Design of a Prototype Neural Network for Smart Homes and Energy Efficiency

被引:21
作者
Teich, Tobias [1 ]
Roessler, Falko [1 ]
Kretz, Daniel [1 ]
Franke, Susan [1 ]
机构
[1] Univ Appl Sci Zwickau, D-08056 Zwickau, Germany
来源
24TH DAAAM INTERNATIONAL SYMPOSIUM ON INTELLIGENT MANUFACTURING AND AUTOMATION, 2013 | 2014年 / 69卷
关键词
Neural networks; learning systems; energy efficiency; smart homes;
D O I
10.1016/j.proeng.2014.03.032
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As a part of smart homes, a subsystem consisting of three components including a neural network is designed to provide personalized services. Unique factor combinations of building specifics, user profiles and external influences lead to the necessity of self-adaptive systems for personal comfort. The system supports room temperature control in order to heat rooms energy-efficiently at a set time. Smart home systems require a software architecture that allows services to be deployed on virtual and hardware devices. The design of automated processes is the first step of later programming and implementation into smart home systems that will automatically supervise and re-train its components and will also allow live feedback. (C) 2014 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:603 / 608
页数:6
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