A Time Based Markov Model for Automatic Position-Dependent Services in Smart Home
A smart home is likely in the near future. An important ingredient in an intelligent environment such as a home is automatic services, which means home system itself could know or predict what the inhabitant want to do, and so provide inhabitant the services automatically. Many researches reveal that most of the services in smart home are location-dependent so the automatic services must be built on the location awareness. In this paper we model inhabitant location pattern as a time based markov model (TMM). The simulation result shows that compared to the other models, the TMM has a set of benefits such as less time complexity, higher prediction accuracy and faster convergences rate. These benefits make TMM meets the requirements of automatic services in smart home.
Markov Model Location Awareness Automatic Service Smart Home
Yi Yang Zhiliang Wang Qiong Zhang Yang Yang
School of Information Engineering, University of Science and Technology Beijing, Beijing, 100083, Ch School of Information Engineering, University of Science and Technology Beijing, Beijing, 100083, Ch
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
2771-2776
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）