worsen due to security restrictions
Solution Approach 1:
The patent introduces intermediary components (IoT Edge units and intermediate servers) that act as mediators between the industrial plant's control systems and cloud computing resources. These intermediaries enable secure data exchange by preprocessing and filtering data locally, reducing the need for frequent cloud communication while maintaining access to cloud computational power when needed.
Solution Approach 2:
Computational tasks are performed in advance at edge devices and intermediate servers before data reaches the cloud, reducing the need for real-time cloud processing. This preliminary computation decreases latency by handling time-critical operations locally while still leveraging cloud power for non-critical analytical tasks.
3Loss of information
If all sensor data is transmitted to central data sinks, then data completeness is improved, but network bandwidth and processing load increase
Solution Approach 1:
The patent extracts only the most relevant features and metadata from complete sensor data at the edge device level before transmission. By taking out essential information (processed data points, metadata, aggregated statistics) while leaving redundant raw data at the source, the system maintains data completeness for analysis purposes while significantly reducing network bandwidth consumption.
Solution Approach 2:
Instead of transmitting all sensor data, the patent applies partial action by selectively transmitting only necessary processed data and metadata to central data sinks. This selective transmission maintains sufficient data completeness for analytical purposes while optimizing network bandwidth efficiency.
Data Source
AI summary
A system for monitoring product processing equipment (20, 30) of an industrial plant is provided. The system comprises a first layer (100) having a plurality of sensors (110-150) configured to detect parameters of the product processing equipment (20, 30) of the industrial plant, a second layer (200) configured to implement a process control system based on data from the first layer (100), and a third layer (300) configured to implement an operational control system. The system furthermore at least one IoT Edge unit (230,310) in the second and/or third layer (200, 300) configured to receive data from the first and/or second layer (100, 200) and to analyse the received data, and an IoT hub (700) configured to remotely control, manage and/or monitor the at least one IoT Edge unit (230, 310).