| Paper Abstract and Keywords |
| Presentation |
2012-06-21 14:00
A Study on Generating Rules in a Situational Aware Smart Room
Yu-Cheng Lin (Univ. of Aizu), Rung-Ching Chen (Chao-Yang Univ. of Tech.), Qiangfu Zhao (Univ. of Aizu) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Ontology is a semantic technology. It can be used to describe knowledge and resources. In recent years, ontology-based systems are becoming very popular. They have been used in different domains (e.g., medication and mobile computing). An ontology-based system consists of an ontology model, an inference engine, and a rule base. In this architecture, users can easily use their ontology models and rules to solve their problems. Therefore, how to build the ontology model and generate the rules are very important. In context-awareness domain, several ontology models and systems have been proposed. These systems can automatically execute or change services based on the ontology model and the rule base. But existing method for generating the rules are still not efficient enough. The purpose of this paper is to study and provide a more efficient method for generating rules using basic context information. The basic context information includes four kinds of data, namely identifier, time, activity and location. In this paper, we investigate a basic method containing four steps. First, we define situation of the service (e.g. turn-on or turn-off the light). Second, we define the relationship between the situation and basic context information (e.g. the situation "user is in the room and time is evening" is related to the service "turn-on the light"). Third, we generate rules according to the relation found in the second step (e.g. if user is at room and time is evening, then turn-on the light). Fourth, we define priority of rules and resolve the conflicts between rules. We can define some special rules and control the service according to the priority of rules (e.g. energy saving rule). However, since each environment can be different from others, the rules should be adjusted according to the specific environment. If we can obtain other information, then we will add the information in basic context information and repeat step 2 to 4. Simulation results will be provided in the paper to show the efficiency of the above method. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Context-aware service / ontology / reasoning engine / C4.5 / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 112, no. 94, AI2012-2, pp. 7-12, June 2012. |
| Paper # |
AI2012-2 |
| Date of Issue |
2012-06-14 (AI) |
| Conference Information |
| Committee |
AI |
| Conference Date |
2012-06-21 - 2012-06-21 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
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| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Web Intelligence |
| Paper Information |
| Registration To |
AI |
| Conference Code |
2012-06-AI |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
A Study on Generating Rules in a Situational Aware Smart Room |
| Sub Title (in English) |
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| Keyword(1) |
Context-aware service |
| Keyword(2) |
ontology |
| Keyword(3) |
reasoning engine |
| Keyword(4) |
C4.5 |
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| 1st Author's Name |
Yu-Cheng Lin |
| 1st Author's Affiliation |
The University of Aizu (Univ. of Aizu) |
| 2nd Author's Name |
Rung-Ching Chen |
| 2nd Author's Affiliation |
Chao-Yang University of Technology (Chao-Yang Univ. of Tech.) |
| 3rd Author's Name |
Qiangfu Zhao |
| 3rd Author's Affiliation |
The University of Aizu (Univ. of Aizu) |
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| Speaker |
1 |
| Date Time |
2012-06-21 14:00:00 |
| Presentation Time |
30 |
| Registration for |
AI |
| Paper # |
IEICE-AI2012-2 |
| Volume (vol) |
IEICE-112 |
| Number (no) |
no.94 |
| Page |
pp.7-12 |
| #Pages |
IEICE-6 |
| Date of Issue |
IEICE-AI-2012-06-14 |
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