Support Vector Machine for Smart Home

• Main Authors: Ping-Lun Liao, 廖柄
• Other Authors: 鄭錦聰
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/zkdgmm

碩士 === 國立虎尾科技大學 === 資訊工程研究所 === 98 === Smart Home is based on the research of home digitization for human beings. The related researches report that context awareness is able to achieve the applications for a variety of scenarios and perform specific functions, which results in a more comfortable and convenient environment. In addition, the integration system can save energy and lower cost. Therefore, a model for integrating Bluetooth, Zigbee, Universal Serial Bus, WiFi standards is proposed. Those wireless technologies are used for gathering data. To simulate the scenarios of Smart Home, the proposed system substitute CPLDs for home appliances. Machine learning is a theory that enhances a computer system''s knowledge. Support Vector Machines is a machine learning theory that has two major functions that are classification and regression analysis. To enhance the system''s intelligence, Wavelet Support Vector Machine is applied to the system. Besides, the system will be designed by Object-Oriented Design and be analyzed by Object-Oriented Analysis. Therefore, the proposed system will be modeled by Unified Modeling Language. C# is chosen to be the Object-Oriented Language that implements the system software. The experimental results suggest that the proposed model is feasible.