Data fusion system based on data evaluation and system coordination module and working method of data fusion system

Abstract

The invention relates to a data fusion system based on a data evaluation and system coordination module and a working method of the data fusion system. The data fusion system comprises an informationcollection module, an information processing module, an application and feedback module, the data evaluation and system coordination module, a knowledge base module and a data base module. A data analysis and algorithm selection mechanism of the data evaluation and system coordination module performs two times of analysis before and after on collected data through data itself and expert or user feedback information, so that an algorithm suitable for a current data fusion system is determined to coordinate module resources of the system. The introduction of data evaluation and system coordination enables the system to perform ''act according to actual circumstance'' on the data during answering the specific data under the premise of meeting the user requirements, a suitable processing method is selected, the selective rationality of the algorithm and the universality of the system are ensured, the whole data fusion process is more flexible and efficient, and the result is more reliable.

Description

technical field [0001] The invention relates to a data fusion system based on a data evaluation and system coordination module and a working method thereof, belonging to the technical field of data fusion. Background technique [0002] Data fusion refers to the analysis, synthesis and calculation of observation information from multiple sensors or sources, so as to obtain more accurate and complete results than a single data source. It was originally used in the military field, and has gradually been widely used in various fields such as industrial manufacturing, smart home, and medical diagnosis. [0003] Most of the information to be processed in data fusion comes from different aspects of the same target. For example, when judging the status of human body signs, by analyzing and computing the body temperature, blood pressure, pulse, heart rate and other sign information collected by multi-source sensors, using data Fusion algorithm and decision rules get the final judgme...

AI Technical Summary

Problems solved by technology

Regardless of the application scenario, whether or not an appropriate algorithm can be selected for data processing determines the effectiveness of the entire data fusion system. In an increasingly complex system structure, when faced with various data from different sources and with different characteristics, often only The use of specific algorithms often cannot meet the requirements of data fusion systems

The lack of "flexibility" in the system is not conducive to the expansion and wide application of the system

[0005] To sum up, the current data fusion technology still lacks a unified framework and cannot cope with complex and changeable application scenarios. The algorithms used cannot achieve the best results when faced with data from different sources and with different characteristics.

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