Application in Data Fusion of Internet of Things Based on the KL Distance of Reputation Model

2013 ◽  
Vol 760-762 ◽  
pp. 587-591 ◽  
Author(s):  
Xu Ping Zhu

The Internet of Things is a bearer network based on the Internet, the traditional telecommunications network, wireless self-organizing networks etc, so that all can be individually addressable ordinary physical objects to achieve the interconnection network. The Internet of Things is evolved from the wireless sensor network, which has limited resource in energy, memory, calculation, bandwidth and etc,. In addition, many applications in the Internet of Things are related to user privacy. In the process of data collection and transmission, the data may be forged , tampered, and a variety of other information security threats. In order to extend the network lifetime, to protect the authenticity and reliability of data fusion, this paper presents a reputation model of data fusion algorithm. The algorithm is verified by simulation, the experimental results show that the proposed algorithm is effective and the result of data aggregation is reliable.

2017 ◽  
Vol 13 (11) ◽  
pp. 25
Author(s):  
Jie Zhang

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">In order to prove the effect of data fusion technology in the Internet of things, a wireless sensor Internet of things security technology based on data fusion is designed, and the impact of data fusion in the field of communication technology is studied. Therefore, two security fusion algorithms are designed on the basis of analyzing and comparing the advantages and disadvantages of various security fusion algorithms, namely, data security fusion algorithm EDCSDA and approximate fusion algorithm PADSA. By analyzing the probability distribution model of the data collected by the nodes, the disturbance data is superimposed on the original data to hide the effect of the original data. A test bed system for perception layer of the Internet of things is designed and implemented. The test results prove the feasibility of the two algorithms. Meanwhile, it shows that the two algorithms can reduce the transmission overhead of the network while guaranteeing the security. Based on the above finding, it is concluded that data fusion technology is very effective for improving network efficiency and prolonging the network life cycle as one of the key technologies in the perception layer of Internet of things.</span>


2021 ◽  
Vol 2143 (1) ◽  
pp. 012030
Author(s):  
Duo Peng ◽  
Jingqiang Zhao ◽  
Tongtong Xu

Abstract Analyzed in this paper based on the Internet of things technology for intelligent building data, redundancy of data fusion are pointed out, based on the dynamic Kalman filter algorithm of multi-sensor fusion, first using the theory of fuzzy and covariance matching technique to adjust the noise covariance of traditional algorithm, combined with weighted minimum variance matrix under the optimal information fusion algorithm of data fusion, Finally, the simulation results show that this algorithm can effectively reduce the redundancy of intelligent data and make the estimated value of data fusion more close to the actual value.


Information ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 517
Author(s):  
Flávia C. Delicato ◽  
Tayssa Vandelli ◽  
Mario Bonicea ◽  
Claudio M. de Farias

In the Internet of Things (IoT), extending the average battery duration of devices is of paramount importance, since it promotes uptime without intervention in the environment, which can be undesirable or costly. In the IoT, the system’s functionalities are distributed among devices that (i) collect, (ii) transmit and (iii) apply algorithms to process and analyze data. A widely adopted technique for increasing the lifetime of an IoT system is using data fusion on the devices that process and analyze data. There are already several works proposing data fusion algorithms for the context of wireless sensor networks and IoT. However, most of them consider that application requirements (such as the data sampling rate and the data range of the events of interest) are previously known, and the solutions are tailored for a single target application. In the context of a smart city, we envision that the IoT will provide a sensing and communication infrastructure to be shared by multiple applications, that will make use of this infrastructure in an opportunistic and dynamic way, with no previous knowledge about its requirements. In this work, we present Heracles, a new data fusion algorithm tailored to meet the demands of the IoT for smart cities. Heracles considers the context of the application, adapting to the features of the dataset to perform the data analysis. Heracles aims at minimizing data transmission to save energy while generating value-added information, which will serve as input for decision-making processes. Results of the performed evaluation show that Heracles is feasible, enhances the performance of decision methods and extends the system lifetime.


Author(s):  
Xu Sun ◽  
Kunliang Shu

AbstractThere are often agricultural product quality problems in the production and circulation of agricultural products. Therefore, there are more and more people on the agricultural product supply chain based on the Internet of things. This article mainly introduces the research on the perception data fusion of agricultural product supply chain in the context of the Internet of things. This is a simple research result based on the Internet of things technology platform, which analyzes the current status of the product according to market demand. After analysis and comparison, a sensory data fusion model suitable for the supply chain of agricultural products is obtained, and information technology based on the Internet of things is used to transform and optimize the Internet of things in the circulation of agricultural products. The experimental results of this article show that data fusion technology based on the Internet of things can solve and track 69.45% of the problem of unknown sources of agricultural products, improve the supply efficiency of agricultural products by 43%, reduce the health problems of agricultural products by 31.24%, and reduce the prices of agricultural products by 13–20%. Improving logistics efficiency can save 5 million tons of agricultural products.


2020 ◽  
Vol 171 ◽  
pp. 105309 ◽  
Author(s):  
Andrei B.B. Torres ◽  
Atslands R. da Rocha ◽  
Ticiana L. Coelho da Silva ◽  
José N. de Souza ◽  
Rubens S. Gondim

Author(s):  
Benjamin Aziz Aziz ◽  
Paul Fremantle Fremantle ◽  
Alvaro Arenas Arenas

2014 ◽  
Vol 668-669 ◽  
pp. 1430-1433
Author(s):  
Cui Qing Jiang ◽  
Rui Ya Wang ◽  
Fa Xiang Chen ◽  
Zhao Wang

To provide siltation state information for dredging of urban sewer network, an evaluation method of siltation state based on data collected through the Internet of things is proposed. We present a data acquisition program, and use the adaptive weighted fusion algorithm as a data preprocessing method. Based on Manning formula, an assessment model of siltation state is established. The experiment proves that this assessment model of siltation state is effective for sewer network.


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