基于智能水龙头组成的网状传感器网络的家庭行为观察系统

Ryuichi Inoue, Hiroshi Yamamoto
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引用次数: 0

摘要

近年来,以智能家居为核心的设备迅速普及,有望应用于独居老人的日常活动观察、能源效率控制等支持居民日常生活的服务中。要实现智能家居,能够高精度、低成本地识别居民日常活动的系统必不可少。现有的研究提出了各种传感器的识别方法,如相机和超声波传感器,以估计生活行为。然而,现有的方法在隐私性和安装成本方面存在问题。因此,在本研究中,我们提出并开发了一种新的行为观察系统,该系统通过在家中不同位置放置支持无线通信的智能水龙头来估计居民的日常活动。智能水龙头具有测量和分析连接设备的功耗和智能水龙头之间无线电波接收信号强度的功能。此外,该系统利用一种短距离无线通信方式Thread构建了智能水龙头的网状网络,并通过采集和分析测量数据来估计居民的位置和行为。该系统仅通过分析电器功耗和无线电波接收信号强度的测量结果,实现了准确的行为估计,且无隐私问题,安装成本低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Household Behavior Observation System Utilizing Mesh Sensor Network Consisting of Smart Taps
In recent years, the devices focusing on the smart home have rapidly been spreading and have been expected to be applied to the services that support daily life of the residents such as the observation of daily activity of the elderly people living alone and controlling the energy efficiency. To realize the smart home, the system that can recognize daily activities of the residents with high accuracy and low cost is indispensable. The existing studies have proposed the recognition methods using various sensors such as cameras and ultrasonic sensors for estimating the living behavior. However, the existing methods have problems in terms of the privacy and installation cost. Therefore, in this study, we propose and develop a new behavior observation system that estimates daily activities of the residents by placing smart taps supporting the wireless communication on various places at home. The smart tap has a function of measuring and analyzing the power consumption of the connected devices and the received signal strength of radio waves between the smart taps. In addition, the system constructs a mesh network of the smart taps using the Thread, a type of short-range wireless communication, and the location and behavior of the residents are estimated by collecting and analyzing the measurement data. By analyzing only the measurement results of the power consumption of appliances and the received signal strength of the radio wave, the proposed system achieves accurate behavioral estimation with no privacy issues and low installation cost.
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