Fault Matters: Sensor data fusion for detection of faults using Dempster–Shafer theory of evidence in IoT-based applications

作者：

Highlights：

• Applying Dempster–Shafer Theory for fault detection.

• A new mass function based on normal distribution for Dempster’s Combination Rule.

• Demonstration of experimental test-bed containing sensors and microcontroller.

• Verifying the applicability of the proposed method on multiple data sets.

摘要

•Applying Dempster–Shafer Theory for fault detection.•A new mass function based on normal distribution for Dempster’s Combination Rule.•Demonstration of experimental test-bed containing sensors and microcontroller.•Verifying the applicability of the proposed method on multiple data sets.

论文关键词：Classification,Data fusion,Dempster–Shafer,Fault detection,Internet of Things (IoT)

论文评审过程：Received 8 April 2020, Revised 28 July 2020, Accepted 13 August 2020, Available online 22 August 2020, Version of Record 10 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113887