Industrial IoT Sensor Switching for Real-Time Edge 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 improved 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 processed in batches at a central office, then data collection and analysis can be performed, but the process takes weeks or months and is limited to specific sensor data sets
Solution Approach 1:
The patent segments the centralized data processing function into distributed edge computing nodes deployed at multiple locations within the industrial environment. Each edge node independently processes sensor data locally, eliminating the need to transport all data to a central office and enabling parallel processing across multiple segments simultaneously.
Solution Approach 2:
The patent implements preliminary data processing and filtering at the edge devices before data is transmitted to central systems. This preliminary action reduces the volume of data requiring centralized analysis and provides faster initial insights, cutting down the overall processing time from weeks to near-real-time.
2Loss of information
If multiple sensors are deployed to capture comprehensive industrial data, then more complete information is obtained, but the complexity of dealing with this data increases significantly
Solution Approach 1:
The patent merges multiple sensor data streams and processing functions into integrated edge computing devices that can handle heterogeneous sensor inputs uniformly. This consolidation reduces the operational complexity of managing multiple separate data collection systems while maintaining comprehensive data coverage.
Solution Approach 2:
The patent implements self-service mechanisms where edge devices automatically perform data validation, filtering, and preliminary analysis without requiring centralized intervention. This autonomy reduces the complexity burden on central systems and enables the deployment of numerous sensors without proportionally increasing overall system complexity.
3Use of energy by moving object
If batch processing of sensor data is used for analysis, then resource consumption is reduced, but the ability to provide real-time monitoring and intelligent diagnosis is limited
Solution Approach 1:
The patent implements periodic action by alternating between low-power batch processing modes and active real-time analysis modes. During normal operation, edge devices perform lightweight periodic monitoring with minimal energy consumption, and only activate full processing capabilities when anomalies are detected or during scheduled analysis cycles, thus balancing energy efficiency with real-time responsiveness.
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.