Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院

Journal:Advances in Computer Science and Ubiquitous Computing

Key Words:Data fusion Ontology Sensor data fusion

Abstract:The paper proposes an ontology-based multi-sensor data fusion model framework for the wide application of multi-sensor data fusion, which uses ontology as the semantics model of data in the feature level data fusion to solve the heterogeneous problem of multi-source data. In the framework, an effective data processing algorithm is presented to preserve a reliable confidence level for data in a dynamic environment based on the requirements of data timeliness in real-time data fusion systems. Considering the uncertainty of fuzzy information, Transferable Belief Model (TBM) is used in the decision level of data fusion to achieve multi-source heterogeneous distributed data fusion. Finally, the effectiveness of the fusion framework and algorithm is verified via an example instance of onboard sensors data fusion.

ISSN No.:1876-1100

Translation or Not:no

Date of Publication:2017-12-01

Co-author:Wang, Shun,Li, Yan-hui,Zhang, Zhe,Wei, Zheng-xian

Correspondence Author:Kang Dazhou