Room occupancy detection: Combining RSS analysis and fuzzy logic

A. Baldini, L. Ciabattoni, R. Felicetti, F. Ferracuti, S. Longhi, A. Monteriù, A. Freddi
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引用次数: 9

Abstract

In this paper we focus our attention on the world of Internet of Things (IoT) objects and their potential for human indoor localization. Our aim is to investigate how Received Signal Strength (RSS) can be effectively used for identifying the position of a person at home, by exploiting common IoT communication networks. We propose a plug and play solution where the Anchor Nodes (ANs) are represented by smart objects located in the house, while the Unknown Node (UN) can be any smart object held by the user. The proposed solution automatically identifies the rooms where the smart objects are placed, by comparing a fuzzy weighted distance matrix derived from the anchor signals, with a threshold weighted distance matrix derived from the distances between rooms. The information can be easily integrated in any IoT environment to provide the estimation of the user position, without requiring the a priori knowledge of the positions of the anchor nodes.
房间占用检测:结合RSS分析和模糊逻辑
在本文中,我们将重点关注物联网(IoT)对象的世界及其在人类室内定位方面的潜力。我们的目标是通过利用常见的物联网通信网络,研究如何有效地利用接收信号强度(RSS)来识别家中人员的位置。我们提出了一个即插即用的解决方案,其中锚节点(ANs)由位于房屋中的智能对象表示,而未知节点(UN)可以是用户持有的任何智能对象。该方法通过比较锚点信号得到的模糊加权距离矩阵和房间间距离得到的阈值加权距离矩阵,自动识别智能物体所在的房间。这些信息可以很容易地集成到任何物联网环境中,以提供对用户位置的估计,而不需要对锚节点位置的先验知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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