Multi-source heterogeneous data fusion based on perceptual semantics in narrow-band Internet of Things

Abstract

With its strong coverage, small power consumption, low cost, and large connectivity, narrow-band Internet of Things technology has become the key technology in Internet of Things communication. However, in the face of a large number of terminals, the rational allocation of limited resources and the heterogeneous data fusion in the system become an important topic in the research of narrow-band Internet of Things. So a multi-source heterogeneous data fusion based on perceptual semantics in NB-IoT is proposed in this paper. Firstly, we introduce the advantages and key technologies of NB-IoT, which includes the key techniques of physical layer and media access control layer. Then, in order to eliminate data redundancy and extend the network lifetime, we analyze the centralized mode and distributed mode in NB-IoT network, and proposed a multi-source heterogeneous data fusion based on semantic perception to form a uniform format. Finally, an improved D-S evidence theory is adopted to proceed data fusion, obtaining the final fusion result. The experiment has shown that our proposed algorithm has faster convergence rate, higher stability, and its judgment to fusion results are more suitable to actual conditions.