Sensor Data Transmission Protocol for Industrial Analytics
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Solution Overview
Problem
Existing sensor networks in industrial settings face challenges in efficiently transmitting and processing the increasing amounts of data generated by advanced sensors, particularly in real-time analytics, due to the complexity of signal processing and data management.
Innovation Solution
A computer-implemented system that includes a transmitting device and a receiving device, utilizing protocols to determine and conditionally transmit only the most recent sensor data values that have changed, and processes received data to derive time-aligned values for timely analytics, reducing unnecessary data transmission and enhancing data validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all sensor data values are transmitted periodically, then data completeness is maintained, but data transmission volume and network load increase significantly
Solution Approach 1:
The patent extracts only the essential information (change indicators) from the full sensor data packets. Instead of transmitting complete data sets periodically, the system transmits only indicators showing whether parameter values have changed, thereby reducing transmission volume while maintaining data completeness for analytics.
Solution Approach 2:
The system transmits partial data information selectively. When sensor parameters remain within normal ranges, only minimal change indicators are transmitted. When parameters exceed thresholds or show significant changes, more detailed data is transmitted, optimizing the balance between data completeness and transmission efficiency.
2Speed
If sensor data is transmitted at high frequency, then real-time analytics capability is improved, but network bandwidth and processing resources are consumed
Solution Approach 1:
The patent implements periodic data transmission with adaptive frequency. Instead of continuous high-frequency transmission, the system uses periodic transmissions triggered by parameter changes or threshold exceedances. This maintains real-time analytics capability when needed while conserving network bandwidth during normal operating conditions.
Solution Approach 2:
The transmission frequency and data detail level are made dynamic rather than static. The system adjusts transmission characteristics based on real-time sensor readings, transmitting more frequently and with greater detail when parameters approach critical thresholds, and reducing transmission when conditions are stable, thereby optimizing resource usage.
3Productivity
If complex signal processing is performed at remote locations, then data analysis capability is enhanced, but device complexity and processing requirements increase
Solution Approach 1:
The patent segments the data processing function into two parts: simple change detection and threshold monitoring performed at remote sensor locations, and complex analytics performed centrally at the home office. This segmentation allows enhanced data analysis capability at the home office while keeping remote device complexity minimal.
Solution Approach 2:
The system introduces an intermediary layer that pre-processes sensor data by identifying changes and filtering significant events before transmission. This intermediary processing at the edge reduces the complexity burden on remote devices while enabling comprehensive analytics at the home office through selective data transmission.
Data Source
AI summary
A system for transmitting discrete data packets of sensor measured values of operating parameters. The system includes a transmitting device configured to transmit the measured values per a transmittal protocol. The system includes a receiving device that receives the measured values processes the received measured values in accordance with a receiving protocol. The transmittal protocol includes: determining a most recent measured value for the sensor; selecting previous measured values for the sensor; comparing the most recent measured value to the previous measured values to determine a difference therebetween; and conditionally transmitting the most recent measured value based on the difference. The receiving protocol includes: determining a most recent received measured value for each of the sensors; deriving an analytic time based the most recent received measured values; and deriving a time-aligned value for one of the operating parameters measured by the sensors at the analytic time.