Self-Sufficient Data Acquisition Box for Adaptive Sensor Data Routing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial environments face challenges in data collection and utilization due to complex sensor configurations, variable network conditions, and the need for real-time data management, which limits the effectiveness of monitoring and optimization in heavy industrial settings.
Innovation Solution
The implementation of a system for continuous ultrasonic monitoring, self-organizing data marketplaces, and AI training based on industry-specific feedback, along with a self-sufficient data acquisition box that dynamically reconfigures data transmission and storage, enabling efficient data collection and processing at the edge and in the cloud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is collected and returned to a central office for analysis, then data analysis can be performed, but the time scale is weeks or months and only limited data sets can be handled
Solution Approach 1:
The patent segments the centralized data analysis system into distributed edge computing nodes (data acquisition boxes) that perform local signal processing and analysis. Each box independently processes sensor data from its associated sensors, eliminating the need to transport all raw data to a central office and enabling real-time analysis decisions at the source.
Solution Approach 2:
The data acquisition boxes perform preliminary signal processing, filtering, and analysis functions locally before potentially transmitting results to central systems. This preliminary action at the edge reduces the volume of data requiring central processing and enables immediate response to critical events without waiting for central office analysis.
2Reliability
If sensor configurations are conservative and detect many parameters, then comprehensive monitoring is achieved, but parameters that are not needed during most operations are detected increasing complexity
Solution Approach 1:
The system dynamically reconfigures sensor activation and data collection parameters based on real-time operational context, process stage, and detected anomalies. The data acquisition boxes adjust which sensors are active and what sampling rates are used, transitioning from comprehensive monitoring during critical operations to selective monitoring during normal operations, thereby reducing complexity while maintaining reliability.
Solution Approach 2:
The patent changes operational parameters of the sensor system based on process conditions, including sampling frequency, active sensor subsets, and data transmission intervals. This allows the system to maintain comprehensive monitoring capability when needed while reducing complexity during routine operations by adjusting parameters rather than maintaining fixed conservative configurations.
3Speed
If data is transmitted continuously from multiple sensors, then real-time monitoring is achieved, but network bandwidth and data management become challenging under variable network conditions
Solution Approach 1:
The data acquisition boxes extract and process only the essential features and anomalies from raw sensor data before transmission to central systems. By taking out only the critical information rather than transmitting complete raw data streams, the system achieves real-time monitoring capability while significantly reducing network bandwidth requirements and simplifying data management at central offices.
Solution Approach 2:
The system transmits data at varying levels of detail based on operational needs and network conditions. During normal operations, only essential parameters are transmitted at reduced sampling rates, while during critical events or when network bandwidth is available, more comprehensive data is transmitted. This partial action approach balances real-time monitoring needs with network management constraints.
Data Source
AI summary
The present disclosure describes systems for data collection in an industrial environment having a self-sufficient data acquisition box for capturing and analyzing data in an industrial process. A system can include a data circuit for analyzing a plurality of sensor inputs, and a network control circuit for sending and receiving information related to the sensor inputs to an external system. The system may provide sensor data to a plurality of other similarly configured systems, and the system dynamically reconfigures where it sends data and what quantity of data it sends based on an availability of the other similarly configured systems.