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Multi Sensor Data Fusion and Smart Decision Making Using Dempster-Shafer Theory: A Case Study

Journal: International Journal of Scientific Engineering and Research (IJSER) (Vol.7, No. 5)

Publication Date:

Authors : ; ;

Page : 27-31

Keywords : Data fusion; Decision making; Dempster-Shafer theory; Dempster- Shafer engine;

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Parallel distributed detection system consists of several separate sensor-detector nodes (separated spatially or by their principles of operation), each with some processing capabilities. These local sensor-detectors send some information on an observed phenomenon to a centrally located Data Fusion Center for aggregation and decision making. Several techniques are developed to combine data from sensor ? detector nodes. This article focuses on heterogeneous sensor data fusion using Dempster-Shafer evidence theory, which is one of the most effective approaches for sensor data fusion. The Dempster ? Shafer theory of evidence has uncertainty management and inference mechanisms analogous to our human reasoning process. This paper describes the use of Dempster- Shafer theory for multi sensor data fusion and demonstrates the easiness of using Dempster Shafer engine for obtaining inference through a simple case study.

Last modified: 2021-07-08 16:37:09