Research on Data Fusion and Analysis Based on Artificial Intelligence Algorithm in Sensor Networks

Abstract

This paper discusses the data fusion and analysis technology based on artificial intelligence algorithm in sensor networks. Firstly, the basic concept, composition and structure of sensor network are summarized, and its characteristics and challenges are analyzed. Then, the basic principle of data fusion technology and its application in sensor networks are introduced, and the basic concept, classification and application of artificial intelligence algorithm in data fusion are described in detail. On this basis, this paper constructs a data fusion framework based on artificial intelligence, and proposes a new data fusion method combining deep learning and machine learning algorithm. This method can effectively improve the accuracy and reliability of sensor data and reduce data redundancy and noise interference. In addition, the thesis also conducts in-depth research on the application scenarios of data fusion and analysis in sensor networks, including Environmental monitoring, intelligent transportation, medical health and other fields. The effectiveness and practicability of the proposed method are verified by experiments and case studies. Experimental results show that the data fusion technology based on artificial intelligence algorithm can significantly improve the data processing ability and analysis accuracy of sensor networks, and provide strong support for related applications. Finally, this paper summarizes the main conclusions of the study, and points out the shortcomings of current research and future prospects. In the future, the data fusion method based on artificial intelligence will be further optimized and improved, and its application in more fields will be expanded, which will provide more powerful support for the development and application of sensor network technology.