Energy-saving Smart Home based on ZigBee and Fuzzy Neural Network

被引：2

作者：

Yuan, Bingjie ^{[1
]}

Ye, Shaozhen ^{[1
,2
]}

机构：

[1] Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350108, Fujian, Peoples R China

[2] Fujian Key Lab Med Instrumentat & Pharmaceut Tech, Fuzhou 350002, Fujian, Peoples R China

来源：

2017 INTERNATIONAL CONFERENCE ON GREEN INFORMATICS (ICGI) | 2017年

关键词：

energy conservation; smart home; ZigBee; fuzzy neural network; mixed reality; MANAGEMENT-SYSTEM; ALGORITHM;

D O I：

10.1109/ICGI.2017.29

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a novel smart home system integrating energy efficiency features. The paper firstly introduces the attempt tried by the power system and researchers for home energy-saving. Secondly the paper compares the performance of three kinds of network, and raised timing sleep, routing node rotation mechanism and data compression for ZigBee to conserve energy. Thirdly introduces three main sensors monitored to conserve energy and presents an experiment to find the optimal light intensity for healthy and sustainable lifestyle. Fourthly combines fuzzy neural network for energy-saving and puts forward the design and learning procedure for home controlling. At last it prospects the future research work about smart home visualized by mixed reality to achieve more ideal control.

引用

页码：191 / 198

页数：8

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