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A METHOD FOR HUMAN PRESENCE DETECTION AND ZONAL HUMAN SUBJECT LOCALIZATION IN WIRELESS SENSOR NETWORKS BASED ON DISTRIBUTED PROCESSING OF SHANNON ENTROPY IN THE SIGNAL STRENGH SPACE
A METHOD FOR HUMAN PRESENCE DETECTION AND ZONAL HUMAN SUBJECT LOCALIZATION IN WIRELESS SENSOR NETWORKS BASED ON DISTRIBUTED PROCESSING OF SHANNON ENTROPY IN THE SIGNAL STRENGH SPACE
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机译：基于信号熵空间中香农熵分布处理的无线传感器网络中人体出现和区域人体定位的方法
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摘要
The presented invention significantly improves the existing ambient intelligence solutions through the synthesis of radio-communication protocols and advanced statistical techniques for the radio signals processing, in order to detect human presence without the use of conventional sensor solutions. The method exploits the fact that the human body interferes with radio signals by introducing irregularities in the radio signature which indicate possible human presence, given in a form of received signal strength indicator's (RSSI) variations. According to this phenomenon, a human presence can be detected within a specific area, or in a particular zone, by providing the information to the system for unobtrusive interaction with the human subject in real-time. The idea is to apply the presented method for human presence detection to the network of novel, commercially available wireless LED bulbs, which are comprised of an embedded IEEE 802.15.4 transceiver module for wireless communication with other wireless devices. The proposed algorithm for human presence detection is implemented as a software module that can be easily incorporated into a variety of wireless systems (including the aforementioned smart LED bulbs, or any other wireless nodes) without high processing and memory loads of the system's resources. By incorporating the presented method, the original functionality of the wireless devices is extended with the possibility of device-free presence detection, which can be used for various ambient intelligence applications with very low installation costs. By applying the statistical techniques for signal processing, such as Shannon's information Entropy, combined with the incremental algorithm for extracting the principal components of the matrix of radio links (Candid Covariance-free Incremental Principal Component Analysis - CCIPCA), the implemented method can be integrated into any network of wireless devices, including the devices with low-power processing resources.
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机译：本发明通过综合无线电通信协议和用于无线电信号处理的高级统计技术，显着改善了现有的环境情报解决方案，从而无需使用传统的传感器解决方案就可以检测人的存在。该方法利用了这样的事实：人体通过在无线电签名中引入不规则性来干扰无线电信号，该不规则性以接收信号强度指示符（RSSI）变化的形式给出，该不规则性指示人类可能存在。根据该现象，可以通过将信息提供给系统以实时地与人类对象进行不干扰的交互，从而在特定区域或特定区域中检测到人类的存在。该想法是将所提出的用于人类存在检测的方法应用于新颖的，可商购的无线LED灯泡的网络，该灯泡由嵌入式IEEE 802.15.4收发器模块组成，用于与其他无线设备进行无线通信。所提出的用于人类存在检测的算法被实现为软件模块，该软件模块可以轻松地并入各种无线系统（包括上述智能LED灯泡或任何其他无线节点）中，而不会占用系统资源的大量处理和存储负载。通过合并所提出的方法，无线设备的原始功能得以扩展，并具有无设备存在检测的可能性，该设备可以以非常低的安装成本用于各种环境智能应用。通过将诸如Shannon信息熵之类的统计处理技术应用于信号处理，并结合用于提取无线电链路矩阵的主成分的增量算法（Candid-Covariance-Free Incremental Main Component Analysis-CCIPCA），可以集成所实现的方法进入任何无线设备网络，包括具有低功耗处理资源的设备。
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