scholarly journals A Context-Aware System for Smart Home Applications

Author(s):  
Wen-Yang Wang ◽  
Chih-Chieh Chuang ◽  
Yu-Sheng Lai ◽  
Ying-Hong Wang
2013 ◽  
Vol 3 (2) ◽  
pp. 129-138 ◽  
Author(s):  
Willy Allègre ◽  
Thomas Burger ◽  
Jean-Yves Antoine ◽  
Pascal Berruet ◽  
Jean-Paul Departe

2015 ◽  
Vol 9 (11) ◽  
pp. 55-62 ◽  
Author(s):  
M. Humayun Kabir ◽  
M. Robiul Hoque ◽  
Hyungyu Seo ◽  
Sung-Hyun Yang

Author(s):  
Katsunori Oyama ◽  
Carl K. Chang ◽  
Simanta Mitra

Most of context models have limited capability in involving human intention for system evolvability and self-adaptability. Human intention in context aware systems can evolve at any time; however, context aware systems based on these context models can provide only standard services that are often insufficient for specific user needs. Consequently, evolving human intentions result in changes in system requirements. Moreover, an intention must be analyzed from tangled relations with different types of contexts. In the past, this complexity has prevented researchers from using computational methods for analyzing or specifying human intention in context aware system design. The authors investigated the possibility for inferring human intentions from contexts and situations, and deploying appropriate services that users require during system run-time. This paper presents an inference ontology to represent stepwise inference tasks, and then evaluate contexts surrounding a user who accesses PCs through a case study of the smart home environment.


2016 ◽  
Vol 10 (4) ◽  
pp. 65-76
Author(s):  
M. Humayun Kabir ◽  
M. Robiul Hoque ◽  
Hyungyu Seo ◽  
Sung-Hyun Yang

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Qin Ni ◽  
Ana Belén García Hernando ◽  
Iván Pau de la Cruz

We propose a three-layered context-aware architecture for monitoring activities of daily life in smart home. This architecture provides for the inclusion of functionalities that range from low-level data collection to high-level context knowledge extraction. We have also devised an upper-level ontology to model the context in which the activities take place. This enables having a common activity-related context representation, on which to infer and share knowledge. Furthermore, we have begun to implement a platform that realizes our architecture and ontology, making use of Microsoft’s Lab of Things (LoT) platform, being the preliminary results on this task also described in the paper.


2009 ◽  
Vol 20 (10) ◽  
pp. 2655-2666 ◽  
Author(s):  
Dong LIU ◽  
Xiang-Wu MENG ◽  
Jun-Liang CHEN ◽  
Ya-Mei XIA

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