期刊
HELIYON
卷 5, 期 9, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.heliyon.2019.e02450
关键词
Computer science; Sensors data fusion; Wireless sensor networks; Neutrosophic sets; Sensors data correlations; Heterogeneous sensors; Occupancy detection; Random forest; LDA; Fuzzy genetic
Occupancy detection using ambient sensors has many benefits such as saving energy and money, enhancing security monitoring systems, and maintaining the privacy. However, sensors data suffers from uncertainty and unreliability due to acquisition errors or incomplete knowledge. This paper presents a new heterogeneous sensors data fusion method for binary occupancy detection which detects whether the place is occupied or not. This method is based on using neutrosophic sets and sensors data correlations. By using neutrosophic sets, uncertain data can be handled. Using sensors data fusion, on the other hand, increases the reliability by depending on more than one sensor data. Accordingly, the results of experiments applied using Random Forest (RF), Linear Discriminant Analysis (LDA), and FUzzy GEnetic (FUGE) algorithms prove the new method to enhance detection accuracy.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据