scholarly journals Interoperability technology of sports health monitoring equipment based on multi-sensor information fusion

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Di Zhang
Keyword(s):  
Information Fusion ◽  
Health Monitoring ◽  
Integrated System ◽  
Living Standard ◽  
Application Framework ◽  
Fusion Technology ◽  
Fusion Algorithm ◽  
Monitoring Equipment ◽  
Application Model ◽  
Sensor Information

AbstractNowadays, the pace of society is accelerating, people’s living standard has been greatly improved compared with the past, and we pay more and more attention to the real-time, flexibility, and intelligence of medical services. Information fusion technology is the study of how to effectively and comprehensively utilize multi-sensor information to overcome information imperfections and uncertainties. In recent years, it has become a hotspot for research, but with the development of communication technology, electronic technology, and computers, the form of information becomes complicated and diverse in science and technology such as technology. In this case, the information obtained by a single sensor is always imperfect, so multiple sensors must be used to detect the target from multiple angles. Obtaining more dimensional information about the target and fusing it to ensure the integrity and accuracy of the information helps to accurately determine the physiological health of the human body. This paper analyzes the multi-sensor information fusion technology in detail, discusses the basic principle of multi-sensor information fusion, fusion process, fusion level, architecture and general fusion algorithm, constructs a sensor information fusion technology and its application model in biomedical detection, from the application framework, control structure of multi-sensor integrated system, information fusion, etc. The current situation of multi-sensor information fusion technology is studied in several aspects. An interoperability technology of sports health monitoring equipment based on multi-sensor information fusion is constructed. The experimental results show that the experimental efficiency is improved by 20% after using the application model in this paper, which has certain practicability.

The Application of Distributed Multi-Sensor Information Fusion Technology in Underwater Vehicle

2012 ◽  
Vol 532-533 ◽  
pp. 1006-1010 ◽  
Author(s):  
Ye Li ◽  
Yan Qing Jiang
Keyword(s):  
Mathematical Model ◽  
Kalman Filtering ◽  
Information Fusion ◽  
Underwater Vehicle ◽  
System Structure ◽  
Experimental Result ◽  
Fusion Technology ◽  
Fusion Algorithm ◽  
Single Sensor ◽  
Sensor Information

The application of distributed multi-sensor information fusion technology in accurate positioning of Underwater Vehicle was introduced in this paper. According to the system structure of Distributed multi-sensor in an AUV “T1”, this article establishes the Kalman filtering mathematical model, accomplishes the fusion algorithm based on Kalman filtering and a numerical simulation. The experimental result shows that the application of fusion algorithm based on Kalman filtering can avoid the limitations of a single sensor, reduce its uncertainty impact and increase the confidence level of data.

scholarly journals Multi-sensor Information Fusion Method Based on BP Neural Network

2016 ◽  
Vol 12 (05) ◽  
pp. 53 ◽  
Author(s):  
Lin Liandong
Keyword(s):  
Neural Network ◽  
Bayesian Inference ◽  
Information Fusion ◽  
System Development ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Fusion Algorithm ◽  
Temperature Detection ◽  
Posterior Expectation ◽  
Sensor Information

This study aims to solve the problem of multi-sensor information fusion, which is a key issue in the multi-sensor system development. The main innovation of this study is to propose a novel multi-sensor information fusion algorithm based on back propagation neural network and Bayesian inference. In the proposed algorithm, a triple is defined to represent a probability space; thereafter, the Bayesian inference is used to estimate the posterior expectation. Finally, we construct a simulation environment to test the performance of the proposed algorithm. Experimental results demonstrate that the proposed algorithm can significantly enhance the accuracy of temperature detection after fusing the data obtained from different sensors.

scholarly journals Application of Multi-sensor Information Fusion Technology on Fault Diagnosis of Electrical System

2017 ◽  
Vol 11 ◽  
pp. 05003
Author(s):  
Ling-Wen Meng ◽  
Ji-Pu Gao ◽  
Ming-Yong Xin ◽  
Jin-Mei Xiong ◽  
Guo Rui
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Fusion Technology ◽  
Electrical System ◽  
Sensor Information

Research on Vague Set of Target Threat Information Fusion Algorithm

2014 ◽  
Vol 599-601 ◽  
pp. 1671-1678
Author(s):  
Ke Hu Xu ◽  
Jin Yu Chen ◽  
De Peng Kong ◽  
Pu Fan
Keyword(s):  
Information Fusion ◽  
Scoring Function ◽  
Score Function ◽  
Quantitative Information ◽  
Uncertain Information ◽  
Fusion Technology ◽  
Fusion Algorithm ◽  
Information Process ◽  
Vague Set ◽  
Research Areas

Information fusion technology is one of the most active research areas currently, which is affected by the fact that the computer can only handle quantitative information and the result cannot reflect the actual feature of the target sometimes. This paper makes use of advantages of the vague set in dealing with uncertain information process to establish the target threat sequencing model based on vague set and take both quantitative and qualitative information of target into account. Using the improved scoring function, this paper comes up with the target threat sequence steps based on extreme score function method to provide a better data supporting for the decision-making function of information fusion technology.

The Methods of Information Acquisition and Information Fusion of the Photoelectric Sensor-Based Quadrotor Unmanned Aerial Vehicle

2020 ◽  
Vol 15 (1) ◽  
pp. 82-91
Author(s):  
Fen Hang ◽  
Xiangyang Hao
Keyword(s):  
Kalman Filter ◽  
Unmanned Aerial Vehicle ◽  
Kalman Filtering ◽  
Information Fusion ◽  
Information Acquisition ◽  
Reference System ◽  
Fusion Technology ◽  
Photoelectric Sensor ◽  
Aerial Vehicle ◽  
Sensor Information

When quadrotor unmanned aerial vehicle (UAV) is performing various tasks, even a small angular error will affect the evaluation of the entire motion trajectory. The multiple photoelectric sensor information fusion technology and the ARM microprocessor platform are used to form an attitude reference system for UAV. First, the hardware design of the small quadrotor UAV attitude reference system based on an ARM is introduced. The design framework and information acquisition module are expounded. In terms of the software of the system, the photoelectric sensor is used to receive different kinds of information, and the dynamic loading component is adopted as the solution to the interface diversification problems. Based on the attitude reference system, the collected information needs to be fused. The Kalman filtering is taken as the research object. Combined with the multiple photoelectric sensor information fusion technology, the Kalman filtering method is improved in the data preprocessing, and the low-pass filtering is added. Therefore, the abnormal data is filtered, and the estimated values are converged in a short time. Then, the data fusion is performed by the joint Kalman filter, least-squares fusion, and extended Kalman filter, respectively. During the experimental process, the system is proved to have good robustness, that is, in the case of individual sensor failure, the attitude acquisition section still obtains accurate attitude information of the UAV. The attitude reference system of UAV is realized. With the help of multi-sensor/information fusion technology, the attitude of the UAV is better handled, and its flight stability is improved.

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