Sensor Metadata Matching for Reduced Processing Load
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Solution Overview
Problem
The increasing demand for real-time matching of sensing data from multiple providers to multiple users leads to a significant processing load, particularly when sensors on mobile objects require constant metadata position updates, necessitating a reduction in processing load to efficiently specify and deliver required sensing data.
Innovation Solution
A control device and sensor management device system that acquires and compares metadata between sensors and applications, using dynamic handling conditions to determine if sensing data meets specific requirements, thereby reducing processing load and preventing redundant data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time matching is performed between sensor metadata and application metadata to deliver sensing data to appropriate users, then the accuracy and timeliness of data delivery is improved, but the processing load increases significantly
Solution Approach 1:
The patent applies preliminary action by performing static matching between sensor metadata and application metadata in advance, before real-time data delivery. The control device acquires sensor-side metadata and application-side metadata, executes matching to extract sensors that can provide required sensing data, and generates data flow control commands beforehand. This pre-processing reduces the processing load during real-time operation while maintaining delivery accuracy.
Solution Approach 2:
The patent segments the metadata matching process into static components and dynamic components. Static metadata (such as sensor type, data format, positional information) is matched in advance to generate data flow control commands. Dynamic metadata (such as real-time positional updates for mobile objects) is handled separately through event conditions. This segmentation allows the system to reduce processing load by handling only necessary dynamic updates in real-time.
2Measurement precision
If constant matching is performed for mobile objects to update metadata position information in real-time, then the position accuracy is improved, but the processing load increases
Solution Approach 1:
The patent applies dynamics by making the metadata handling adaptive based on the state of the sensor. For mobile objects, the system distinguishes between static metadata (sensor type, data format) that is matched in advance, and dynamic metadata (positional information) that is updated through event conditions. The data flow control commands include dynamic handling conditions that are executed only when changes occur, rather than performing constant matching for all mobile objects.
Solution Approach 2:
The patent implements periodic action through event conditions that trigger metadata updates only when necessary. Instead of continuous matching, the system monitors for specific events (such as position changes of mobile objects) and performs matching only when these events occur. This event-driven approach maintains position accuracy while significantly reducing the processing load compared to constant matching.
3Reliability
If comprehensive metadata matching is performed to ensure all requirements are met, then the completeness of data delivery is improved, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by performing comprehensive static metadata matching in advance. The control device acquires and compares sensor-side metadata and application-side metadata, executes matching to extract suitable sensors, and generates data flow control commands before real-time data delivery. This pre-processing ensures that all static requirements are verified beforehand, reducing the need for time-consuming checks during real-time operation.
Solution Approach 2:
The patent segments the matching process into static and dynamic components. Static metadata matching (sensor type, data format, basic compatibility) is performed comprehensively in advance to ensure completeness. Dynamic metadata (real-time positional information, mobile object updates) is handled through event conditions that are evaluated only when changes occur. This segmentation ensures comprehensive requirement verification while minimizing processing time during data delivery.
Data Source
AI summary
A communication unit acquires sensor-side metadata, which is information relating to a sensor, and application-side metadata, which is information relating to an application. A comparison unit extracts a sensor that can provide the sensing data through matching between the sensor-side metadata and the application-side metadata, and a notification unit transmits, based on a result of the extraction, a data flow control command to a sensor management device. The sensor-side metadata and the application-side metadata contain data that can be handled as dynamic data.