Sensor Data Processing for Real-Time Monitoring
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Solution Overview
Problem
Current monitoring systems lack efficient methods for real-time data collection and analysis from multiple sensor units, leading to suboptimal operational efficiency and decision-making in environmental and electrical monitoring within facilities.
Innovation Solution
A monitoring system comprising multiple multi-sensor units, a gateway device, and a monitoring data analysis system that communicates via electromagnetic signals and networks, enabling bidirectional data transmission and processing to populate a measurement database, analyze data, and generate control data for sensor units, facilitating adaptive measurement collection and resource allocation based on detected conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous data collection from multiple sensor units is performed, then measurement coverage and monitoring completeness are improved, but data processing complexity and system resource consumption increase
Solution Approach 1:
The patent segments the data processing task by collecting and pre-processing data at individual sensor units before transmitting to the central server. Each sensor unit independently processes its own measurements, filtering and preparing data locally, which reduces the processing burden on the central system while maintaining comprehensive monitoring coverage across multiple units
Solution Approach 2:
The patent implements preliminary data processing at the sensor units before data transmission to the central server. Measurements are pre-filtered, validated, and formatted at the source, allowing the central system to receive only processed data rather than raw data from all sensors, thereby reducing overall processing complexity
2Measurement precision
If all measurement data is transmitted to the central server, then data analysis accuracy is improved, but network bandwidth consumption and transmission time increase
Solution Approach 1:
The patent extracts and removes unnecessary data from the transmission process by performing data filtering and selection at the sensor units. Only processed and validated measurement data is extracted for transmission to the central server, reducing the volume of data sent over the network while maintaining the accuracy needed for analysis
Solution Approach 2:
The patent applies partial data transmission by sending only the necessary processed data from each sensor unit rather than all raw data. The system transmits selective measurements that have been pre-filtered for relevance, avoiding unnecessary bandwidth consumption while preserving data analysis accuracy
3Loss of time
If real-time data processing is implemented, then response time to anomalies is improved, but computational resources and processing power requirements increase
Solution Approach 1:
The patent segments computational tasks between edge devices (sensor units) and central server. Simple real-time processing and anomaly detection are performed at the sensor units using minimal computational resources, while more complex analysis is deferred to the central server, enabling real-time response without excessive computational demands
Solution Approach 2:
The sensor units perform self-processing of their own data locally, including basic validation, filtering, and preliminary anomaly detection. This self-service approach enables real-time local response to conditions without requiring continuous computational support from external systems, reducing overall power requirements
Data Source
AI summary
A method for execution by a monitoring data analysis system includes receiving a plurality of measurement data from the gateway device, each indicating a measurement generated by one of a plurality of multi-sensor units. A set of measurement entries are generated based on the plurality of measurement data, and the set of measurement entries are added to a measurement database. A custom function definition for a custom function is received from a client device based on user input to a graphical user interface. Custom function output is generated by performing the custom function on a filtered subset of the plurality of measurement entries by utilizing the custom function definition. The custom function output is transmitted to the client device for display via the graphical user interface.