IIoT Sensor Crosspoint Switching for Real-Time Industrial Data Collection
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Solution Overview
Problem
Heavy industrial environments face challenges in data collection and utilization due to the complexity of dealing with data from multiple sensors, limiting the effectiveness of 'smart' solutions for optimization and diagnosis, with existing methods being time-consuming and inefficient.
Innovation Solution
The implementation of a system for continuous ultrasonic monitoring, cloud-based machine pattern recognition, on-device sensor fusion, self-organizing data marketplaces, and AI training based on industry-specific feedback, along with a distributed ledger for tracking transactions, enables efficient data collection, processing, and utilization at the edge and in the cloud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is collected by human beings using dedicated data collectors and recorded on media for later analysis, then data collection is performed, but the process is time-consuming and takes weeks or months to complete analysis
Solution Approach 1:
The patent replaces manual data collection and analysis methods with automated electronic systems. Sensors continuously collect data from industrial equipment, and cloud-based platforms automatically process and analyze the data using algorithms and machine learning, eliminating the need for human operators to manually record and analyze data batches.
Solution Approach 2:
The system implements continuous data collection and analysis rather than batch processing. Sensors continuously monitor equipment parameters, and the cloud platform continuously processes data streams, enabling real-time detection and response to equipment issues without the delays inherent in periodic manual collection and analysis.
2Device complexity
If the range of available data is limited in complex industrial environments, then data collection is simplified, but the effectiveness of smart solutions for optimization and diagnosis is reduced
Solution Approach 1:
The cloud-based platform serves multiple functions: it collects data from various sensors, stores data in databases, processes data using multiple algorithms, performs predictive analytics, generates maintenance recommendations, and provides user interfaces for different stakeholders. This multi-functional system handles diverse industrial data types without requiring separate specialized systems for each function.
Solution Approach 2:
The cloud-based platform acts as an intermediary between industrial equipment and analysis tools. It receives raw data from sensors on equipment, processes and structures the data, applies analytical algorithms, and delivers processed insights to users. This intermediary layer simplifies the complexity by centralizing data handling and analysis capabilities in one accessible platform.
3Ease of operation
If batches of data are returned to a central office for analysis, then centralized control is maintained, but the speed and efficiency of data-driven decision-making is significantly reduced
Solution Approach 1:
The system transitions from two-dimensional batch data transfer (physical media to central office) to multi-dimensional continuous data streaming (sensors to cloud platform). Data is transmitted continuously over networks in real-time, enabling simultaneous access and analysis by multiple users and systems, thereby increasing decision-making speed while maintaining centralized management capabilities.
4Device complexity
If manual data collection and analysis methods are used, then system simplicity is maintained, but intelligence and automation capabilities are limited
Solution Approach 1:
The cloud-based platform performs self-service through automated data processing pipelines. The system automatically ingests data from sensors, cleans and validates data, applies appropriate analytical algorithms, generates insights and recommendations, and delivers results to users without requiring manual intervention at each step. This automation maintains system simplicity from the user perspective while enabling advanced intelligent capabilities.
Data Source
AI summary
The system generally includes a crosspoint switch in a local data collection system having multiple inputs and multiple outputs including a first input connected to a first sensor and a second input connected to a second sensor. The multiple outputs include a first output and a second output configured to be switchable between a condition in which the first output is configured to switch between delivery of a first sensor signal and a second sensor signal and a condition in which there is simultaneous delivery of the first sensor signal and the second sensor signal. Each of multiple inputs is configured to be individually assigned to any of the multiple outputs. The local data collection system includes multiple data acquisition units each having an onboard card set configured to store calibration information and maintenance history. The local data collection system is configured to manage data collection bands.